What is Automatic Identification and Data Collection (AIDC)?

Automatic identification and data collection—sometimes also referred to as automatic identification and data capture—is a category of related technologies used to collect data without manual intervention. Data can be collected from an individual person or from an object, image, or sound, among other things. From unlocking your phone to scanning groceries at the self-checkout aisle, chances are you interact with AIDC technologies every day.

Consider some of the most common applications of AIDC technology and how often you encounter them:

• Barcodes and QR codes
• Magnetic stripes (credit cards, hotel key cards)
• RFID chips
• Biometrics (fingerprint scanners, facial recognition)

The use of AIDC technology can enhance efficiency and security and improve the accuracy and reliability of collected information. Many organizations use AIDC in an extensive array of applications, from inventory management to product tracking to secure access and ID control to interactive product marketing.

How Does AIDC Work?

AIDC works by orchestrating a series of technologies—hardware, software, and communication protocols—to create a seamless flow of data identification and collection processes. These processes are carried out in several stages.

Data Encoding and Capture

Many AIDC use cases start with users interacting directly with a device to scan a QR code or undergo a biometric scan—for example, when logging securely into a PC or operating system. This might be for accessing product information or gaining secure access to physical spaces or digital platforms.

In all scenarios, AIDC starts with encoding relevant information into a specific data format for processing. This can take the form of barcodes and biometric identifiers or similar encoding formats such as quick response (QR) codes and radio frequency identification (RFID) chips like those found in toll booth transducers.

The encoded data encapsulates various attributes like user authentication credentials, product details, manufacturing dates, pricing, or geographical location. Specialized devices designed to capture the encoded data from physical objects or entities are then used to read the data.

Data Transmission and Processing

Captured AIDC data is then sent to a designated system or server for real-time data processing over a wired connection such as USB and ethernet, or using wireless technologies like WiFi, Bluetooth, and cellular networks.

Once transmitted, the collected data undergoes various processing activities, typical data validation, analysis, transformation, and integration into overarching enterprise systems like customer relationship management (CRM) systems or business intelligence (BI) platforms. This crucial phase converts raw data from the field into actionable insights for guiding strategic decision-making processes.

What is AIDC Used For?

Due to its general automation benefits and adaptability to specific industries and use cases, AIDC has become a staple in a wide range of applications and industries, from retail and logistics to healthcare and finance. Here are some of the most common enterprise applications for AIDC.

Identification, Access Control, and Security

Biometric AIDC systems ensure secure access to physical spaces, computer networks, and confidential information. One of the earliest and most common AIDC use cases involves using a key card to access an office building.

Manufacturing, Logistics, and Warehousing

AIDC enhances production efficiency by enabling the real-time tracking of raw materials, work-in-progress items, and finished goods, resulting in streamlined operations and reduced downtime. For example, supplier data, material inventory levels, and machine performance can be accessed and tracked throughout the production process using a combination of AIDC technologies—typically IoT and sensor devices. Once items, products, or orders are assembled, AIDC facilitates precise shipment tracking, reducing errors, enhancing order fulfillment, and enabling efficient route optimization.

Medicine and Healthcare

Even the most typical, non life-threatening medical and healthcare scenario calls for minimal errors and an exceedingly high degree of accuracy and precision. To this end, AIDC is being used to quickly onboard new patients—for example, scanning and updating patient status and vitals quickly through different departments—and proactively track patient health and wellness. It’s also used widely in medication management through the use of auto-refilling prescriptions using QR codes and medical equipment monitoring.

Parking and Transportation

AIDC-based systems are employed in toll collection, electronic ticketing, and vehicle identification, enhancing traffic management and reducing congestion. For city dwellers in particular, AIDC is a highly visible, common fixture—from barcode scanning solutions for access control to parking lots to barcode-based ticket validation devices at train stations.

Retail and Inventory Management

AIDC technologies like barcodes and RFID tags have revolutionized inventory tracking, enabling retail and shipping enterprises to implement real-time stock monitoring and more efficient supply chain management.

AIDC Types

AIDC encompasses a diverse array of technologies, each catering to distinct requirements and industries. The following is an overview of the most prominent types.

Barcodes

Barcodes are the oldest, most basic of AIDC types, invented over 70 years ago. The technology itself has changed relatively little since then—barcodes consist of patterns of parallel lines of varying widths that together represent data when scanned by a barcode reader. These days, this elemental AIDC type is a cornerstone of retail and inventory management, offering a cost-effective and efficient solution for standardized data collection across industries.

Biometrics

Biometric AIDC uses a person’s unique physiological or behavioral traits for identification purposes. Common biometric identifiers include fingerprints, iris patterns, facial features, voiceprints, and even gait patterns derived through visual analysis. The Biometrics Institute has defined 16 different types of biometrics for automatically identifying people by their unique physical characteristics.

Because they offer a high level of security and accuracy, biometrics are ideal for applications that demand stringent security and strong authentication measures (e.g., secure access control, employee time tracking, and identity verification).

The Biometrics Institute has identified and defined 16 types of biometrics that can be used to automatically identify people by their unique physical characteristics.

Near Field Communication (NFC)

NFC is a subtype of RFID that enables short-range communications between devices. NFC-enabled devices can establish connections by being in close proximity, typically within a few centimeters, for applications in contactless payment systems, access control, and data exchange between devices like smartphones and point-of-sale terminals.

QR Codes

A close cousin of the barcode, the QR code was developed for parts tracking during the automobile assembly process. These two-dimensional barcodes are capable of storing more data than traditional linear barcodes and can support a wide range of data types, including website URLs, contact information, product details, and more. QR codes have gained immense popularity due to their versatility, enabling marketers to engage customers with interactive content and information.

RFID

RFID technology uses radio frequency signals to enable wireless communication between an RFID tag and a reader. RFID tags come in passive and active form. Passive tags derive power from the reader’s signal and are suitable for applications like inventory management and supply chain tracking. Active tags have their own power source and can transmit data over longer distances, making them suitable for scenarios such as vehicle tracking and large-scale logistics.

Benefits of AIDC

Though AIDC technologies have been around for some time, they remain relevant due to their balance of simplicity, efficiency, security, and affordability. Each of the many types of AIDC offers a unique set of advantages—they should be selected based on application requirements, industry standards, and specific security considerations, among other factors. Regardless of the type, firms that implement AIDC technologies generally realize a wide range of benefits. Here are some of the most prominent.

Accuracy and Efficiency

AIDC systems virtually eliminate errors associated with manual data entry, leading to more accurate and reliable data collection. By eliminating typos and human mistakes, organizations can achieve a high level of data accuracy and more reliable strategic decision-making. The automation of data collection reduces the time required to gather information, allowing employees to focus on more high order, value-added tasks. This optimization of human resources in turn boosts the enterprise’s overall operational efficiency.

Enhanced Customer Experience

AIDC technologies are especially prevalent in retail environments where they enhance customer experiences by simplifying processes like product information requests and checking out/completing purchases. By expediting and automating these previously high-touch interactions, AIDC helps to enhance customer satisfaction and loyalty through shorter wait times and smoother interactions.

Real-Time Insights and Inventory Management

AIDC technologies provide real-time data, enabling businesses to make informed decisions promptly. This agility enables organizations to respond promptly to changing conditions in response to market conditions and competitive activity. In retail, logistics, and warehousing, AIDC expedites and streamlines inventory tracking, helping to minimize stock-outs and reduce excess inventory. The results are leaner operations and improved levels of customer satisfaction.

Stronger Security

Biometric AIDC technologies ensure secure access to sensitive physical areas and environments, safeguarding both tangible and digital assets. By relying on unique physiological identifiers for authentication, biometric AIDC ensures that only authorized personnel are granted access to sensitive physical areas and online/offline resources.

Bottom Line: Automating ID and Data Collection

Despite being a relatively older set of technologies, automated identification and data collection (AIDC) continues to drive innovation and operational efficiency in modern enterprises and industries. Businesses apply the wide range of technologies to an even wider range of use cases that automate data collection, enhance accuracy, streamline operations, and improve security.

Because it’s cost effective to implement, accurate, generally easy to use, and useful in many different applications, AIDC has become an indispensable tool in today’s data-driven world and will likely hold its place for the indefinite future.

To learn more about software to help turn collected data into actionable insights, read Top 7 Data Analytics Tools next.

What are IoT Protocols and Standards?

IoT protocols are established rules about how IoT devices should work and communicate. Standards are similar to protocols, but are used more widely—across an entire industry, for example. Together they ensure that all IoT devices have a minimum level of compatibility with one another and with other related devices and applications.

For instance, a manufacturer might use two different IoT sensors from different brands. As long as both companies follow the same guidelines, the sensors will work on the same network. IoT protocols and standards typically function in a single layer as a distinct part of a larger network—most commonly in the application and middleware layers of a standard five-layer network architecture, although not exclusively. For example, Bluetooth and Wi-Fi operate on the network layer.

Commercial IoT Standards and Protocols

Commercial IoT is a huge, still-growing industry. Interest in smart home tech is creating high demand for devices in the consumer electronics market. As a result, protocols and standards are emerging to ensure consumers get a streamlined, user-friendly experience. While some of these standards are also used in industrial applications, their biggest benefits stand out most in commercial settings. A few commercial IoT standards and protocols are so widely used they have become ubiquitous—like Bluetooth and Wi-Fi, for example.

Bluetooth

It’s hard to imagine consumer electronics today without the Bluetooth standard for wireless device-to-device communication. Every new smartphone, tablet, and laptop includes Bluetooth support as a standard feature.

Bluetooth was one of the first IoT communication protocols to open the door for a boom in consumer IoT devices, such as smartwatches and wireless headphones. It uses wireless personal area networks (WPANs), allowing for short-range data transmission using radio waves.

Bluetooth was originally standardized by the world’s largest technical professional organization, the IEEE, in 2005 under standard IEEE 802.15.1. Though updates ceased in 2018, Bluetooth remains an extremely popular IoT protocol—particularly among consumer electronics.

Data Distribution Service (DDS)

The Data Distribution Service (DDS) protocol and standard is designed for communication across hardware and software platforms. Its main benefits include easy scalability, high reliability, and low-latency connectivity. DDS is great for ensuring all the IoT components in a system can maintain high-quality data transfers.

DDS is popular across commercial and industrial IoT applications. Originally published in 2004 by the Object Management Group, which maintains it today, it is a middleware protocol for standardizing machine-to-machine communication using the publisher-subscriber model.

Matter

Matter is a communication and interoperability standard designed to address the issue of smart home device communication between brands. Many commercial device manufacturers want consumers to buy all their smart home devices from one brand. This isn’t necessarily in the consumer’s best interest, but poor communication between products from different companies may force them to pick a single brand.

Matter ensures that smart home devices from participating manufacturers work together natively. It benefits both manufacturers and consumers. Since companies don’t have to be a one-stop shop, they can instead focus on making great smart thermostats, for example, without worrying about losing money to a competing brand that also makes other products.

Wi-Fi

Wi-Fi is among the oldest IoT standards and one of today’s most well-known and widely used. Its invention dates back to 1942, when actress and inventor Hedy Lamarr patented frequency hopping. It evolved over the decades until the first WiFi standard was created in 1997.

This first set of standards established the Wi-Fi we know today. The IEEE 802.11 family of standards outlines how communication over wireless local area networks (WLANs) should work. It also establishes a minimum data transfer speed of 2 megabytes per second. The IEEE continues to maintain the 802.11 standards, and Wi-Fi is still found in most consumer electronics and commercial IoT devices, such as smart home appliances and sensors.

XMPP

Extensible Messaging and Presence Protocol (XMPP) was originally developed for human-to-human communication in 2002. In the 20-plus years since, it has evolved into a machine-to-machine communication protocol popularly used by smart appliances.

Today, XMPP is an open-source protocol maintained by the XMPP Standards Foundation. It’s a lightweight middleware system that standardizes communication and XML data. XMPP runs in the application layer, where it can provide near-real-time data transfers. This responsiveness, combined with XMPP’s high accessibility, makes it ideal for communicating with smart home devices like appliances.

Industrial IoT Standards and Protocols

The industrial IoT market is among the strongest-performing in the world, which should come as no surprise given the countless applications of IoT in manufacturing, logistics, and construction. Industrial IoT (IIoT) is considered its own distinct niche.

IIoT standards and protocols are becoming increasingly important as businesses grow to rely on their IoT devices more. For instance, a manufacturer in a smart factory might use IIoT sensors to send maintenance alerts, which could affect employee safety. IoT communication standards ensure sensors send real-time alerts successfully, regardless of the brand or model.

Constrained Application Protocol (CoAP)

Constrained Application Protocol, or CoAP, is a protocol that allows IoT devices to use HTTP without excessive power consumption. Launched in 2013, it’s  popular for machine-to-machine (M2M) communication—particularly in industrial applications like supply chain environments.

CoAP lets industrial users include a wider variety of IoT devices in their networks without being restricted by low power capabilities or bandwidth. Its main drawback is a lack of security features. CoAP is somewhat exposed on its own and needs the additional datagram transport layer security (DTLS) protocol to ensure secure data transmission.

Lightweight M2M (LWM2M)

Lightweight M2M, or LWM2M, is a protocol specifically for remote device management in IoT or machine-to-machine environments. It is purpose-built for IoT sensors, making it a highly useful protocol for industrial applications. Its light weight means it doesn’t require much power, storage, or computing resources to run.

LWM2M was originally published in 2017 and is still active and maintained by OMA SpecWorks. The 2020 update to the protocol added compatibility with edge networking and 5G, making LWM2M a cutting-edge standard for today’s industrial environment. LWM2M works over TCP/TLS, MPTT, and HTTP.

MQTT

MQTT is an application-layer protocol for machine-to-machine communication using the publisher-subscriber model. It was developed in 1999 and is a popular open-source protocol for standardizing communication between industrial IoT devices.

MQTT is particularly well-suited for IIoT sensors due to its lightweight nature and tolerance for low bandwidth. Since it doesn’t require much memory space, MQTT is highly compatible with the full range of IIoT devices. It essentially acts as a bridge to applications.

Zigbee

Zigbee is a highly popular network protocol specifically for mesh networks used in automation. Consumer and industrial devices use Zigbee, although its emphasis on automation and various applications makes it ideal for business. It was developed by the Connectivity Standards Alliance, which also created Matter.

Zigbee’s top benefits include low power consumption and a high degree of flexibility. It’s designed for short range, similar to Bluetooth. One feature that’s particularly beneficial in the industrial space is its high level of security. Zigbee includes encryption and authentication by default while staying lightweight. This means industrial users can build a mesh network of IoT devices with security features without using excessive power and computing resources.

Security IoT Standards and Protocols

Cybersecurity standards have always played an important role in the IoT’s development and growth. Some communication-related protocols include security features, but this isn’t always the case. A growing pool of IoT protocols and standards is designed to emphasize cybersecurity. Some of these are add-on rulesets for other offerings—for instance, Wi-Fi Protected Access 2 is one of today’s leading network security protocols to add to Wi-Fi.

Ascon (NIST)

Ascon is the National Institute of Standards and Technology’s (NIST) official standard for IoT encryption, selected in 2023. It is now the formal standard in the U.S. for securing IoT devices and communications.

Ascon is a collection of cryptographic algorithms that provide highly secure encryption without requiring high amounts of power and computing. Implementing Ascon can help IoT device manufacturers be more proactive about preventing cyberattacks and vulnerabilities rather than just responding to them.

DTLS

Datagram Transport Layer Security, or DTLS, is a security protocol for encrypted communications. A datagram is a standard data transfer unit, such as a single message—they are commonly used in gaming, streamed video, or videoconferencing applications.

Designed by the Internet Engineering Task Force, DTLS secures wireless communications so senders and receivers know their messages won’t be intercepted or spied on. It’s a commonly used protocol across commercial and industrial spaces.

Z-Wave

Z-Wave is a proprietary alternative to protocols like Bluetooth and Wi-Fi designed for encrypted mesh network communications, offering more security than its open-source counterparts. It functions on various low-level radio frequencies.

Z-Wave is popular among smart home automation systems, particularly those focusing on security. It is primarily used in consumer electronics and commercial applications but can also be used in industrial environments.

Bottom Line: Understanding IoT Protocols and Standards

IoT devices are a common part of people’s lives. They’re in our homes, our doctors’ offices, our oceans and skies, and businesses increasingly rely on them for a wide range of purposes. Day in and day out, these devices generate massive volumes of data used for business intelligence, competitive analysis, more efficient manufacturing, consumer feedback, and more. Dozens of protocols and standards run in the background to ensure that these devices and sensors work smoothly and securely and can communicate with each other effectively—understanding these protocols can help enterprises make better purchase decisions and build more secure, robust IoT networks.

Read next: Top 7 IoT Analytics Platforms

Experts predict 175 zettabytes of data worldwide within two years, much of it coming from IoT (Internet of Things) devices. Companies of all sizes should expect significant troves of data, most of it unstructured and not necessarily compatible with system of record (SOR) databases that have long driven mission-critical enterprise systems like enterprise resource planning (ERP).

Even unstructured data should be subject to many of the same rules that govern structured SOR data. For example, unstructured data must be secured with the highest levels of data integrity and reliability if the business is to depend on it. It must also meet regulatory and internal governance standards, and it must be able to move freely among systems and applications on clouds, internal data repositories, and mobile storage.

To keep pace with the enormous demands of managing voluminous high velocity and variegated data day-in and day-out, software-based tools and automation must be incorporated into data management practices. Newer automation technologies like data observability will only grow in importance, especially as user citizen development and localized data use expand.

All of these forces require careful consideration as enterprise IT builds its data management roadmap. Accordingly, here are seven emergent data management trends in 2023.

Hybrid End-to-End Data Management Frameworks

Enterprises can expect huge amounts of structured and unstructured data coming in from a wide range of sources, including outside cloud providers; IoT devices, robots, drones, RF readers, and MRI or CNC machines; internal SOR systems; and remote users working on smart phones and notepads. All of this data might be committed to long- or short- term storage in the on-premise data center, in a cloud, or on a mobile or distributed server platform. In some cases, real-time data may need to be monitored and/or accessed as it streams in real time.

In this hybrid environment, the data, its uses, and its users are diverse—data managers will need data management and security software that can span all of these hybrid activities and uses so data can be safely and securely transported and stored point to point.

IBM is a leader in the data management framework space, but SAP, Tibco, Talend, Oracle, and others also offer end-to end data fabric management solutions. A second aspect of data management is being able to secure data, no matter where it is sent from or where it resides—end-to-end security mesh software from vendors such as Fortinet, Palo Alto Networks, and Crowdstrike can meet this need.

The Consolidation of Data Observability Tools

Because many applications now use multiple cloud and on-premises platforms to access and process data, observability—the ability to track data and events across multiple platform and system barriers with software—is a key focus for enterprises looking to monitor end-to-end movements of data and applications. The issue with most organizations that are using observability tools today is that they are using too many different tools to effect end-to-end data and application visibility across platforms.

Vendors like Middleware and Datadog recognize this and are focused on delivering integrated, “single pane of glass” observability tool sets. These tools enable enterprises to reduce the number of different observability tools they use into a single toolset that’s able to monitor data and event movements across multiple cloud and on premises systems and platforms.

Master Data Management for Legacy Systems

As businesses move forward with new technologies, they face the challenge of figuring out what to do with older ones. But some of those continue to provide value as legacy systems—systems that are outdated or that continue to run mission-critical functions vital to the enterprise.

Some of these legacy systems—for example, enterprise resource planning (ERP) systems like SAP or Oracle—offer comprehensive, integrated master data management (MDM) toolsets for managing data on their cloud or on-premises solutions. Increasingly enterprises using these systems are adopting and deploying these MDM toolsets as part of their overall data governance strategies.

MDM tools offer user-friendly ways to manage system data and to import data from outside sources. MDM software provides a single view of the data, no matter where it resides, and IT sets the MDM business rules for data consistency, quality, security, and governance.

Data Management Using AI/ML

While the trend of using artificial intelligence and machine learning (AI/ML) for data management is not new, it continues to grow in popularity driven by big data concerns as the unprecedented volume of data enterprises are faced with managing collides with an ongoing staffing shortage across the tech industry as a whole—especially in data-focused roles.

AI and ML introduce highly valuable automation to manual processes that have been prone to human error. Foundational data management tasks like data identification and classification can be handled more efficiently and accurately by advanced technologies in the AI/ML space, and enterprises are using it to support more advanced data management tasks such as:

• Data cataloging
• Metadata management
• Data mapping
• Anomaly detection
• Metadata auto-discovery
• Data governance control monitoring

As AI/ML continues to evolve, we can expect to see software solutions that offer intelligent, learning-based approaches including search, discovery, and capacity planning.

Prioritizing Data Security

In the first quarter of 2023, over six million data records were breached worldwide. A data breach can destroy a company’s reputation, impact revenue, endanger customer loyalty, and get people fired.This is why security of all IT—especially as more IT moves to the edge and the IoT—is an important priority for CIOs and a major IT investment area.

To meet data security challenges, security solution providers are moving toward more end-to-end security fabric solutions. They are offering training for employees and IT, since increases in user citizen development and poor user security habits can be major causes of breaches.

Although many of these security functions will be performed by the IT and network groups, clean, secure, and reliable data is foremost a database administrator, data analyst, and data storage concern as well.

Automating Data Preparation

The exponential growth of big data volumes and a shrinking pool of data science talent is stressing organizations. In some cases, more than 60 percent of expensive data science time is spent cleaning and preparing data.

Software vendors want to change this corporate pain point with an increase in data preparation and cleaning automation software that can perform these tedious, manual operations. Automated data preparation solutions ingest, store, organize, and maintain data, often using AI and ML, and can handle such manually intensive tasks as data preparation and data cleansing.

Using Blockchain and Distributed Ledger Technology

Distributed ledger systems enable enterprises to maintain more secure transaction records, track assets, and keep audit trails. This technology, along with blockchain technology, stores data in a decentralized form that cannot be altered, improving the authenticity and accuracy of records related to data handling. This includes financial transaction data, sensitive data retrieval activity, and more.

Blockchain technology can be used in data management to improve the security, shareability, and consistency of data. It can also be used to provide automatic verification, offering avenues to improve data governance and security.

Bottom Line: The Future of Data Management

As businesses confront the need to collect and analyze massive volumes of data from a variety of sources, they seek new means of data management that can keep pace with the expanding need. Cutting edge technologies like AI/ML and blockchain can be used to automate and enhance some aspects of data management, and software vendors are incorporating them into their platforms to make them an integral part of the work. As new technologies continue to evolve, data management methods will evolve with them, integrating them into processes driven by increasing demand.

Read next: Structured Data: Examples, Sources, and How it Works

Samuel Pasquier Q&A

How Did You First Start Working In The IoT Market?

In November 2015, after having spent 10 plus years working in Cisco’s Enterprise switching product lines. I wanted to expand my scope and take on a new challenge with a new market. Cisco offered me this opportunity and It’s been an amazing 8 plus years.

What Is Your Favorite Thing About Working At Cisco?

It’s hard to pick one thing, but I can break it down to three main things. I love the IoT space and the technologies we build. Every day I’m working with customers and our internal teams to connect people and the physical world with great technology to create a better future for everyone. That brings me to number two – and that’s the people. I love our teams who bring their amazing experience, spirit, and dedication to helping our customers achieve success. We do that with a lot of hard work and also fun mixed in. And I can’t leave out Cisco. It’s a great company to work for with great values and amazing leadership. We continually win Best Place to Work and I do feel that way about the company as well.

What Sets Cisco’s IoT Approach Or Solutions Apart From The Competition?

Cisco understood very early on that to get the promise of IoT, you need to get people working together. For us, that’s usually the IT teams that have built out decades of networking infrastructure collaborating with the operational technology (OT) teams. These OT teams are running the manufacturing sites, power grids, highway departments, mines, ports, and so many other industries where technology is empowering the operations. That’s where we really stand apart from the competition—combining decades of Cisco networking experience with our expertise in these operational settings.

The IoT Market

What Is One Key New IoT Technology That Particularly Interests You?

IoT isn’t a single technology. It’s more an umbrella term about how technologies can be leveraged to help drive outcomes for organizations. It’s about connecting IT to the physical world to improve business outcomes, make operations more efficient, and make the world safer and more secure.

The interesting part for me is exactly that—that IoT is a set of technologies that need to work together and that we get to spend our days figuring out how to constantly improve on that.

Asking me to pick one is like being asked to pick your favorite child. If I have to pick, I would say LoRaWAN (Editor’s note: low-power, wide area networking protocol built on top of the LoRa radio modulation) as it’s a disruptive technology that enables new use cases that were not previously affordable.

What Is One New IoT Technique That Teams Should Implement?

For me, it’s not so much a question of technique but a question of culture. Our customers have teams with very different backgrounds and responsibilities. You need to find ways for them to collaborate and work cross functionally to digitize their processes.

What Is One New IoT Strategy That Companies Should Implement?

Over the last 8 years working within the IoT space, I have observed that the most successful companies leveraging technology to improve their business have really started by changing the way they look at the problem. They create internal organizations with a mix of skills/experience/expertise. Then they are able to have these interdisciplinary teams work together to solve their key challenges without the boundaries of internal team organization. So to be successful, organizations first need to have the right people organization to lead the change.

What Is The Biggest IoT Mistake You See Enterprises Making?

I have seen a lot of enterprises creating some digitization offices, or innovation teams to help transform the business. Unless it’s really built-in to the business/organizational entities, it generally has a very hard time to go beyond the proof-of-concept phase. We all love great ideas but enterprises need to have teams involved that can scale and deploy the solutions as well.

What Are Some Current Trends In The IoT Market That Are Promising?

As we look to the future, we see clear trends in industrial operations—more use of cloud-based applications, virtualization of control functions, and more artificial intelligence/machine learning (AI/ML)–powered analytics. Software-defined approaches will use software to manage and optimize the entire manufacturing process, including product design, scheduling, supply chain management, quality control, and maintenance. “Digital twin” technology will simulate a product from its design, production, and performance when deployed and optimizes the product and production system before investment in physical prototypes and building of assembly lines.

These uses are possible only through high-performance networking, built-in security, and machine-to-cloud connectivity. I am proud to say that Cisco Industrial Ethernet switches and the rest of our IoT portfolio is gearing up to lead this charge.

What Are The Biggest Factors That Are Driving Change In IoT?

I can’t overstate the impact of security on the IoT market. Organizations need to accelerate their security posture in the networks and operational spaces. Cybersecurity remains one of the top drivers in the IoT space. As they look to digitize their operational environments, they need to do this with security built in.

The collaboration between IT and OT is also accelerating. As organizations digitize and transform their operational settings, these teams are coming together to leverage existing technology investments and their collective expertise.

Another leading factor is supporting organizations on their sustainability journey. New types of initiatives like electric vehicle (EV) charging networks, energy storage, and carbon capture and storage are becoming more common.

How Has IoT Changed During Your Time In The Market?

I’ve seen first-hand the shift from awareness of IoT technologies to a progression of proof of concepts and now the acceleration of deployments across industries.

It was 20 years ago, March 2003, that we launched our first industrial ethernet switch and entered the industrial networking market. At that time, we arrived to support industrial organizations in adopting IP connectivity throughout their operations, along manufacturing lines, inside electric substations, deep inside mines and beyond. The past two decades have brought an explosion in the number and variety of applications that IT and operational technology teams are supporting—often in some of the wettest, dustiest, non-climate-controlled places on Earth.

Personnel in IoT

If You Could Give One Piece Of Advice To An IoT Professional In The Beginning Of Their Career, What Would It Be?

I’d say that you should accept that you need diverse expertise to be successful in an IoT Project. It’s not about IT vs OT. It’s IT + OT + security teams working together.

With The Shortage Of Tech Talent, How Is Your Team Finding And Retaining Professionals To Work In IoT?

Cisco has extensive programs to ensure that we attract and retain great talent across the organization, from our university hiring programs, veteran programs, return to work, and more. For us in IoT, my teams tell me that the reason they love working is seeing first hand the great outcomes we are delivering for our customers. With IoT, you get the benefit of seeing first-hand how IoT is improving organizations—more efficient manufacturing plants, weaving renewables into the grid, making the roads safer, and more.

For The Greatest Business Impact, What Should IoT Professionals Be Focusing On Most In Their Roles?

To bring the greatest business impact, IoT professionals should think about scale and operational aspects from the beginning of any project. Proof of concepts are easy; production deployment at scale that will need years of support are much harder.

Work-Life

What Is One Of Your Top Professional Accomplishments?

I take great pride in building great teams and getting everyone to work together. We spend so much of our time at work. It’s really important to have teams that work with great people accomplishing great things.

What Is Your Favorite Part Of Working In The IoT Market?

I love how we can leverage technology to solve a real customer problem. In a world that is more virtual than ever, it’s nice to see the very direct impact of technology with the physical world. Seeing a tangible outcome makes the work likewise tangible and rewarding.

What Is One Of Your Favorite Parts Of The Work Week? How Does It Encourage Or Inspire You?

I meet three or more customers a week which affords me the opportunity to learn directly from them, hear their business/challenges, and understand their view on technology. It’s a great way to step back from the kitchen to understand what they really need.

Do You Have A Favorite Way To Recharge During The Workday?

I start my day very early with a one-hour workout at 5:30am. It sounds crazy and I was the first person to be confused how people do this. But it’s actually very energizing and helps me tremendously to keep my mind in check during the long work hours.

What Are Your Favorite Hobbies Or Ways To Spend Time Outside Of Work?

If I’m not in my garage doing woodworking, I’m on a rugby field coaching my two sons’ rugby team.

About Samuel Pasquier

Samuel Pasquier is head of product management for Cisco System’s Industrial IoT Connectivity Portfolio, which is designed to meet IoT needs in manufacturing, oil and gas, utilities, transportation, mining, and the public sector. In this position he oversees the development of the portfolio’s strategic direction, roadmap and investments. Under his leadership the portfolio has achieved 16 consecutive quarters of double-digit revenue growth, increased share in five markets, and doubled its overall revenue.

Yasser Alsaied Q&A

How did you first start working in the IoT industry?

For the past six years, I have been involved with the Internet of Things (IoT) from chipsets to System-on-Chip (SoC) to modules to devices and the cloud. I joined Amazon Web Services in 2021 as the vice president of IoT. I lead the AWS IoT business, which covers a wide range of cloud and devices services, such as Robotics, Industrial, Automotive, Consumer, Public Sector and Commercial segments. Our services are among the highest-connected IoT services globally and continue to grow in the fields of digital twins, smart cities and connected vehicles. 

Before joining AWS, I was with Qualcomm as their vice president of IoT as well. During my time at Qualcomm, I held several leadership roles, covering the launch of Qualcomm’s first wireless local-area network (WLAN) chip for mobile phones, Qualcomm Innovation Center, and Code Aurora Foundation to solve legal and operational issues around the open-source software release. During my last four years at Qualcomm, I managed their IoT ecosystem and led the strategy to scale IoT chipsets, including key technologies such as artificial intelligence (AI), computer vision drones, robotics and 5G.

What is your favorite thing about working at AWS?

The most important thing for me is how our work at AWS positively impacts humanity and the environment using IoT technologies. The positive impact and opportunity that AWS offers are unmatched anywhere else.

What sets AWS’s IoT approach or solutions apart from the competition?

It really starts with our market approach to IoT. We understand it is not enough to provide just an IoT platform and disconnected services, and that our customers need fully verticalized, purpose-built solutions that derive actionable insights. They need to be paired with industry partners and account managers that have specialized domain knowledge to reduce complexity of integration and understand customer problems or industry challenges. At AWS, we have created such a deep and broad set of partners, solutions and services, so customers can choose the best solution to drive value for their use case, from secure device connectivity to management, storage, and analytics. Everything runs on the same infrastructure and tools from the cloud to the edge—which ensures seamless performance, reliability, security, scalability, and makes it easier and faster to launch. To support industry verticals, we offer a variety of IoT solution options for the Connected Vehicle, Industrial, Consumer, Public Sector and Commercial markets to best fit the customer’s needs and technical capabilities. 

Another reason AWS is the best place for IoT is our commitment to continuously innovate and make it easier for customers to realize IoT solutions. Since I joined in 2021, AWS IoT has rolled out over 50 updates and launched brand new services, such as AWS IoT FleetWise, AWS IoT ExpressLink, AWS IoT TwinMaker, and AWS IoT RoboRunner. Our qualified device catalog repository has grown over 800 partner devices. 

Lastly, IT and line-of-business customers see security concerns as the top challenge for IoT projects, which limits a business’s ability to move an IoT pilot to production. At AWS, security is the top priority. With all of these services and solutions, AWS is extending the most secure cloud computing environment available today to IoT devices at the edge. Whether they are using AWS IoT managed services, partner solutions, or builder services, customers have access to preventative and active monitoring and response to keep data and devices secure. We also provide a security-dedicated service for IoT devices, AWS IoT Device Defender, which makes it easy to audit configurations, authenticate devices, detect anomalies and receive alerts to help secure your IoT device fleet.

The IoT Industry

What is one key new IoT technology that particularly interests you?

I am keen to focus on the industrial and automotive sectors, as they both seek to promote sustainability and the well-being of humanity and the environment. For example, automation and remote sensing will increase the ability to prevent disasters and know ahead of time if things may go wrong, utilizing AI modeling while protecting equipment and people from running into risky situations.

What is one new IoT technique that teams should implement?

We see a growing need for more simplistic IoT-centric tools. It’s critical to make these tools more accessible for companies to innovate and leverage them, and easier to enter industries as the adoption of IoT technologies continues to grow. For example, tools like AWS IoT Core Device Advisor help developers validate IoT devices for reliable and secure connectivity with AWS. They can identify device software issues, such as being unable to reconnect and get detailed logs to troubleshoot issues during development, and testing cycles.

Another IoT technique that teams should implement is security. As customers move from IoT experimentation and PoCs to deploying IoT production-ready solutions at scale, we find that security is no longer a concern, it’s a barrier to IoT adoption and it’s slowing down digital transformation. Business leaders are excited about the possibilities of IoT, they are also pragmatic about the complexity and security risks associated with deploying IoT solutions. This is due, in part, to a lack of understanding of how to adopt security best practices to the new technologies, as well as a struggle with disparate, incompatible, and sometimes immature security offerings that fail to properly secure deployments, leading to an increased risk. 

AWS IoT’s security strategy is focused on delivering a broad and deep set of security capabilities that allow customers to keep their devices and infrastructure secure with multi-layered protection from edge-to-cloud—protecting their IoT devices, their connectivity, and the data that they generate.

What is one new IoT strategy that companies should implement?

We continue to see very strong IoT interest and adoption from our customers. We don’t anticipate IoT growth will slow down any time soon. However, it is clear that the role of IoT hyperscalers is changing, and in large part, this is tied to an industry shift towards verticalized solutions instead of IoT as a horizontal offering. This shift is in the best interest of customers because they never come to us asking for IoT directly. Instead, they come to us seeking specific business outcomes and for help determining how they can leverage technology to monitor, control, and optimize their business processes to get those outcomes. What this shift means for cloud and IoT software providers is they must put IoT into context for customers’ unique vertical challenges by offering industry-focused solutions and partners that drive business value based on their customer’s in-house skillset, IT scale requirements and use cases. 

In addition, it is becoming more important for companies to work with partners to build complete IoT solutions and applications together. It is vital to ensure companies and their partners are building and creating solutions that are deployed quickly to realize business outcomes and accelerate their time to value. This is also another key strategy companies should implement.

What is the biggest IoT mistake you see enterprises making?

IoT can become complex, and not all companies grasp it. But companies are starting to understand the incredible value of collecting available data, especially in manufacturing, automotive, and enterprise verticals. Data is critical for companies that need to monitor, protect, and improve their products and services. Therefore, the biggest challenge is misunderstanding the value of IoT data and not looking at them as valuable sources to help improve the environment or challenges that companies face today.

In addition, we heard from our customers about the other common areas where they struggle with IoT. For example, they need to navigate the breadth of technologies and skills required for the ecosystem. They also encounter challenges related to adoption, scaling, and device management. For instance, they often need help connecting legacy equipment that wasn’t designed for digitization, or guidance on how to connect digitized OT with IT backend quickly and cost-effectively. Finally, customers also have concerns with future-proofing investments. They have to consider how IoT investments will impact existing infrastructure, drive ROI or incur technical debt in the future.

What are some promising current trends in the IoT market?

Customers are broadening their sustainability initiatives to go beyond emission reduction to create smart environments (i.e. cities, buildings, factories), leveraging IoT to monitor energy performance, reduce waste, and align facility operations with occupancy trends. One great example of this is how Yara collaborated with us to build an efficient and sustainable Digital Production Platform (DPP) for the farming industry. This DPP is a key enabler to digitize their production system across 28 production sites, 122 production units, and two mines. The DPP detects, collects, and runs sophisticated analytics on production data linked to productivity, reliability, environment, safety, quality, and innovation, using AWS IoT SiteWise, AWS IoT Greengrass, AWS IoT Core, AWS IoT Analytics, and Amazon SageMaker. This solution has helped Yara to predict product quality and composition, improve balancing of the site utilities and detect when machines need repair or maintenance to keep production at optimal efficiency levels.

At AWS, we’ve made the consumer-centric vertical approach the north star of our IoT strategy. To better serve our customers, we’ve verticalized our IoT and AI services in ways that are optimized to deliver accelerated outcomes for segment-specific use cases. For instance, AWS IoT SiteWise and AWS IoT TwinMaker services were built to support Industrial IoT customers with collecting, organizing, and analyzing industrial data, as well as creating digital twins of real-world industrial environments. AWS IoT FleetWise supports our automotive customers. We also work with vertically-focused partners who use these services to build solutions for our customers. Our IoT products, sales, and support resources have been restructured to align with key customer industries, allowing us to be more customer obsessed and streamlined in our ability to address customer needs and challenges.

At AWS, we consider the cost implications of every service and feature we design and across our offerings such as compute, storage, and databases—the foundational building blocks for every IT system and application—AWS continuously works to help customers improve performance while lowering their costs. As the impacts of the challenging macroeconomic environment continue, we are seeing customers more focused on controlling costs, and we are actively helping customers optimize cloud spending for existing workloads. In fact, one of the benefits of the cloud compared to managing a data center is the ability to optimize costs relatively quickly. For example, when it comes to IoT, we are providing edge processing and connectivity capabilities through FreeRTOS, AWS IoT ExpressLink and AWS IoT Greengrass, thus enabling customers to analyze data closer to where it is being captured and optimizing their cloud-related expenses.

What are the biggest factors that are driving change in IoT?

The technology that is traditionally referred to as IoT has advanced hugely in recent years. We are rapidly evolving towards a new paradigm of hybrid edge, cloud-connected architectures that achieve much more than just collecting and sharing data. I believe this is one of the factors that is driving the change in IoT. Our commitment to making IoT solutions more accessible globally ties directly into our continued efforts to expand our hybrid cloud and edge computing capabilities. By extending our AWS infrastructure, services, application programming interfaces (APIs), and tools to edge locations like on-premises data centers, 5G towers, and smart factories, we are able to provide all the benefits of the cloud for workloads that require low latency, data residency, local data processing, or complex application interdependencies. 

How has IoT changed during your time in the market?

Over the last decade, IoT has grown from aspirational technology, such as simple task machines to a core differentiator that businesses use to solve problems and drive value through revenue generation, operational improvements, and innovation. For example, more and more companies deploy IoT devices and use them to support critical use cases. Companies have transitioned from “Why do we need to invest in IoT” to “How can we scale IoT deployments more efficiently.” During this period, customers had to go through their internal alignment to bring IT and OT teams together. Now, we see those who embarked on the IoT journey early on reaping the benefits of it with new business value. Take the case of Autodesk, which has built a whole range of IoT services around its Info360 platform for water utilities. Using AWS IoT as the basis of their platform design, they have reduced their technical debt and development time by 60 percent.

We have also seen customers needing help to create scalable architectures where they can easily connect a range of devices, collect data, and analyze it to make informed decisions. These customers have relied on AWS and AWS Partners to simplify their IoT journey by offering a deep, broad, and secure set of solutions and services. Continuing to reduce initial costs and complexities has proven to help customers get the most out of their IoT vision. For instance, Dexatek Technology, a Taiwanese company that gives electronic consumer products smart capabilities using its IoT solutions, increased the performance of its IoT platform, enhanced security, and lowered management time by migrating to AWS IoT Core.

Where do you predict the IoT market will be five or 10 years from now?

I believe IoT will become a universal business expectation rather than an exception, and the growth of IoT will continue with connected enterprises and factories. Many businesses and industries will continue to invest in IoT because it provides business and operational value and they want to connect to the cloud for scalability and benefit from infrastructure cost savings. Companies will also continue investing in IoT technologies and other relevant rising trends, such as generative AI, AI/ML applications. As a result, we will continue to see new customer segments unlocking the value of IoT. 

New data analytics patterns will also be unlocked in the future as more and more IoT sensors come online. These sensors will be capable of capturing new information with high accuracy, such as new analytics in software-defined vehicles or factories of the future with Industry 4.0 initiatives. Companies will look to IoT leaders like AWS to provide more verticalized solutions that are easy to deploy and repurpose across multiple instances. AWS IoT has already embarked on such a direction by offering industry-specific verticalized services, such as AWS IoT SiteWise, AWS IoT TwinMaker, AWS IoT FleetWise, AWS IoT RoboRunner, and AWS IoT ExpressLink. In the coming years, it will be critical to make IoT-centric and solution-based tools more accessible for companies to innovate and leverage them, allowing them to more easily enter the industry as the adoption of IoT technologies continues to grow.

Personnel in IoT

What is one new IoT development your team wants professionals to know?

One of the IoT developments that professionals should know about is the services built to collect, manage, and visualize data from industrial equipment sources at the edge. For example, AWS IoT SiteWise is built to enable industrial enterprises to collect, store, organize, and visualize thousands of sensor data streams across multiple industrial facilities. This will become an important technology to help industrial companies as IoT is becoming increasingly critical.

If you could give one piece of advice to an IoT professional at the beginning of their career, what would it be?

Be cautious about operational excellence and security, two critical success factors for the IoT business. The scale and growth of IoT have a large radius; therefore, IoT professionals need to understand how to securely design, build and scale IoT technologies that can withstand these requirements.

With the shortage of tech talent, how is your team finding and retaining professionals to work in IoT?

The IoT business has always been a team sport. Whether companies are working with their own teams or partners, when there is a shortage in certain areas, they should look for partners to find the right solutions to help solve customer challenges. The goal is to ensure customers are up and running securely and at scale.

For the greatest business impact, what should IoT professionals be focusing on most in their roles?

One of our leadership principles is customer obsession. We start with the customer and work backward to earn and keep their trust. Therefore, delivering results and bringing value (e.g., helping customers to optimize costs when using our services or reducing energy consumption and waste by utilizing the data from IoT devices) to the customer is the bottom line that IoT professionals should focus on most in their roles.

Work-Life

What is one of your top professional accomplishments?

One of my top professional accomplishments was developing and opening up an ecosystem for OEM partners to build smartphones more easily when I worked at Qualcomm. Also, at AWS, I am pleased to work closely with some of the chip providers in the industry, such as Arm, NXP Semiconductors, Intel, Qualcomm, and others to integrate cloud services in their product design and bridge the gap between HW and SW for IoT applications.

What is your favorite part of working in the IoT market?

I truly believe in the transformative power of IoT and its ability to drive innovation, create new business models, and improve lives. Meeting and getting to know the people and experts within the IoT industry, from small businesses to large, open-minded enterprises, is important for me. I enjoy connecting with IoT professionals to learn more about their visions and innovations.

What is one of your favorite parts of the workweek? How does it encourage or inspire you?

Investing in our people is important for me. I enjoy talking to new and upcoming engineers and junior staff, our customers, and partners, hearing and understanding their big picture and thoughts about the IoT industry. I strongly believe that by working together, we can push the boundaries of what is possible in IoT and deliver innovative solutions that make a real difference and impact in the world.

Do you have a favorite way to recharge during the workday?

Connecting with people around me and keeping in touch with family and friends keeps me going during the workday. I love hearing stories and how those impact our lives and the environment surrounding us, starting with family members and extending to people I work or interact with.

What are your favorite hobbies or ways to spend time outside of work?

Outside work, I like to cook and spend time with my family and friends. I also enjoy car racing in my leisure time.

About Yasser Alsaied

Alsaied leads Amazon Web Services (AWS) IoT business, which includes IoT Core, Industrial, Automotive and IoT devices. His group’s services are among the highest-connected IoT services globally and continue to grow in the fields of digital twins, smart cities, and connected smart vehicles. He joined AWS from Qualcomm, where he was vice president of IoT and held various leadership roles, including managing teams that released Qualcomm’s first Wireless Local Area Network (WLAN) chip for mobile phones and leading the formation and launch of the Qualcomm Innovation Center (QuIC) and Code Aurora Foundation (CAF) to solve legal and operational issues around the open-source software release. 

For the past four years, Alsaied managed Qualcomm’s IoT ecosystem. He directly managed the critical part of the strategy to scale IoT chipsets, including key technologies such as artificial intelligence (AI), computer vision drones, robotics, and 5G. In later years, Alsaied was involved in developing a network application vehicle in Nortel Networks that provided advanced speech recognition technology. Alsaied was then part of the Nortel research team to develop 3G architecture and participated in the location-based services and payment processes on 3G. The years following Nortel were spent holding major leadership roles in Philips, ATI, and AMD. He was part of their respective consumer electronic business units and played key roles in design wins that implemented leading-edge technologies in consumer products with very large volumes.

As businesses discover new use cases and develop the infrastructure to support more IoT applications, the entire Internet of Things continues to evolve. Let’s look at some of the current trends in that evolution.

Table Of Contents

• Top 5 IoT Trends
  1. IoT Cybersecurity Concerns Grow
  2. IoT Advancements In Health Care
  3. 5G Enables More IoT Opportunities
  4. Demand For Specialized IoT Data Management
  5. Bundled IoT For The Enterprise Buyer
• The Future Of IoT
• Bottom Line: IoT Trends

Top 5 IoT Trends

IoT devices can help companies use their data in many ways, including generating, sharing and collecting data throughout their infrastructure. While some companies are leaping into IoT technology, others are more cautious, observing from the sidelines to learn from the experiences of those pioneering IoT.

When looking through these five key trends, keep in mind how IoT devices affect and interact with company infrastructure to solve problems.

1. IoT Cybersecurity Concerns Grow

As new IoT solutions develop quickly, are users being protected from cyber threats and their connected devices? Gabriel Aguiar Noury, robotics product manager at Canonical, which publishes the Ubuntu operating system, believes that as more people gain access to IoT devices and the attack surface grows, IoT companies themselves will need to take responsibility for cybersecurity efforts upfront.

“The IoT market is in a defining stage,” Noury said. “People have adopted more and more IoT devices and connected them to the internet.” At the same time they’re downloading mobile apps to control them while providing passwords and sensitive data without a clear understanding of where they will be stored and how they will be protected—and, in many cases, without even reading the terms and conditions.

“And even more importantly, they’re using devices without checking if they are getting security updates…,” Noury said. “People are not thinking enough about security risks, so it is up to the IoT companies themselves to take control of the situation.”

Ben Goodman, SVP of global business and corporate development at ForgeRock, an access management and identity cloud provider, thinks it’s important that we start thinking of IoT devices as citizens and hold them accountable for the same security and authorization requirements as humans.

“The evolution of IoT security is an increasingly important area to watch,” Goodman said. “Security can no longer be an afterthought prioritized somewhere after connectivity and analytics in the Internet of Things. Organizations need to start treating the ‘things’ in the Internet of Things as first-class citizens.”

Goodman said such a measure would mean that non-human entities are required to register and authenticate and have access granted and revoked, just like humans, helping to ensure oversight and control.

“Doing this for a thing is a unique challenge, because it can’t enter a username or password, answer timely questions, or think for itself,” he said. “However, it represents an incredible opportunity to build a secure network of non-human entities working together securely.”

For more information on IoT and security: Internet of Things (IoT) Security Trends

2. IoT Advancements In Healthcare

The healthcare industry has benefited directly from IoT advancements. Whether it’s support for at-home patient care, medical transportation, or pharmaceutical access, IoT solutions are assisting healthcare professionals with more direct care in situations where they cannot provide affordable or safe hands-on care.

Leon Godwin, principal cloud evangelist for EMEA at Sungard AS, a digital transformation and recovery company, explained that IoT not only makes healthcare more affordable—it also makes care and treatment more accessible and patient-oriented.

“IoT in healthcare will become more prevalent as healthcare providers look to reduce costs and drive better customer experience and engagement,” Godwin said. “This might include advanced sensors that can use light to measure blood pressure, which could be incorporated in watches, smartphones, or standalone devices or apps that can measure caloric intake from smartphone cameras.”

Godwin said that AI is also being used to analyze patient data, genetic information, and blood samples to create new drugs, and after the first experiment using drones to deliver organ transplants across cities happened successfully, rollout is expected more widely.

Jahangir Mohammed, founder and CEO of Twin Health, a digital twin company, thinks that one of the most significant breakthroughs for healthcare and IoT is the ability to constantly monitor health metrics outside of appointments and traditional medical tests.

“Recent innovations in IoT technology are enabling revolutionary advancements in healthcare,” Mohammed said. “Until now, individual health data has been mostly captured at points in time, such as during occasional physician visits or blood labs. As an industry, we lacked the ability to track continuous health data at the individual level at scale.

“Advancements in IoT are shifting this paradigm. Innovations in sensors now make it possible for valuable health information to be continuously collected from individuals.

Mohammed said advancements in AI and Machine Learning, such as digital twin technology and recurrent neural networks, make it possible to conduct real-time analysis and see cause-and-effect relationships within incredibly complex systems.

Neal Shah, CEO of CareYaya, an elder care tech startup, cited a more specific use case for IoT as it relates to supporting elders living at home—a group that suffered from isolation and lack of support during the pandemic.

“I see a lot of trends emerging in IoT innovation for the elderly to live longer at home and avoid institutionalization into a nursing home or assisted living facility,” Shah said. Through research partnerships with university biomedical engineering programs, CareYaya is field testing IoT sensors and devices that help with everything from fall prevention to medication reminders, biometric monitoring of heart rate and blood pressure—even mental health and depression early warning systems through observing trends in wake-up times.

Shah said such IoT innovations will improve safety and monitoring and make it possible for more of the vulnerable elderly population to remain in their own homes instead of moving into assisted living.

For more information on health care in IoT: The Internet of Things (IoT) in Health Care

3. 5G Enables More IoT Opportunities

5G connectivity will make more widespread IoT access possible. Currently, cellular companies and other enterprises are working to make 5G technology available in more areas to support further IoT development.

Bjorn Andersson, senior director of global IoT marketing at Hitachi Vantara, a top-performing IoT and  IT service management company, explained why the next wave of wider 5G access will make all the difference for new IoT use cases and efficiencies.

“With commercial 5G networks already live worldwide, the next wave of 5G expansion will allow organizations to digitize with more mobility, flexibility, reliability, and security,” Andersson said. “Manufacturing plants today must often hardwire all their machines, as Wi-Fi lacks the necessary reliability, bandwidth, or security.”

But 5G delivers the best of two worlds, he said—the flexibility of wireless with the reliability, performance, and security of wired networks. 5G provides enough bandwidth and low latency to have a more flexible impact than a wired network, enabling a whole new set of use cases.

Andersson said 5G will increase the feasibility of distributing massive numbers of small devices that in the aggregate provide enormous value with each bit of data.

“This capacity to rapidly support new apps is happening so early in the deployment cycle that new technologies and infrastructure deployment can happen almost immediately, rather than after decades of soaking it in,” he said. “With its widespread applicability, it will be feasible to deliver 5G even to rural areas and remote facilities far more quickly than with previous Gs.”

For more: Internet of Things (IoT) Software Trends

4. Demand For Specialized IoT Data Management

With its real-time collection of thousands of data points, the IoT solutions strategy focuses heavily on managing metadata about products and services. But the overwhelming amount of data involved means not all IoT developers and users have begun to fully optimize the data they can now access.

Sam Dillard, senior product manager of IoT and edge at InfluxData, a data platform provider for IoT and in-depth analytics use cases, believes that as connected IoT devices expand globally, tech companies will need to find smarter ways to store, manage and analyze the data produced by the Internet of Things.

“All IoT devices generate time-stamped (or time series) data,” Dillard said. “The explosion of this type of data, fueled by the need for more analytics, has accelerated the demand for specialized IoT platforms.”

By 2025, around 60 billion connected devices are projected to be deployed worldwide—the vast majority of which will be connected to IoT platforms, he said. Organizations will have to figure out ways to store the data and make it all sync together seamlessly as IoT deployments continue to scale at a rapid pace.

5. Bundled IoT For The Enterprise Buyer

While the average enterprise buyer might be interested in investing in IoT technology, the initial learning curve can be challenging as IoT developers work to perfect new use cases for users.

Andrew De La Torre, group VP of technology for Oracle Communications at cloud and data management company Oracle, believes that the next big wave of IoT adoption will be in bundled IoT or off-the-shelf IoT solutions that offer user-friendly operational functions and embedded analytics.

Results of a survey of 800 respondents revealed an evolution of priorities in IoT adoption across industries, De La Torre said—most notably, that enterprises are investing in off-the-shelf IoT solutions with a strong desire for connectivity and analytics capabilities built-in.

Because of specific capabilities, commercial off-the-shelf products can extend IoT into other industries thanks to its availability in public marketplaces. When off-the-shelf IoT aligns with industrial needs, it can replace certain components and systems used for general-use practices.

While off-the-shelf IoT is helpful to many companies, there are still risks as it develops—security risks include solution integration, remote accessibility and widespread deployments and usage. Companies using off-the-shelf products should improve security by ensuring that systems are properly integrated, running security assessments, and implementing policies and procedures for acquisitions.

The Future Of IoT

Customer demand changes constantly. IoT services need to develop at the same pace.

Here’s what experts expect the future of Iot development to look like:

Sustainability and IoT

Companies must embrace IoT and its insights so they can pivot to more sustainable practices, using resources responsibly and organizing processes to reduce waste.

There are multiple ways a company can contribute to sustainability in IoT:

• Smart energy management: Using granular IoT sensor data to allow equipment control can eliminate office HVAC system waste and benefit companies financially and with better sustainability practices.
• Extent use style: Using predictive maintenance with IoT can extend the lifespan of a company’s model of manufacturing. IoT will track what needs to be adjusted instead of creating a new model.
• Reusing company assets: Improved IoT information will help a company determine whether it needs a new product by looking at the condition of the assets and use history.

IoT and AI

The combination of Artificial Intelligence (AI) and IoT can cause industries, businesses and economies to function in different ways than either IoT or AI function on their own. The combination of AI and IoT creates machines that have smart behaviors and supports strong decision-making processes.

While IoT deals with devices interacting through the internet, AI works with Machine Learning (ML) to help devices learn from their data.

AI IoT succeeds in the following implementations:

• Managing, analyzing, and obtaining helpful insights from customer data
• Offering quick and accurate analysis
• Adding personalization with data privacy
• Providing assistance to use security against cyber attacks

More Use of IoT in Industries

Healthcare is cited as one of the top IoT industries, but many others are discovering how IoT can benefit their companies.

Agriculture

IoT can be used by farmers to help make informed decisions using agriculture drones to map, image, and survey their farms along with greenhouse automation, monitoring of climate conditions, and cattle monitoring.

IoT enables agriculture companies to have more control over their internal processes while lowering production risks and costs. This will reduce food waste and improve product distribution.

Energy

IoT in the energy sector can improve business performance and customer satisfaction. There are many IoT benefits for energy industry, especially in the following areas:

• Remote monitoring and managing
• Process optimization
• Workload forecasting
• Grid balancing
• Better decision-making

Finance

Banks and customers have become familiar with managing transactions through many connected devices. Because the amount of data transferred and collected is extensive, financial businesses now have the ability to measure risk accurately using IoT.

Banks will start using sensors and data analytics to collect information about customers and offer personalized services based on their activity patterns. Banks will then better understand how their customers handle their money.

Manufacturing

Manufacturing organizations gather data at most stages of the manufacturing process, from product and process assistance through planning, assembly and maintenance.

The IoT applications in the manufacturing industry include:

• Production monitoring: With IoT services’ ability to monitor data patterns, IoT monitoring provides optimization, waste reduction and less mundane work in process inventory.
• Remote equipment management: Remote work has grown in popularity, and IoT services allow tracking and maintaining of equipment’s performance.
• Maintenance notifications: IoT services help optimize machine availability by receiving maintenance notifications when necessary.
• Supply chains: IoT solutions can help manufacturing companies track vehicles and assets, improving manufacturing and supply chain efficiency.

For more industries using IoT: IoT in Smart Cities

Bottom Line: IoT Trends

IoT technology reflects current trends and reaches many areas including AI, security, healthcare, and other industries to improve their processes.

Acknowledging IoT in a business can help a company improve a company structure, and IoT will benefit a company’s infrastructure and applications.

For IoT devices: 85 Top IoT Devices

Particularly with innovations like the cloud, edge computing, Internet of Things (IoT) devices, and streaming, big data has become more prevalent for organizations that want to better understand their customers and operational potential. 

Big Data Trends: Table of Contents

• Real Time Analytics
  
• Stronger Reliance on Cloud Storage
  
• Ethical Customer Data Collection
• AI/ML Powered Automation
• Big Data in Different Industries
• Challenges in Big Data
• Bottom Line: Big Data Trends

Real Time Analytics

Real time big data analytics – data that streams moment by moment – is becoming more popular within businesses to help with large and diverse big data sets. This includes structured, semi-structured, and unstructured data from different sizes of data sets.

With real time big data analytics, a company can have faster decision-making, modeling, and predicting of future outcomes and business intelligence (BI). There are many benefits when it comes to real time analytics in businesses:

• Faster decision-making: Companies can access a large amount of data and analyze a variety of sources of data to receive insights and take needed action – fast.
• Cost reduction: Data processing and storage tools can help companies save costs in storing and analyzing data. 
• Operational efficiency: Quickly finding patterns and insights that help a company identify repeated data patterns more efficiently is a competitive advantage. 
• Improved data-driven market: Analyzing real time data from many devices and platforms empowers a company to be data-driven. Customer needs and potential risks can be discovered so they can create new products and services.

Big data analytics can help any company grow and change the way they do business for customers and employees.

For more on structured and unstructured data: Structured vs. Unstructured Data: Key Differences Explained

Stronger Reliance On Cloud Storage

Big data comes into organizations from many different directions, and with the growth of tech, such as streaming data, observational data, or data unrelated to transactions, big data storage capacity is an issue.

In most businesses, traditional on-premises data storage no longer suffices for the terabytes and petabytes of data flowing into the organization. Cloud and hybrid cloud solutions are increasingly being chosen for their simplified storage infrastructure and scalability.

Popular big data cloud storage tools:

• Amazon Web Services S3
• Microsoft Azure Data Lake
• Google Cloud Storage
• Oracle Cloud
• IBM Cloud
• Alibaba Cloud

With an increased reliance on cloud storage, companies have also started to implement other cloud-based solutions, such as cloud-hosted data warehouses and data lakes. 

For more on data warehousing: 15 Best Data Warehouse Software & Tools

Ethical Customer Data Collection 

Much of the increase in big data over the years has come in the form of consumer data or data that is constantly connected to consumers while they use tech such as streaming devices, IoT devices, and social media. 

Data regulations like GDPR require organizations to handle this personal data with care and compliance, but compliance becomes incredibly complicated when companies don’t know where their data is coming from or what sensitive data is stored in their systems. 

That’s why more companies are relying on software and best practices that emphasize ethical customer data collection.

It’s also important to note that many larger organizations that have historically collected and sold personal data are changing their approach, making consumer data less accessible and more expensive to purchase. 

Many smaller companies are now opting into first-party data sourcing, or collecting their own data, not only to ensure compliance with data laws and maintain data quality but also for cost savings.

AI/ML-Powered Automation

One of the most significant big data trends is using big data analytics to power AI/ML automation, both for consumer-facing needs and internal operations. 

Without the depth and breadth of big data, these automated tools would not have the training data necessary to replace human actions at an enterprise.

AI and ML solutions are exciting on their own, but the automation and workflow shortcuts that they enable are business game-changers. 

With the continued growth of big data input for AI/ML solutions, expect to see more predictive and real-time analytics possibilities in everything from workflow automation to customer service chatbots.

Big Data In Different Industries 

Different industries are picking up on big data and seeing many changes in how big data can help their businesses grow and change. From banking to healthcare, big data can help companies grow, change their technology, and provide for their data.

Banking

Banks must use big data for business and customer accounts to identify any cybersecurity risk that may happen. Big data also can help banks have location intelligence to manage and set goals for branch locations.

As big data develops, big data may become a basis for banks to use money more efficiently.

Agriculture

Agriculture is a large industry, and big data is vital within the industry. However, using the growing big data tools such as big data analytics can predict the weather and when it is best to plant or other agricultural situations for farmers.

Because agriculture is one of the most crucial industries, it’s important that big data support it, and it’s vital to help farmers in their processes. 

Real Estate And Property Management 

Understanding current property markets is necessary for anyone looking, selling, or renting a place to live. With big data, real estate firms can have better property analysis, better trends, and an understanding of customers and markets.

Property management companies are also utilizing their big data collected from their buildings to increase performance, find areas of concern, and help with maintenance processes.

Healthcare

Big data is one of the most important technologies within healthcare. Data needs to be collected from all patients to ensure they are receiving the care they need. This includes data on which medicine a patient should take, their vitals are and how they could change, and what a patient should consume. 

Going forward, data collection through devices will be able to help doctors understand their patients at an even deeper level, which can also help doctors save money and deliver better care.

Challenges in Big Data

With every helpful tool, there will be challenges for companies. While big data grows and changes, there are still challenges to solve.

Here are four challenges and how they can be solved:

Misunderstanding In Big Data

Companies and employees need to know how big data works. This includes storage, processing, key issues, and how a company plans to use the big data tools. Without clarity, properly using big data may not be possible.

Solutions: Big data training and workshops can help companies let their employees learn the ins and outs of how the company is using big data and how it benefits the company.

Data Growth

Storing data properly can be difficult, given how constantly data storehouses grow. This can include unstructured data that cannot be found in all databases. As data grows, it is important to know how to handle the data so the challenge can be fixed as soon as possible.

Solutions: Modern techniques, such as compression, tiering, and deduplication can help a company with large data sets. Using these techniques may help a company with growth and remove duplicate data and unwanted data.

Integrating Company Data

Data integration is necessary for analysis, reporting, and BI. These sources may contain social media pages, ERP applications, customer logs, financial reports, e-mails, presentations, and reports created by employees. This can be difficult to integrate, but it is possible.

Solutions: Integration is based on what tools are used for integration. Companies need to research and find the correct tools.

Lack Of Big Data Professionals

Data tools are growing and changing and often need a professional to handle them, including professionals with titles like data scientists, data analysts, and data engineers. However, some of these workers cannot keep up with the changes happening in the market.

Solutions: Investing money into a worker faced with difficulties in tech changes can fix this problem. Despite the expense, this can solve many problems with companies using big data.

Most challenges with big data can be solved with a company’s care and effort. The trends are growing to be more helpful for companies in need, and challenges will decrease as the technology grows. 

For more big data tools: Top 23 Big Data Companies: Which Are The Best?

Bottom Line: Growing Big Data Trends

Big data is changing continuously to help companies across all industries. Even with the challenges, big data trends will help companies as it grows.

Real time analytics, cloud storage, customer data collection, AI/ML automation, and big data across industries can dramatically help companies improve their big data tools.

Lockheed Martin is adopting Red Hat Device Edge to help it support U.S. national security missions by using AI technology in geographic locations that are hard to reach, according to Red Hat last month.

Lockheed Martin and Red Hat believe the use of Red Hat Device Edge will help military platforms “adapt to threat environments” in real-time.

Red Hat Device Edge will provide Lockheed Martin’s military platform with a Kubernetes orchestration solution, MicroShift, built from the capabilities of Red Hat OpenShift, Kubernetes container platform, and Red Hat Enterprise Linux.

Lockheed Martin is considered a key contributor to the MicroShift project to help bring edge capabilities to inaccessible environments. Lockheed Martin plans to use Red Hat Device Edge for a range of military use cases: land, sea, air, space, and cyber.

For instance, the companies are using Red Hat Device Edge to equip U.S. military platforms, such as the Stalker unmanned aerial system (UAS). Red Hat Device Edge is designed to enable small platforms to handle large AI workloads, increasing their field capability and data-backed decision making.

The Stalker used onboard sensors, Red Hat Device Edge, and AI in flying intelligence, surveillance, and reconnaissance (ISR) missions to more accurately classify a military target and improve situational awareness, according to Red Hat.

Lockheed Martin is also using Red Hat OpeShift to enhance Lockheed’s 5G.MIL solutions for communications for the Department of Defense, according to Red Hat.

“Global innovation”

With Red Hat Device Edge, Lockheed Martin is “leading the infusion of cutting-edge commercial technology into military capabilities that deliver advanced solutions to our customers,” said Justin Taylor, VP, AI, Lockheed Martin.

“Unlocking these AI technologies can help national security decision makers stay ahead of adversaries, enabling a safer and more secure world.”

With Red Hat Device Edge, Red Hat will work with Lockheed Martin to “change what communications and artificial intelligence looks like in the most space-constrained and far-flung environments, whether remote mountain ranges or beyond the boundaries of Earth’s atmosphere,” said Francis Chow, VP and GM, in-vehicle operating system and edge, Red Hat. 

Recent Red Hat activity

Over the past year, Red Hat has formed numerous deals and partnerships in various industries, including several recent ones:

• Red Hat OpenShift and Siemens are working to innovate at the factory edge
• Red Hat launched Red Hat Enterprise Linux for AWS
• Crédit Agricole Group’s infrastructure platform is driving automation and operations with Red Hat

The growing AI market

The global artificial intelligence (AI) market was estimated to be valued at $87.04 billion in 2021 and is anticipated to hit $1.59 trillion by 2030, at a compound annual growth rate (CAGR) of 38.1%, according to Precedence Research.

Growth in the market is being driven by new technologies using machine learning (ML) and deep learning (DL), according to Precedence Research.

The growing military cybersecurity market

The global defense cyber security market is estimated to grow from $19.96 billion in 2021 to $29.81 billion in 2028, at a CAGR of 5.36%, according to Fortune Business Insights.

China, India, and the U.S. are leading the market as they invest in cybersecurity within their defense departments.

Red Hat and Lockheed leaders discuss AI tech

Nick Barcet — senior director of customer-led open innovation at Red Hat — and Greg Forrest — director of AI foundations at Lockheed Martin — talk at KubeCon + CloudNativeCon North America:

For years, organizations have leveraged analytics with the goal of transforming data into insight and then action. Traditionally, many have relied on an approach known as “centralize and analyze,” where they pool all of their application, service, and system health data into a central repository for indexing and crunching. 

In recent years, this approach has become increasingly problematic from a variety of perspectives, including the difficulty in keeping up with exploding data volumes and subsequently monitoring costs. As teams struggle to harness all of their data in order to optimize overall service health, they find themselves forced to make painful decisions regarding what data to analyze and what to neglect — a very risky proposition given the capricious nature of performance issues. 

As a byproduct of this decision, teams often don’t have the data they need to anticipate or quickly resolve issues. This shows in the fact that despite technology advancements and the industry’s strong investment in resiliency, outages persist, with the number of outages lasting more than 24 hours increasing substantially. 

Here, we’ll explore how a new approach to monitoring applications solves this problem. Rather than compressing and shipping massive data volumes to compute resources downstream, this new approach flips traditional monitoring on its head. Now, it is possible to push your compute to your datasets. Pushing data analytics upstream — or processing data at the edge — can help organizations overcome certain challenges and maximize the value of their data and analytics.

Analyzing all application and system health data at its source

Bringing compute resources geographically closer to users reduces latency and helps organizations deliver significantly better user performance as well as the ability to monitor new services without creating bottlenecks in downstream systems and on-premise data centers. Simply put, teams no longer need to predict upfront which datasets are valuable and worth analyzing in order to fix issues that can impact the customer’s/user’s experience.

Pushing analytics upstream to the edge can help organizations avoid such dilemmas by processing all application, service, and system health data at various points across the edge, simultaneously and broken down into bite-sized chunks. This allows organizations to effectively have an eye on all their data, without having to neglect even a single dataset.

See more: Top Edge Data Center Companies

Safeguarding and driving conversions

For transaction-heavy online services — e-commerce companies and travel booking sites, for example — highly performing applications and systems are the lifeblood of the business. When these applications go down — or even slow down, by as little as a few milliseconds — the result is a noticeable hit to conversion rates. According to statistics, the highest e-commerce conversion rates occur on sites with web page load times between 0-2 seconds, and with each additional second of load time, website conversion rates drop by an average of 4.42%. These statistics also note that a site that loads in one second has a conversion rate three times higher than a site that loads in five seconds.

In this context, mean-time-to-detect (MTTD) and mean-time-to-respond (MTTR) requirements are exceedingly slim, essentially zero. As discussed above, pushing analytics upstream enables teams to more proactively identify and address anomalies, while also intuitively pinpointing the exact location of growing hot spots or a particular infrastructure or application running on it. Teams can fix problems much faster, ideally before user performance is impacted in the first place — which is perhaps the most important step in safeguarding conversions. 

But when it comes to actually increasing conversions, application and system health data are not the only type of data that can benefit from analytics being pushed further upstream. Today, nearly three out of every four dollars spent on online purchases is done so through a mobile device. A matter of nanoseconds can mean the difference between capitalizing on a site visitor’s ephemeral attention span — or not. When customer behavioral data is processed at the edge — thus avoiding long-distance communication flows back to the cloud — an organization can become much more agile and instantaneous in delivering highly personalized, high-velocity marketing that fuels conversions.

See more: How Edge Data Centers are Used by Comcast, TED, Goodwill, Georgia Tech, Zaxby’s, Villa-Tech, and Afterpay: Case Studies

Keeping a lid on monitoring costs

The old “centralize and analyze” approach entailed routing all application and system health data to hot, searchable, and relatively expensive retention tiers. Many organizations experience sticker shock as they run up against, and in many cases, unknowingly exceed, data usage limits. One alternative is to purchase in advance more capacity than one may actually end up needing, but small businesses in particular can’t afford to be spending money on capacity they don’t ultimately use. Another drawback is the more data is in a repository, the longer the expected search time tends to be.

In the context of these challenges — and as edge processing grows — data stores need to follow suit. Gartner estimates that by 2025, 70% of organizations will switch their analytics approaches from “big” to “small and wide,” and a key enabling factor is that the edge offers tremendous flexibility and creates space for more real-time data analysis across larger volumes of data. When analytics are pushed upstream, organizations process their data then and there, right at the source. From there, teams can move their data to a more low-cost storage option in the cloud, where it remains searchable. 

Whether driven by compliance requirements, the desire to mine historical data for further analysis, or something else — there are going to be occasions where teams do need access to all their data. In these cases, it will be there, readily and easily available to anyone who needs it, without exhausting or exceeding budgets in the process. 

Conclusion

As data volumes grow exponentially, processing data at the edge becomes the most feasible way to cost-effectively and comprehensively leverage an organization’s rich data. Now, teams can realize the potential to analyze all of their data to ensure high performance, uptime, and strong user experiences.

See more: 5 Top Edge Data Center Trends 

Enterprises typically work with edge data centers to be more hands-on with the data, reduce latency, and extract more front-line analytics. 

The edge data center market is estimated to grow from a value of around $6.5 billion in 2020 to $21.4 billion by 2027, according to ResearchandMarkets.

See below to learn all about edge data center technologies and the top companies in the edge data center market:

For more: The Edge Data Center Market

Choosing the edge data center companies

• Top edge data center companies

• • American Tower

• • Edge Data Solutions

• • Edgeconnex

• • Frontier Communications

• • H5 Data Centers

• • Leading Edge DC

• • SBA Edge

• • Proximity Data Centres

• • Dart Points

• • 1623 Farnam

• Edge data center companies features

• Edge data center companies benefits

• Use cases

Top edge data center companies

American Tower

Boston-based American Tower is a telecommunications company that has about 222,000 communication sites, with about 43,000 sites in the United States and Canada, and American Tower has about 179,000 properties internationally. American Tower’s portfolio includes American Tower Edge Data Centers.

American Tower Edge Data Centers can give enterprise network elasticity optimization; provide disaster recovery and network redundancy; offer cloud services; security enhancement; high-bandwidth connections; and have other applications such as artificial intelligence (AI) autonomous driving, and the internet of things (IoT).

“American Tower is a business interested in B2B relationships, which is rare in the data center industry. Working with major data center providers, sometimes the relationships are purely transactional. The fact that American Tower is B2B focused means a lot to Villa-Tech and our customers,” says Miguel Villarreal, Principal, Villa-Tech, Inc., a user of American Tower Edge Data Centers.

American Tower Edge Data Centers won the 2021 Light Reading Leading Light Awards for their innovative edge computing solutions, by Villa-Tech, Inc.

Differentiators

• Man-trap doors
• Network Ops Center (NOC)
• Remote hands services

Pricing

For pricing, go to American Tower’s contact page.

Edge Data Solutions

Edge Data Solutions, based in Atlanta, Georgia, is an IT services and consulting company that specializes in data centers, crypto mining, and cloud infrastructure. Edge Data Solutions also has an emphasis on edge data centers. Their benefits are based on their five key pillars: reliability, efficiency, sustainability, profitability, and scalability.

Edge Data Solution’s edge data centers want to reduce the CO2 footprint of data centers. The approach has three parts: data center tanks, enterprise modular containers, and edge fluids. The data center tanks are stainless steel tanks that are racked to accommodate 21” wide servers. The enterprise modular containers are made to sustain high winds and heavy loads enabling the operator to move quickly. The edge fluids give hardware protection, customized solution, reduced hash rate spikes, and are professionally engineered.

“EDGE’s first-of-a-kind solutions provide the best overclock performance free of hash rate peaks while giving the blockchain community a unique opportunity to lead the world in next-generation cooling technology,” says Daniel Wong, co-founder and president of Edge Data Solution.

Differentiators

• Three separate parts
• Maximize hardware efficiency and lifespan by 30%
• 60% less of a footprint

Pricing

For pricing, go to the Edge Data Solutions contact page.

EdgeConneX

Herdon, Virginia-based EdgeConneX is a telecommunications company that focuses on keeping up with the growing demand for data, content, cloud services, and computing.  EdgeConneX has 40 data centers globally that cover edge, far edge, and hyper-scale data centers. EdgeConneX data centers, Edge Data Centers, are some of the top products in edge data centers.

Edge data centers are designed to be in the correct proximity for an enterprise, assist in delivering and distributing digital content, have high-density power of up to 30 kW per rack, offer network diversity, and offer a self-service management application called EdgeOS.

“The EdgeConneX Edge Data Center model enables new opportunities for in-market interconnection that offer a substantial performance improvement over the traditional centralized interconnection model,” says Noam Freedman, senior VP, Networks & Chief Network Architect at Akamai Technologies, a user of EdgeConneX Edge Data Centers.

EdgeConneX won the “Competitive Strategy Leadership Award” by Frost & Sullivan.

Differentiators

• EdgeOS
• Network diversity (MSOs, ISPs, fiber, mobile provider)
• up to 30kW per rack

Pricing

For pricing, go to EdgeConneX contact us page.

Frontier Communications

Frontier Communications, based in Norwalk, Connecticut, is a telecommunications company that offers gigabit speeds for consumers and businesses in 25 states. Frontier aims to build critical digital infrastructure across the country with its fiber-optic network and cloud-based solutions and provide edge data centers for their customers.

Frontier Communications is working towards edge data centers to be able to process remote applications like IoT and 5G networks to advanced innovations like AI and quantum computing. Frontier Communications’ customers need access to their applications and data. Frontier Communications aims to bring data and workloads closer to their customers. They have 180,000 miles of fiber for their network and over 2,500 edge locations nationwide.

“We’re gonna keep on with the hard graft of building fiber as fast as we can, selling it as actively as we can, really improving customer care, becoming more efficient, and delivering what I hope is going to be the net of this, which is a truly great American turnaround story,” says Nick Jeffery, Frontier CEO, on their technology growth strategy.

Frontier Communications was recognized and awarded the “Most Innovative Broadband Project Award” by NY State Broadband Summit and Awards Ceremony.

Differentiators

• Supports high bandwidths 100G to 400G services
• 180,000 miles of fiber
• Traditional networking and edge colocation

Pricing

For pricing, go to Frontier’s buy page.

H5 Data Centers

H5 Data Centers is an IT services and consulting company located in Englewood, Colorado. It is a private owner data center operation in the United States with over three million square feet of data centers. H5 Data Centers runs nine edge data centers across the U.S.

H5 Data Centers’ edge data centers aim to support the needs of Ethernet providers, content companies, network operators, internet exchanges, and cloud service providers across the country.

“H5 Data Centers continues to make investments across our national footprint to improve the reliability and efficiency of our data centers. We are committed to energy efficiency innovation and long-term sustainability,” said Josh Simms, CEO of H5 Data Centers.

H5 Data Centers was awarded the “Data Center Efficiency Award” by Xcel Energy.

Differentiators

• Network operators ROBCs, ILECs, mobile, cable companies
• Latency-sensitive apps such as multi-player gaming, virtual reality (VR), and self-driving cars
• Peering-internet exchange access

Pricing

For pricing information, go to the H5 Data Centers contact us page.

See more: 10 Top Data Center Certifications

Leading Edge DC

Leading Edge Data Centres, based in North Sydney, Australia, is a data center operations company that’s mission is to “bridge the digital divide of metropolitan and regional Australia”. Leading Edge DC offers many products: colocation services, internet connectivity, cross-connect, and data centre interconnect. Customer premises, regional edge data centre, and metro data centre are their main use cases. Leading Edge DC’s regional edge data centre is one of Leading Edge DC’s largest products.

The regional edge data centre is where Leading Edge DC is focused with a regional edge space of 1-5 ms latency. The regional edge data centre can be close to enterprises for the best experience, build to tier-3 data centres, scalable space with high-density power, fixed OpEx investment, connected 3rd party service providers, and the business continuity of 99.985% uptime SLA.

“With a local data centre, I can build and create the configuration I need for our business needs and IT architecture, access the services, speed, stability, and security that we require, all while eliminating the cost of downtime, maintenance, and corporate overhead,” says Angus Collins IT Manager, JT Fossey Cars and Trucks, a user of Leading Edge DC.

Leading Edge DC was recognized as one of the Top Tech Startups in Australia by Tracxn and won “The Edge Award” by DataCloud.

Differentiators

• Connect to third-party service providers
• Built to Tier-3 data center standards
• Fixed OpEx investment

Pricing

For pricing, go to Leading Edge DC’s contact us page or book a tour.

SBA Edge

SBA Edge is a colocation facility that provides data center solutions. SBA Edge Data Centers’ parent company, SBA Communications, develops new tower sites to expand their tower portfolio. The tower portfolio is the backbone for their edge computing capabilities, with both data centers and infrastructure at their towers. SBA Edge data centers are a large focus of their business.

SBA Edge has more than 32,500 communications sites in 14 markets throughout the Americas and South Africa. SBA Edge offers the infrastructure to deploy edge data centers for edge computing solutions. There are three main locations for the edge data centers. One is in West Chicago, one in Jacksonville, Florida, and the other is named tower to the edge. SBA has 100% infrastructure SLAs, over 400 customers, two large peering exchanges, 100% power uptime since inception, and customizable deployment options for businesses they work with.

“I have been with this data center for over seven years and had the pleasure of visiting the center. As a QSA auditor for the PCI-PSA, I have to say this data center is top notch and they follow all security protocols. … The IT support is beyond reproach, during the seven years I cannot recall any substantial outage, I feel they were up well over 99.9%,” says a user of SBA Edge data centers.

SBA Edge has multiple certifications to maximize the reliability of their data centers including SSAE 18, PCI, Open-IX, as well as being HIPAA Certified.

Differentiators

• SSAE-18 SOC I Type II certified, HIPAA and PCI Compliant, OIX-2 Certified
• 100% uptime SLA
• Water system cooling

Pricing

For pricing, go to the estimate now page.

Proximity Data Centres

UK-based Proximity Data Centres is a network of 20 internet edge data centres with low latency colocation services. Proximity Data Centres aims to have their edge data centers within 15 miles of 95% of the UK population, and while they have customers that are both large enterprises and small businesses, Proximity Data Centres seek to protect all of their customers’ data.

Proximity Data Centres’ edge data centers are made for businesses who want to keep pace with the rising demand for more data storage and security. 5G, artificial intelligence (AI), the internet of things (IoT), cloud gaming, and other entertainment services are growing every day, making businesses need to stay caught up. With their 1000s of customers and over 134,000 square feet of data centers, Proximity Data Centres works to satisfy and grow their customer experience.

“Edge data centers will play a pivotal role in ensuring the whole of the UK, not just its major cities, is reaping the rewards of 5G,” says John Hall, managing director, Proximity Data Centres about the need for edge data centers.

Proximity Data Centres was recognized as one of the 100 edge computing companies to watch in 2022, by STL.

Differentiators

• CCTV, VESDA, and IG55 fire suppression
• ISO9001, 14001, 27001 certification
• Over 2,000 racks

Pricing

For pricing, reach out to Proximity Data Centres at info@proximitydatacentres.com.

Dart Points

Dallas-based DartPoints is an IT services and consulting company that works with cloud, data center, and managed services. With around 170 data centers, DartPoints has multiple edge data centers to connect millions of consumers and businesses in 25 states. DartPoints also focuses on edge interconnection data centers for carriers, enterprises, and content providers by harnessing the power of interconnection.

DartPoints’ Edge data centers are working to manage, process, and fulfill data traffic, as well as providing 24×7 CCTV monitoring, dual authentication entry, and individually secured cabinets for security; carrier-neutral partner ecosystem for scalable and collective growth; multi-tenant, shared-cost model; and SSAE 18 SOC 2 Certified, HIPAA, and PCI SAQ-D compliance.

“The benefit of working with DartPoints is reflected in the sense of security we have housing our data and server systems in their facility. We can rely on DartPoints, and knowing our systems are running properly, we can focus on other tasks instead of wasting time making sure our servers are running,” says Cody Reid, IT systems admin, Tupelo Honey Café, a user of DartPoints.

DartPoints made the Datacloud Global Awards 2021 shortlist for The Edge Award 2021 category and received recognition for DartPoints’ innovative approach to edge colocation and interconnection building, as the company also earned the 2020 “DCD Global Awards Edge Project of the Year”.

Differentiators

• Pay as you grow
• Nationwide SLAs and N+1
• Carrier-neutral partner ecosystem

Pricing

For pricing, go to DartPoints’ contact page.

1623 Farnam

1623 Farnam is a computer and network security company based in Omaha, Nebraska. 1623 Farnam offers access to 50 network companies that have local, regional, national and international reach with 75,000 square feet of space. Omaha Interconnected Edge Data Center, 1623 Farnam’s edge data center, offers security for an enterprise’s infrastructure and applications.

1623 Farnam’s edge data center offers a minimum suite of 1,000 square feet, has more than 50 carriers with Omaha IX both IP and peering exchange, 120/208 volt AC power with N+1 UPS available, environmental awareness, and security every day of the year. They are certified in SOC2 Type 1, SOC2 type 2, ISO, and BCP.

“We are very excited to unveil this rebrand of Omaha IX. Omaha IX is a really big differentiator for us at 1623 Farnam, and we are very proud to host it. It gives our customers a unique opportunity to peer without hassle, and does a great deal to strengthen and diversify our network ecosystem,” says 1623 Farnam President, Todd Cushing, on the growth of their data centers.

Differentiators

• Pre-action dry pipe zoned interlock detection
• Facial/bio/proxy to data center space
• Powered shell, build-to-suit, managed suites

Pricing

For pricing, go to 1623 Farnam’s get started page.

Edge data center features

Location: allow enterprises to be closer to customer data

Size: smaller footprint makes it easier to process real-time data in direct communication with devices

Network: either connect to the main network or a network of other edge data centers

Hub and mobile: with edge hubs being located in the center of the network, mobile data centers, or spokes, are small and located at the edge of the data center

Edge data center benefits

• Enhanced speed
• Bandwidth relief
• Data management
• Cybersecurity
• Reliability
• Disaster recovery
• Speed

Use cases

Zaxby’s

Zaxby’s is a fast-casual chicken brand based in Athens, Georgia. 

Zaxby’s required a disaster recovery and colocation site that was close to their headquarters. They also needed the data center requirements but wanted more of a partnership and support with company growth.

Zaxby’s moved data to DartPoints’ Asheville, North Carolina edge location, which is both close to the chain’s headquarters and a favorable weather area. The relationship with DartPoints left Zaxby’s comfortable and feeling safe about their data protection.

“I would most definitely recommend DartPoints to my peers. From day one, the DartPoints team has been very professional, always helpful, and very knowledgeable about the data center space itself and what they have in the data center,” says Kevin Blount, director of IT operations and security, Zaxby’s.

Windstream Wholesale

Windstream Wholesale provides connectivity between major domestic data centers. They have built into 150 data centers in the U.S.

Windstream Wholesale needed to improve their capacity and fast connections. They chose to get assistance from 1623 Farnam and the provider’s edge data center in Omaha, Nebraska, which is ideal to improve connections and access for Windstream’s customers.

“We’ve seen about a 30% increase in data traffic and about a 50% increase in voice traffic. …  And I’m very proud to say that there is no congestion anywhere on our network,” says John Nishimoto, VP strategy and product development, Windstream Wholesale.

See more: The Data Center Storage Market