The world has been forced to digitize more quickly and to a greater extent in 2020 and 2021. COVID has created the need to remodel the work, socializing, production, entertainment, and supply chains function. Despite decades of digitization efforts, with the pandemic upon us, digitization challenges have become transparent. With people leaning heavily on online digital solutions, internet infrastructure is at its capacity limit. Accordingly, users are seeing broadband speeds drop by as much as half. In Europe, governments even requested to reduce the quality of Netflix, Amazon Prime, Youtube and other streaming services to improve network speed.

The Internet of Things is growing exponentially with connected devices ranging from smart lights and ovens to industrial analysis data capture devices. By 2025, it is expected that there will be 41.6 billion connected IoT devices, generating 79.4 zettabytes (ZB) of data, according to IDC. For comparison, one zettabyte is approximately one billion terabytes.

In the early days of IoT, most of those devices would send all of the data they collected to the cloud for analysis. However, when you start trying to send trillions of gigabytes to the cloud, the data pipeline starts to get a little clogged up. That’s where edge computing comes in—it helps IoT devices process some of that data locally instead, before, or sometimes in lieu of, sending it to the cloud. That’s where the name comes from—the data is being processed at the “edge” of your own network, instead of being sent away.

The Role of Edge Computing in IoT

Edge computing serves a variety of purposes in the current IoT landscape. This distributed, local computing paradigm untethers IoT devices from latency and connectivity issues that would otherwise make some IoT use cases impossible. This essential technology forms the backbone of IoT applications that include classified data, require real-time or low-latency decision making, occur in environments where cloud connectivity is either sparse or entirely unavailable, and particularly data-heavy cases such as in industrial IoT implementations.

Because edge computing devices analyze data in-house, there is zero latency, unlike with cloud-analyzed data. For precision time-sensitive tasks, this can make or break the functionality of IoT devices. Edge computing is a computationally efficient, secure, private, cost-effective way to utilize the Internet of Things at scale without running the risk of data breaches or network overloads. Additionally, edge computing offers a layer of resilience and redundancy for mission-critical tasks. Because this process is distributed—i.e. not centralized to a single system—if something breaks down, business can still continue uninterrupted while the broken element is fixed.

That is not to say that edge computing can’t work in unison with cloud-based analysis—it absolutely can and often does. In these instances, edge computing may serve to offer some real-time data as well as filter which data to upload to the cloud over time for use in deeper or more complex analysis techniques.

In an industrial IoT scenario, such as on a production facility floor, edge computing is duly important to reduce the risk of downtime or data breach as well as for more effective management of huge swathes of data. For manufacturers using edge computing, the low-latency aspect is a major boon for worker safety. For example, if the information collected from a data adapter shows subtle anomalies—e.g. chatter—that may indicate a stress fracture or other form of near-term failure, a machine can be immediately shut off rather than waiting for cloud analysis, the latency of which could result in downtime and scrap parts.

In short, edge computing analyzes some of the data from IoT devices at the edge of the local network—vs. transmitting it to the cloud—for faster, redundant, connectivity-agnostic IoT processing that is readily scalable.

Managing IoT Flood Gates

5th Generation Networks (5g), the Internet of Things (IoT) and Edge Computing are essential infrastructure enablers for a range of new business and technology developments, often termed Industry 4.0, that cover areas like autonomous vehicles, smart city grids, e-health, automated factories, mobile content streaming and data analytics. This marks a significant step on the journey to genuine digital transformation.

There will be 125 billion IoT devices, and cellular IoT connectivity will grow to 3.5 billion devices by 2030, as predicted by Ericsson Mobility Report. This IoT connectivity unleashes floods of data–Cisco expects to exceed 800 zettabytes.

Comprehensive IoT Toolkit

Toolkits can be easily tailored to your business needs and include all the essential tools needed to build an IoT solution right out of the box–and compiled into an intuitive web management console. The IoT appliance for each edge site must be simple to install without requiring programming and proprietary technology–and support a wide selection of data topologies with the capability to internally and simultaneously manage a wide range of protocols, including BacNet, Modbus, SNMP, MQTT, and raw serial strings.


Transparent pricing is essential. As are features for connection to cloud analytics services and third-party applications without the cost and hassle of on-site programming and can be easily wired to your subsystems or devices without additional costs or new equipment and systems.

Highly Scalable

Quickly scale to meet your needs, collect and manage data from one location or across a portfolio of thousands of global locations allowing you to harness critical insight on operations and efficiency without limiting portfolio size or future.

Open Integration

Without any major overhauls, integrate into/with your existing systems– including BMS – no matter what equipment, software or the technology you are currently using. This will improve business decisions using the data already available collectively under one management tool.

Hard-Wired Ethernet Connectivity

The best-in-breed IoT platform appliance should enable information access and communications through hard-wired ethernet connectivity to connect cellular communications for backup. The platform should also offer an outbound, internet-capable IP port (or cellular connection) to allow secure data transport – resolving issues of connectivity with various data sub-systems.

No Commissioning

Rapid provisioning of newly deployed data centers without required onsite commissioning is essential. This makes the availability of a single source Bit API a requirement for all the analytics by any edge data center provider.


To simplify connections and the IoT platform setup, cloud connectivity, and accessibility are critical. Cloud access will reduce costs and eliminate time-consuming on-site programming needs.

Without any major interruptions to business processes, edge data center facility operators can integrate an IoT Platform to gain access to all their critical data and issue a work order while gaining outlier detection and security. By managing operational costs by monitoring energy spend in real-time, operators can also gain real-time access to usage analytics, equipment maintenance, distribution planning, and facility deployments. Selecting the ideal IoT platform will empower you to access the best of actionable analytics for sound business decisions and get the edge off!