Eseye author


IoT Hardware and Connectivity Specialists


As IoT use cases mature in line with the technology, potential applications for IoT and M2M become more data hungry, driving demand for high data rate and low latency connectivity.

To date, the most well-documented use cases for IoT have focused on the ‘massive IoT’ part of the spectrum, where deployments focus on large numbers of devices that typically serve small amounts of data, often at infrequent intervals. These kinds of applications are generally based on passive sensors that report on their environment and have little in the way of bi-lateral activity. Think of temperature, water or energy monitors.

But more ‘critical IoT’ deployments might focus on fewer endpoints and applications that are very much geared towards two-way connectivity, where the IoT-enabled device is relaying information back to a centralized IT system or even a human operator to act on in real-time, even sending commands back. Such applications could include control of an autonomous vehicle, or even remote controlled surgical equipment.

We need to be clear here that the term ‘critical’ is very much industry dependent however and should generally be understood as ‘critical to that industry’, in which case an application could be commercially critical, as much as it could be life- or well-being critical, or even national infrastructure critical.

What’s important to understand is that critical IoT use cases will have significant implications for how a solution is architected and the connectivity chosen to support it. Transforma Insights notes that “a simple ‘best efforts’ approach is increasingly unlikely to be acceptable to companies deploying such applications.”

These use cases, and the enterprises deploying them, will demand a much higher guarantee of reliability for network connectivity, including higher bandwidth and data rates, lower latency, and network redundancy or fallback connectivity in the event of network outage.

In some cases such applications are already being described as Ultra-Reliable Low Latency Communications (URLLC).

Latency is a measurement of time delay on a network – the amount of time it takes a data packet to travel from one location to another. In applications that depend on bilateral or two-way communication, such as a human operator controlling a drone, where the on-board camera is relaying information about the drone’s environment and the human operator is responding in real-time, it can be used to refer to the responsiveness of the application, or the time frame between a request being sent and the response occurring.

Typically measured in milliseconds when talking about network connectivity, low latency is critical for time-sensitive applications, including autonomous vehicles and industrial automation, where immediate response is required.

High-bandwidth connectivity is especially well-suited to real-time IoT applications with low latency requirements, especially when rapid transmission of large data volumes is involved, such as medical robotics used in surgery.

Typical use cases for high data rate connectivity in IoT revolve around the streaming of high quality video, such as remote controlling industrial machinery, or aggregating data from multiple sensors and relaying it back to the cloud controller for real-time decision making, such as with an autonomous vehicle.

Video feeds form a key part of many high data rate applications and the higher the definition the higher the bandwidth required. Video is typically supplemented by data from other IoT sensors adding more demands in terms of latency and bandwidth.

Autonomous Vehicles (AVs) such as driverless cars, trucks, or drones require low latency connectivity as the multitude of sensors on board rely on real-time communication for safety functions. Although a significant amount of data processing is performed locally on the vehicle itself, so that in a critical situation the car can return control to the human driver, large amounts of data are still transmitted back to the cloud.

Video is a key part of the Autonomous Vehicle or drone sensor array, and as technologies such as 5G introduce even greater bandwidth, higher definition video transfer will be possible.

It’s also expected that as more vehicles become equipped with IoT sensors, they will be able to interact with smart city management systems to optimize the flow of traffic or reroute around accidents or breakdowns.

IoT in industrial automation enables remote monitoring and control of machinery or robots in the manufacturing process. Low latency high data connections mean large amounts of information from sensors and cameras can be relayed and acted upon in real time.

Today this could mean monitoring how employees move about the factory floor, and data on temperature, pressure, and vibration of equipment on the production line. But as more advanced applications are being introduced we are expected to see remotely controlled robots, especially in more dangerous or remote industrial locations.

AR and VR applications are heavily reliant on video feeds of the environment around them. As devices or headsets are typically small, most of the compute is done in the cloud, making low latency high data connectivity essential for fast responses and an immersive experience.

Remotely controlled surgical robots have perhaps the greatest demands in terms of high data rates and latency. A surgeon operating on a person remotely needs the highest definition video available, and any delays in terms of latency could be life threatening.

In other healthcare applications, particularly where devices are monitoring vital life signs, large amounts of data may be transferred and need immediate response, making high data and low latency networks critical.

Emergency response services are increasingly adopting various technologies from above, such as drones and remotely controlled robots. In other applications, fire, police, and ambulance services may be streaming large amounts of high definition video and other IoT sensor data requiring real-time communication and coordination, which rely on high data rate and low latency connections. 

High data usage IoT applications require significant throughput on the bandwidth both upload and download, especially when streaming real time video and audio at definitions up to 4K.

Low latency is also essential, especially when the IoT device is being remotely controlled. Latency as low as 50ms for bidirectional response is considered close to ‘real time’.

Reliability is also a key factor. Connectivity redundancy and fallback options are required so the IoT device can connect to an alternative network automatically and immediately in case of an outages.

In a survey of IoT connectivity buyers in 2022, Transforma Insights found that the number one factor influencing selection of a vendor was ‘reputation/brand in IoT’ and that any vendor selling connectivity to critical adopters needs to ensure that they have a reputation for reliability and robustness.

4G and 5G cellular or WiFi connections are preferred options for applications that require real-time streaming or substantial data throughput, such as high definition cameras or monitoring devices.

High-bandwidth options such as 5G are particularly well-suited for real-time applications with low latency requirements, especially when rapid transmission of large data volumes is involved, such as medical robotics used in surgery.

5G is complementary to 4G, rather than a replacement, and as real-world adoption of 5G will be seen first in consumer devices, IoT deployments being planned today will rely on 4G for the next decade or so.

5G has bandwidths of up to 1Gbps, and enables high-speed communication with high capacities and very low latency. It can be used in mission-critical applications, such as autonomous vehicles, as well as applications such as VR, AR, gaming, and any use cases requiring real-time response.

Although WiFi also delivers high data rates, it can be slower compared to LTE in some scenarios, especially if the local network is congested. There is also more infrastructure involved, with a higher chance of misconfiguration or failure.

To this end, cellular is likely to provide more advantageous bandwidth geographically, when compared with many commercially available network options that are required to backhaul WiFi.

Ultimately, the parallel operation of 4G and 5G promises greater capacity and faster network speeds in the future.

When looking at Ultra-Reliable Low Latency Communications (URLLC), LTE 4G does offer significant benefits for IoT deployments broadly speaking.

An IoT-specific flavor of LTE, LTE-M, also known as Cat-M1, is designed for low-power applications requiring narrower bandwidth than LTE. It does have a longer range however, and can lead to power saving and cost savings for large-scale deployments compared to LTE, making it ideal for mobile and wearable devices.

That said, although cellular networks today cover around 98% of populated areas, they’re a long way short of territory coverage, which is often closer to 60%. This is a key consideration for IoT devices that must have access to a consistent, secure, and reliable connection always.

High data low latency IoT devices are already appearing in critical use cases across multiple industries, from industrial robotics to Autonomous Vehicles.

For high data IoT and M2M deployments, Eseye’s AnyNet+ multi-profile SIMs and eSIMs deliver automatic connectivity to the best available mobile network, wherever the installation is, and switch to an alternative if there’s an interruption.

Meanwhile, our Hera IoT edge routers monitor the performance of a connection, and if any changes are detected automatically alter the connectivity preferences to enable seamless failover. The Hera is used for a variety of critical IoT and high data applications including building management systems, EV charge points and payment processing, smart metering and monitoring and digital signage.

Finally, the Infinity IoT Platform™ enables enterprises to manage IoT devices across their entire estate from the skies to the factory floor, and monitor the connection status of every system, centrally, via a single view. The customizable and scalable platform is built around a policy-based software defined network (SDN), which provides extensible, secure, and reliable low latency connectivity.

The SDN mitigates the risk of global IoT deployments by supporting high speed communications between multiple resilient and secure data centres. The advantages of a policy-based SDN are that it removes the need to backhaul data around the world. Data instead is routed within a Private Domain which is much faster and increases resilience and redundancy.

Eseye’s policy-based SDN is based on a global Multiprotocol Label Switching (MPLS) backbone. We have 13 global data centers and on top of that multiple regional points of presence (PoPs) to ensure maximum connectivity resilience. Our global footprint includes more than 25 interconnects which in turn give us access to over 700 mobile networks – this means our infrastructure can comfortably support IoT applications that have high data requirements and low latency needs by offering maximum connectivity redundancy.

Eseye author


IoT Hardware and Connectivity Specialists


Eseye brings decades of end-to-end expertise to integrate and optimise IoT connectivity delivering near 100% uptime. From idea to implementation and beyond, we deliver lasting value from IoT. Nobody does IoT better.

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