Edge computing is a new technology that allows data to be processed locally on the edge of a network instead of at a centralized location.

Industrial IoT (IIoT) has been around for a few years now. In the beginning, IIoT was largely limited to traditional asset- monitoring applications such as systems that monitored oil pipelines or power grids. They would consist of sensors that would capture and send data to a central control centre for processing and analysis. This process can be time consuming and introduce latency into the system. Edge computing offers the solution to this problem by eliminating this lag.  It is a new technology that allows data to be processed locally on the edge of a network instead of at a centralized location.

What is Edge Computing?

Edge computing is an Information Technology architecture that enables data handling, analysis and management at the periphery of the network, as close to the source of the equipment as possible, without depending on a central network or a control center.  It can offer many advantages over centralized computing, including higher performance, lower latency, and reduced cost.


Here are some benefits of using this technology in industrial IoT applications:


The major risks associated with centralized computing are theft of information, accidental deletion of data, or tampering with data by insiders or outsiders. When data is stored closer to devices, however, it is less susceptible to these risks as the computation is being done closer to the source as opposed to a central storage.


Edge computing offers higher performance than centralized computing because all of the time sensitive computing can be performed at the edge node itself rather than at some distant location after being transmitted across networks. Since high-speed transmissions are required only occasionally when transmitting large amounts of data back up to the central location for processing, transmission may occur 10X less frequently than typically required by conventional systems.

Cost savings

Time sensitive centralized computing costs more due to increased system specifications that are required to handle streams of data and transmission costs. Edge computing keeps these costs to a minimum as time sensitive analysis and data operations can happen at the edge and only the important data is transmitted to the central server for storage or less time sensitive review.

Advantages of Edge Computing

In the past, industrial companies had to use a centralized computing system for all of their data processing and analysis. This means that data has to be sent back and forth from the sensors monitoring the machines to the centralized control centre. This process is not only time-consuming but introduces latency into the system. With edge computing, we can capture data at the edge of a network and process it locally instead of having to send it back and forth. The benefits of using this technology include higher performance, lower latency, and reduced cost.

Edge Computing for Industrial IoT

The growth and expansion of Industrial IoT has brought about a drastic increase in the volume of data that is available for the modern maintenance and reliability personnel. Large volumes of data require longer time for transmission and analysis, thereby delaying time-sensitive decision making that may make or break the industrial operations. Real-time data has become essential to ensure that the production units run efficiently, and optimally. With increased demand for scaling IoT solutions across plants and operations, the volume of data will only grow larger, making it even more difficult to compute these data sets in real-time.  Edge computing solves this emerging problem of scaling Industrial IoT by keeping the data close to the source, thereby offering faster and responsive network. Edge enabled IoT devices offer various advantages to modern industrial operators such as:

Last Mile Automation

IIoT devices will cause a paradigm shift in the industrial processes and operations through complete integration of sensing devices that allow for Machine-to-Machine communications. However, with higher number of IoT devices producing even larger volumes of data, sending data to control centres and waiting for actions to be taken, will eventually slow down the automation process. Edge computing can help to avoid this conundrum by eliminating the time lag between processing and communication, thereby allowing for last mile automation. 

Real-time Monitoring

With edge computing the data captured by the wireless sensors are analyzed right at the periphery of the network to identify any discrepancies. Only when a discrepancy is found, will these sensors transmit the data packet to the central server for a detailed analysis, while discarding all other irrelevant data sets. This ensures continuous real-time information about the performance of machines, without any transmission delay or overburdening a centralized computation system.

Increased Security

IIoT devices such as wireless sensors that are connected on the shop floor create multiple access points for hackers to exploit any possible loopholes in the network. As Edge enabled IoT devices perform the computations closer to the source, it reduces the risk of security challenges by connecting less frequently to the network, thereby making it harder to have any sustained intrusion.

Why Edge Processing is used in Industrial IoT

Edge computing is important to the industrial IoT (IIoT) space because processing data locally at the edge can offer many advantages over centralized computing. One of the major reasons why this technology is being used in IIoT applications, is because it gives engineers more flexibility in designing their systems. It also allows for greater scalability since it doesn’t require centralized infrastructure to process all of the data. Another key reason is that its architecture allows for faster response times due to the low latency processing of data. This means that when there are sudden changes in power flow or other changes in a system, engineers can see these changes immediately without having to wait for the data to be sent back from a central location.

Edge computing is the future of Industrial IoT, due to its ability to offer independence to IoT devices for data management and analysis. It is an emerging technology that leverages the power of smart devices to solve some of the most pressing challenges facing IoT today. It is the next major step in the evolution of data processing for IoT. Edge computing is truly a game changer and it holds the potential to change the IoT ecosystem as the technology matures.

About Nanoprecise Sci Corp

Nanoprecise Sci Corp is an automated AI-based predictive maintenance solution provider that facilitates remote condition monitoring with the help of an edge-to-cloud based technology solution that supports real-time analytics and allows users to monitor & optimize the equipment performance. Nanoprecise specializes in the implementation of wireless industrial IoT Sensors with Edge Computing capability in order to ensure full-time monitoring without full-time connectivity. Get in touch with us at to know more.