5G has been in the news lately for many reasons, not least of these because of its significant impact on the number and range of devices that it will connect to the internet. Its ability to improve edge computing, bandwidth, and connectivity within cities and across rural areas is promising. And right there at the edge we find internet of things (IoT) devices — sensors, data relays, and small computing devices — that will power the automated data collection necessary for the next generation of ERP.
5G and IoT
5G capabilities for wireless connectivity will be crucial in the extension of IoT to more capabilities and use cases. Most importantly, it will bring data transfer latency across the network to near-zero. According to NetworkWorld, 5G has a “theoretical latency of less than one millisecond,” which is a vast improvement over today’s WiFi latency of 20-40 milliseconds.
The speed of data transfer will undoubtedly improve the current use cases of IoT devices. What we’re looking at is an ability for companies to directly monitor the conditions and automated responses of tooling and mechanical devices in near-real time. When we can implement near-instantaneous data transfers, artificial intelligence (AI) or machine learning (ML) can stop processes, change course, or alert the manager on call to changes.
The internet of things is built from sensors and simple data processors that are connected to the internet. Whereas putting an individual computer on every single freight car on a train would come with a lot of expense and energy consumption, putting an RFID or GPS chip on each car and a single computer at the engine to gather and process the data is much more energy efficient. 5G capabilities ensure that every car is connected to that central computer and the computer to the ERP system in the cloud, even in the most rural areas.
IoT’s impact on ERP
Consider how precision manufacturing, mining, and utilities companies could benefit from near-constant and real-time autonomous monitoring. In the 1990s, my father split a 24-hour shift with a coworker to run a massive precision tooling machine that made molds for twenty foot tall fresnel lenses. Running this machine cost thousands of hours and hundreds of thousands of dollars.
Today’s automation would allow a company to better use the time and money than spending it on manual observation. With an IoT-connected ERP monitoring the machines, the company’s highly trained engineers and machine technicians could spend their time working on research and development and improving the manufacturing process, and the company could improve the employees’ quality of life. Instead of standing by a machine to monitor the speed, temperature, humidity, or lubrication levels, each of these vital statistics can be monitored by IoT sensors that pass data to an integrated ERP.
The next generation of ERP
Real-time data collected via the IoT and ported into an advanced enterprise resource planning software is key to running the autonomous world of the future. ERP systems that are built for tomorrow’s IoT landscape not only gather more data, but they also directly port that data into the right tool for its business function.
If today’s technological trajectory continues toward autonomous logistics and delivery services for industrial and commercial use, and we continue to connect, collect data from, and automate every part of our lives, all of these IoT devices at the edge will require increased connectivity across the open spaces of the world, increased channels to pass data, and increased speed to reach real-time data collection.
Also Read: What You Should Know About Edge Computing
And today’s data collection is the basis for tomorrow’s artificial intelligence and machine learning tools. The real-time data that IoT collects and stores in the ERP can train AI and ML tools according to actual scenarios.
The tools, of course, require intense security measures to secure the transmission of data and the integrity of the data in transit. This is somewhat mitigated by the relative simplicity of the IoT tools: there are fewer moving parts in each of the endpoints, but of course to fully reap the benefits of the IoT landscape, the tools require exponentially more endpoints.
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