The Industrial Internet of Things is increasingly becoming popular. It is described as the use of IoT in different biggest global industrial sectors, and commercial applications such as transportation, aviation, manufacturing, oil & gas, etc. IIoT involves the use of connected devices with industrial applications for process automation, remote monitoring, or predictive maintenance.
IIoT strongly focuses on M2M communication, Big data, and the applications of Machine learning. In industries, IoT-powered smart devices can be installed in supply chain robotics, solar and wind power, agricultural sensor systems, smart irrigation, etc.
According to studies, global spending on IoT-powered industrial platforms for manufacturing is predicted to grow from $1.67B in 2018 to $12.44B in 2024.
In recent news, AWS (Amazon Web Services) greatly emphasized the need for IoT and edge computing in industrial applications including vehicles and equipment sensors, and therefore AWS outstretched its reach of IoT and cloud computing to industries as well. Amazon CTO Werner Vogels said during his keynote at AWS re: Invent, “I actually call this the internet of billions of things”.
Predictive maintenance uses data analysis tools and related techniques to identify, predict and detect the failure of risk either in your business process or equipment. Earlier prediction not only lets you fix your hardware but also enables you to curb disasters before they even occur.
Predictive maintenance applications eliminate the risk of failure and automate the detection process. This technique allows companies to troubleshoot and possibly fix an issue before it reaches the end-user which results in improved maintenance processes, lesser costs, and higher customer satisfaction rates.
Automating business processes is the need of the hour because nowadays when the world is highly globalized and digitized, businesses simply can not afford to fall behind due to those same age-old traditional methods.
Therefore IIoT not only lessens human involvement but also eliminates the unnecessary manual labor that could otherwise lead to higher costs and ineffective processes. The reason why the Industrial Internet of Things drives efficiency and reduces cost and timely prevents risks.
The remote monitoring technique is the core of many IoT-powered industrial applications. Because it is challenging to focus on your equipment when it is out in the field or at remote locations such as in mines or deep wells.
IoT on the other hand makes it practical to monitor industrial equipment remotely such as tank monitoring in oil and gas industries, flow monitoring in agriculture, and chemical process monitoring in refineries.
Last but not least, even though industrial IoT application development is a cumbersome process, it’s not without its benefits. IIot not only improves the performance and productivity of industrial processes but also helps identify the risk of failure beforehand.
Moreover, in this digitized landscape, IIot addresses the challenges faced by industries to uncover opportunities and business value through predictive maintenance, remote asset condition monitoring, and process optimization.