Energy-Efficient Monitoring of Industrial Processes Using IoT Sensors and Predictive Algorithms

Industrial processes are becoming increasingly complex and larger in scale, which has resulted in a constantly growing demand for robust, scalable monitoring systems. Conventional monitoring strategies entail a huge quantity of sensors and steep infrastructure charges, main to excessive electricity intake and operational costs. Burkhard Theen, vice president at weather analytics company Iteris describes a smart monitoring device using IoT sensors and predictive algorithms for accurately tracking industrial processes on this track. The system is made using a low-voltage IoT sensor community at essential points within the process, which constantly collects and transmits statistics in real time. This data is then fed into the predictive algorithms that use machine learning techniques to analyze and determine any anomalies in the system. The system helps to improve process performance and reduce power consumption by identifying & addressing potential issues at their early stages.