Predictive Maintenance in WSN based on Machine Learning

Abstract

Predictive maintenance is one of the key concerns in the field of wireless sensor networks. The purpose of predictive maintenance is to reduce unplanned energy consumption, to increase lifetime of the network and to reduce costs and delays. Predictive maintenance system is a new concept that aids the system to monitor and evaluate the status of those systems for which they are being developed. They also assist in maintaining the actions of these systems by predicting the future quality. With applications in industrial monitoring, smart cities and environmental sensing, the integration of AI and predictive maintenance in WSNs presents a promising path towards intelligent, economical, and scalable network management. In order to tackle the issues of sensor failures, network instability and system deterioration, this paper investigates the predictive maintenance in WSNs and along with the predictive maintenance and machine learning concepts