The Development of a State-Aware Equipment Maintenance Application Using Sensor Data Ranking Techniques

Abstract

Billions of electric equipment are connected to Internet of Things (IoT)-based sensor networks, where they continuously generate a large volume of status information of assets. So, there is a need for state-aware information retrieval technology that can automatically recognize the status of each electric asset and provide the user with timely information suitable for the asset management of electric equipment. In this paper, we investigate state-aware information modeling that specializes in the asset management of electric equipment. With this state-aware information model, we invent a new asset state-aware ranking technique for effective information retrieval for electric power and energy systems. We also derive an information retrieval scenario for IoT in power and energy systems and develop a mobile application prototype. A comparative performance evaluation proves that the proposed technique outperforms the existing information retrieval technique.