Multi-mode Big Data Mining and Analysis Based on Internet of Things on Power

Abstract

With the development of big data mining and artificial intelligence technology, the big data analysis in power is more and more used. At present, the big data is composed of power multi-mode data mainly includes PMS system of power equipment management, Scada system of power data acquisition and monitoring control, online monitoring system of various equipment, patrol system, intelligent video monitoring system and so on. The scale and dimension of these data are huge. This paper is based on Internet of Things with Logistic Algorithms and Neural Network Algorithms. By analyzing and predicting the probability of power failure through real-time monitoring data, the state of the power equipment can be evaluated, the potential risks in power operation can be evaluated and predicted, and the active warning can be given to improve the security of the system.