Da Zhi Xiao Neng intelligent service robot is an intelligent operation and maintenance management APP specially designed for new energy enterprises (photovoltaic, wind power, energy storage, etc.). It deeply integrates AI algorithm and Internet of Things technology, and realizes equipment life cycle monitoring and accurate health assessment by collecting equipment operation data in real time (such as photovoltaic panel temperature, fan speed, and battery pack health status). The accuracy rate of abnormal detection is over 95%, and it can warn potential failures seven days in advance, greatly reducing the risk of unplanned downtime. The application is compatible with mainstream brand inverters, fans and energy storage systems, supports API docking enterprise ERP and SCADA systems, breaks data silos, and has a built-in carbon emission tracking module to generate green electricity operation and carbon emission reduction reports with one click, helping enterprises meet ESG compliance requirements. Based on the fusion of self-developed AI model and meteorological data, the equipment performance decline trend can be predicted, the maintenance cycle and spare parts replacement scheme can be intelligently recommended, and the work order can be automatically distributed to the front-line personnel mobile terminal simultaneously, and the average fault response time can be shortened to 1.5 hours. On the technical level, the edge computing terminal and cloud digital twin collaborative architecture are adopted, and the false alarm rate is lower than the industry average of 40% in complex environments (such as high altitude and extreme temperature difference), and the zero-code drag-and-drop interface is supported to configure the monitoring large screen, which greatly reduces the use threshold. Provide double guarantees of data encryption transmission and localized storage, and support privatization deployment. It can reduce the annual operation and maintenance labor cost by 45%, reduce the power generation loss by 18% and shorten the investment return period by 2.3 years.
