Storage Battery 5G IOT Early Warning Method

• Main Authors: CHEN, YIN-CHUAN, 陳銀泉
• Other Authors: LEE, KUN-YI
• Format: Others
• Language: zh-TW
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/722b97

碩士 === 中華科技大學 === 機電光工程研究所碩士班 === 107 === This research is to develop an efficient power management solution by introducing IOT skills. We use big data analysis to achieve dynamic monitoring of lead-acid batteries and improve the accuracy of early warning.The method is detect and utilize wireless transmission. Transfer the usage status of the lead-acid battery to the cloud server system and store it. Analyze the use status and usage record of lead-acid batteries. When the usage status of the analysis is abnormal, the abnormal state is immediately returned to the control central. When the control central receives alarm for the battery. Notify the administrator immediately to replace the battery. After replacing the battery, the old battery is maintained or eventually discarded. It can effectively track and record the various usage states and used time of the battery. And make a battery usage status history. Use the complete big data to analyze the use of batteries, and to use it to evaluate the risk of power outages.In addition to regular maintenance and repair, we can track and reuse the waste batteries after recycling, so as to reduce environmental pollution.