Starting from the perspective of electricity safety, UK smart meter open data, and digital avatar, this study explores the value-added application of Taiwan's smart meters. In the past, we have cooperated with the Energy Bureau and ITRI to obtain a small amount of Taiwan smart meter data to analyze the behavior of electricity. This study improves the deep learning LSTM method, so that it can predict the three situations of unsafe electricity: instantaneous power consumption exceeds the standard, and continuous and frequent power consumption exceeds the standard. Additionally, we will establish an early warning system for unsafe electricity usage, and then combine IoT devices to collect environmental data, and use smart meters to predict electricity consumption. Finally, we will construct a virtual world in the field of testing, and demonstrate the power-saving rules in a digitally-divided way, so that residents can predict whether electricity is safe in the future and the power-saving behavior that can be performed in the case of personal privacy protection.
|Effective start/end date||1/08/21 → 31/07/22|
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):