Electrical fire monitoring IoT framework for ancient architectural complex leveraging edge computing

Abstract

SummaryElectrical fires caused by leakage, short circuit, overload, and other electrical failures occur frequently in residential areas, and failure to find and locate the fault location in time is the main reason for the evolution of circuit fault into electrical fire, especially in the ancient buildings with aging circuit facilities. Different from modern large‐scale buildings, ancient architectural complex is composed of a large number of scattered low buildings with inconsistent facility specifications and simple structure, so it does not have the conditions to deploy unified electrical lines and establish traditional large‐scale circuit monitoring system. In this study, we design an electrical fire monitoring IoT (EFM‐IoT) framework, which can realize early fire warning by monitoring the residual current of appliances and is easy to deploy in ancient buildings. EFM‐IoT adopts the data cleaning mechanism based on report form to filter redundant data, reducing computing and storage pressure in the cloud. Moreover, we analyze the energy consumption in the process of residual current and temperature data flow, and explore an effective energy‐saving mechanism for transmission. EFM‐IoT has been successfully applied in Chinese historical and cultural street—Pingjiang Road of Suzhou. Extensive evaluation and analysis results demonstrate that EFM‐IoT can effectively alleviate the data traffic and load in the cloud and reduce the response time of early warning.