Decentralized Edge-AI Infrastructure for Public Safety in Smart Cities: A Real-Time Response Model
Virendra Pratap Singh · International Journal for Research Publication and Seminars · 2023
The demand for better, quicker, and more robust public safety systems has increased due to contemporary cities' rapid urbanisation and growing population density. Due to latency, bandwidth constraints, and reliance on dependable internet access, traditional cloud-based infrastructure often falls short of emergency situations' demands for real-time responsiveness and dependability. This paper presents a decentralised Edge-AI architecture created especially to improve public safety management in smart city ecosystems in order to overcome these constraints. The suggested solution makes use of cutting-edge artificial intelligence models that are directly installed on edge nodes, including embedded computer units, environmental sensors, CCTV cameras, and microphones, to enable localised and independent analysis of important occurrences. These include the identification of criminal activity, traffic accidents, fires, unusual crowd behaviour, and abnormalities in audio, such as explosions or gunshots. The system guarantees low latency, improved fault tolerance, and reliable operation even in the event of network outages or cloud server failures by processing data at the edge.