REDUCING CONGESTION AND ENHANCING SECURITY FOR SMART CITIES THROUGH IOT SENSOR NETWORKS AND REAL-TIME DATA COLLECTION

Abstract

IoT sensor networks are transforming smart cities by enabling real-time data collection that significantly reduces traffic congestion and enhances urban security. These networks deploy sensors at critical points to monitor traffic flow, vehicle density, and environmental conditions, allowing adaptive traffic management systems to optimize signal timings and reroute vehicles dynamically, which decreases travel times and lowers pollution levels. Advanced machine learning models integrated with multi-source sensor data improve decisionmaking for traffic control and environmental monitoring, supporting sustainable urban development. Additionally, IoT systems enhance public safety by detecting incidents, managing crowds, and facilitating emergency responses through real-time alerts and optimized routing. Ensuring data security and privacy is crucial; techniques such as encryption, blockchain-based integrity protection, and secure communication protocols safeguard sensitive information against cyber threats. Overall, the fusion of IoT sensor networks with real-time analytics offers a scalable, efficient approach to managing congestion and security challenges in smart cities while promoting sustainability and resilience