IOT-DRIVEN URBANAIRGUARD SYSTEM FOR ENVIRONMENTAL POLLUTION TRACKING AND MANAGEMENT

Abstract

Rapid urbanization and industrialization have intensified air and noise pollution, posing serious threats to environmental sustainability and human health. Conventional monitoring systems are often expensive, static, and limited in coverage, making them inadequate for realtime surveillance. To address this challenge, the proposed IoT-driven UrbanAirGuard system leverages sensor networks, wireless communication, and cloud-based analytics to provide real-time tracking and management of air and noise pollution in urban environments. The system employs low-cost, energy-efficient sensors to measure key parameters such as particulate matter (PM2.5, PM10), carbon monoxide (CO), nitrogen oxides (NOx), sulfur dioxide (SO₂), and noise intensity levels. Data is transmitted to a centralized IoT platform where it is processed, visualized, and analyzed for actionable insights. The integration of geolocation services further enhances pollution mapping and hotspot detection. By providing accurate, scalable, and real-time data, the UrbanAirGuard system supports policymakers, environmental agencies, and citizens in mitigating pollution and promoting healthier, sustainable urban living.