Cellular IoT Based System for Dynamic Real-Time Pollution Mapping in Urban Environment

Abstract

Rapid urbanization in developing countries poses air pollution challenges for urban areas caused by industry and vehicle emissions․ Challenges associated with traditional air pollution monitoring technologies include high costs and poor portability and geographic coverage‚ which make it difficult to monitor short-term and localized air pollution․ Other low-cost IoT solutions relying on Wi-Fi or LoRaWAN technology have their own limitations for outdoor use and dependence on local infrastructure‚ which can make monitoring and other applications difficult in other developing parts of South Asia․ This paper presents the design and testing of a low-cost‚ portable IoT system for monitoring and mapping short-term and localized air pollution․ The system monitors several air pollutants‚ including temperature‚ humidity‚ CO‚ and CH₄‚ and includes GPS and a two-part communications system involving a GSM network for in-field data collection and Wi-Fi and the Firebase cloud platform for remote data reporting․ The system hardware is designed in two-layer format to separate the power supply circuitry from the sensing system. A real-time web and mobile dashboard provide interactive spatial visualization of pollution hotspots. To demonstrate the usability of the developed system, field tests were conducted over a 14․2-kilometer urban route in Karachi‚ Pakistan‚ in the morning and night․ Test results show positive GPS mapping and data collection at nine sample sites and differences in other measured parameters between morning and night samples․ Applications of this technology include a infrastructure-independent complement which is scalable  to fixed monitoring networks in other areas lacking monitoring capabilities and‚ with calibration using data from other monitors‚ detailed air quality studies to support smart city and public health projects․