SenseAPP: An IoT-Based Mobile Crowdsensing Application for Smart Cities

Abstract

Countries around the world are either developing smart cities or converting their existing cities to make them smart. One of the various smart city initiatives is to address environmental issues. Air and noise pollution are a major concern for many countries, and cities are failing to contain their pollution problems, which are indicated by high Air Quality Index (AQI) levels. The increased number of vehicles and restricted availability of parking spaces means more driving time to find an available parking, leading to increased vehicle carbon footprint. The main objective of this work was to develop an IoT-based mobile crowdsensing application to help alleviate air and noise pollution in cities. The main features of the application include 1) the identification of air and noise pollution hotspots and potential fire hazards so as to alert concerned authorities for appropriate and timely action and 2) efficient tracking of parking slot status so as to notify drivers of parking availability thus leading to less driving time and decreased air pollution. The mobile application, SenseAPP, collects data from registered participants' smartphone sensors, and microcontrollers, gas and temperature sensors placed at different city locations, thus leveraging both crowdsensing and IoT techniques. The data stored on a cloud database are processed to provide data visualisation on maps indicating pollution hotspots and free parking slots with customised markers.