Abstract:
Availability of records on environmental factors like noise, temperature, and precipitation is important in making critical decisions concerning public safety and wellbeing. Traditional methods involving dedicated human personnel and equipment in capturing these data have been reliable, but extremely costly and time consuming. We propose a data collecting and visualizing framework based on crowdsourcing that is readily available, extensible, and virtually incurs zero cost. The crowd-sourced data mapping engine (CDME) presents an extensible back-end web application and a noise data collecting mobile application targeting analyses on noise pollution, which poses a significant concern especially in urban areas. The mobile applications runs as a service and updates the server with periodic noise data. The server accepts data updates and provides analytical functions such as graphs and heat maps.
