EnviroSCALE - Resilient Data Collection for Air Quality Monitoring in Developing Cities.

In this panel talk, we present our experiences regarding the development and deployment of an Internet of Things (IoT) based air quality monitoring system for developing cities. We consider the areas where widespread free WiFi is not prevalent; instead, the platform needs to rely on expensive and metered cellular data connections with limited data budgets. For the better utilization of the limited data plan, we apply two adaptation techniques in sensemaking. First, we adjust sensing intervals of periodic sensors so that the data volume remains bounded within the plan. Second, we enable putting application-specific software modules on-board through containers to process media data locally and thus to reduce bulk upload. The platform we developed is called EnviroSCALE (Environmental Sensing and Community Alert Network), which hosts a set of air quality sensors on a Raspberry Pi and uses a 3G connection to upload data. We outline our deployment experience of EnviroSCALE in Dhaka city, the capital of Bangladesh.