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Title	Enviroscale: Resilient Data Collection For Air Quality Monitoring In Developing Cities
ID_Doc	24277
Authors	Yusuf Sarwar Uddin Md.; Venkatasubramanian N.
Year	2019
Published	TESCA 2019 - Proceedings of the 2019 1st ACM International Workshop on Technology Enablers and Innovative Applications for Smart Cities and Communities, co-located with the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, ACM BuildSys 2019
DOI	http://dx.doi.org/10.1145/3364544.3373164
Abstract	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. © 2019 Association for Computing Machinery.
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