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dc.contributor.advisorWilliams, Sarah
dc.contributor.authorWoo, Wesley
dc.date.accessioned2022-06-15T13:08:57Z
dc.date.available2022-06-15T13:08:57Z
dc.date.issued2022-02
dc.date.submitted2022-02-22T18:32:02.749Z
dc.identifier.urihttps://hdl.handle.net/1721.1/143274
dc.description.abstractIn the past few years, air quality in the Global South has become recognized as a significant source of various health problems and general premature death. However, without appropriate data collection, reporting, and storage systems, it is difficult to both build community awareness and drive policy with air quality measurements alone. Furthermore, while investigations into poor air quality and its adverse effects have been conducted in resource-poor areas, the results of such studies rarely engage local communities and encourage collective action. Living Data Hubs is an ongoing project at MIT’s Civic Data Design Lab looking to address these issues. The project aims to reinvent data ownership through the merging of community-owned wireless networks and wireless sensor networks. In this thesis, I discuss the challenges of building digital infrastructure for low-resource communities through the design and implementation of an end-to-end PM2.5 measurement and data storage service for the Living Data Hubs project. The process of designing such a uniquely specified system reveals that minimal technical complexity and cost become essential in designing digital infrastructure for equitable community ownership. I also find that it is possible to bring together free cloud computing and storage tools to create an appropriately extensible and robust data storage system at a competitively low cost, although such systems run the risk of becoming dependent on foreign service providers.
dc.publisherMassachusetts Institute of Technology
dc.rightsIn Copyright - Educational Use Permitted
dc.rightsCopyright MIT
dc.rights.urihttp://rightsstatements.org/page/InC-EDU/1.0/
dc.titleCommunAir: Building Low-cost Community Data Infrastructure with Sensors, Spreadsheets, and Open Datasets
dc.typeThesis
dc.description.degreeM.Eng.
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
mit.thesis.degreeMaster
thesis.degree.nameMaster of Engineering in Electrical Engineering and Computer Science


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