Geospatially Integrated IOT framework to advance justice: applying an equity lens to compare air quality at neighborhood-scale

Keywords: GIS, Air quality, Health and Environmental Justice, Smart City,
Abstract Type: Paper Abstract

Abstract

The smart city framework including the use of IoT, while initially received with enthusiasm, has been critiqued for reproducing urban inequalities rather than reducing marginalization. This paper demonstrates a pilot study in which integrated air quality sensors are deployed for criteria pollutants in two contrasting neighborhoods to demonstrate that a geospatially integrated IoT framework and web-based interactive platform called Community Resiliency Information Systems (CRIS) can be used to compare a white, affluent neighborhood with a marginalized, predominantly Black neighborhood in Saint Petersburg, Florida with an equity lens for baseline data collection and analysis to support communities of color in advocating on their own behalf.
Additionally, regulatory air quality data are not easily accessible to the public. CRIS addresses this problem by using a smart city framework with integrated sensors to make these data available to the public so community members can compare their air quality with others, thus allowing the empowerment of communities and providing data to support community advocacy for specific policies to address the environmental challenges they face. Further, CRIS facilitates the display of air quality data in the context of other mappable data such as poverty, race, and zoning – thus providing a context to aid interpretations of data so communities can easily access them and review them, including in their smartphones, and conduct a quick comparative analysis. CRIS thus provides a road map of how an IOT and smart city framework with integrated sensors can be used to address environmental justice issues in an urban environment.