Optimizing Routes for UVA’s Facilities Management Fleet: Enhancing Sustainability and Pedestrian Safety; How can passive data collection and analysis be leveraged for ethical decision-making in the transition from fossil fuels to renewable energy

My capstone project seeks to help the Facilities Management (FM) group at The University of Virginia with route optimization and safety. Currently the FM group has advised drivers not to travel to work sites through McCormick Road, a road passing through central grounds. This is due to the high volume of students on McCormick road during the school week, increasing travel time as well as increasing accident risk. My team conducted research on exceptions of driving on McCormick Road, while also generating and proposing solutions for safer, more sustainable, and faster alternative driving paths to work sites around grounds. The data for this project was collected through Geotab, an online software that displays telematics data that is collected through a GPS device installed in FM fleet vehicles. The data of interest collected by Geotab includes speed, trips per day, routes taken per trip, and vehicle idling time. The data was then processed through python code to map out routes and travel times of different routes.
One ethical concern behind this technology is how it collects data on drivers' habits without them knowing what is being tracked. This means that with this capstone project comes passive data collection on FM drivers. The idea of passive data collection in support of optimizing systems is what my STS paper is going to analyze. With the growing dependence on data to help drive large-scale decisions, it is important to question whether it's ok or not to collect data without the user's immediate knowledge.
My STS paper breaks down the idea of passive data collection for system optimization with regard to the energy transition. The switch from nonrenewable to renewable energy is growing in popularity for its many environmental and economic benefits. However, whether or not energy consumption data can be used without the user's knowledge is up for debate. This problem will be analyzed through the actor-network theory framework. This framework analyzes how actors respond to changes in their environment and how environments also change how actors are perceived. The research for this paper was carried out through a qualitative analysis using a topic based approach on research papers related to passive data collection in technology, uses of energy consumption data, and user perspectives on passive data collection. Through this research I built understanding on what measures need to be taken, to reduce the ethical concerns surrounding passive data collection. In conjunction, the STS paper and the capstone project work together to address the socio-technical problem of how passive data collection can be responsibly leveraged for positive outcomes in optimizing current systems.