via Nextdoor: (posting in part because no login is required here, so hopefully more people will see and respond)
My name is Devin Harris and I am a Professor at UVA. My background is Civil Engineering and we are researching concepts related to quality of life within communities. I have been part of the Crozet community for the past six years and thought this might be a great place to get some informal feedback on our work. I was reaching out to assess potential interest in our study that focuses on opportunities to understand and improve quality of live in neighborhoods and communities. In brief, this study aims to use a crowd-sensing approach by encouraging community members to take and share data (specifically pictures and descriptions) of issues of concern in their neighborhood/community such as congested streets, sidewalks in disrepair, flooded streets, fallen traffic signs, potholes, etc. These data (primarily images) would then to be used to create models that will automatically detect the issue and report them to decision makers. Such models are expected to help decision makers and members of the community with necessary information for solving the issues. The schematically demonstrates this idea (Note: This is only illustrative of the concept and not real data).
At this point we are not soliciting any participation, but I would like to assess potential interest. If you would so kind as to fill out the attached survey about your potential interest in such an idea, I would really appreciate your input. We are not collecting any information about those participating in the survey, only gathering some basic numbers on who might be interested and how they might be willing participate. The survey is four simple questions and will probably not take more than 30 seconds to complete.
Thank you in advance for participating in this effort.
Devin K. Harris, Ph.D.
Associate Professor – Department of Civil and Environmental Engineering
Director – Center for Transportation Studies
Faculty Director of Clark Scholars Program