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Improving Community and Neighborhood Safety Through Open Data Collection

Primary Investigators:
Daniel Balasubramanian
Brief Description of Project:
The goal of this project is to study how data obtained by members of the public through camera pictures, video feeds and similar technology can be used to improve public safety without unduly infringing on personal rights such as privacy. There are two main aspects to the project: the social aspect involves surveys, focus groups, and other community interactions to study how technology can benefit local neighborhoods. The technical aspect involves building a technical prototype using cameras, machine learning algorithms, mobile apps, and  backend infrastructure.

Desired Qualifications:
A background or interest in web development, backend development, machine learning, or social aspects like focus groups and surveys. Experience with either iOS or Android development is helpful but not required.
Nature of Supervision:
Direct supervision and mentoring; some shared coding experience
A Brief Research Plan (period is for 10 weeks):
-Introduction and existing code review
-Review of related literature (continual task throughout the summer)
-Write new test cases for existing code base
-Implement backend and/or UI improvements
-Cross-platform application testing and debugging to ensure consistent experience across web, iOS, and Android.
-Evaluation of various computer vision machine-learning models on embedded boards
Number of Open Slots: 1
Contact Information:
Name: Daniel Balasubramanian
Department: Computer Science