In what ways, if any, can an AI detection of "anomalies" in video monitoring of crowds be implemented, ethically?
Partner: Software Construction Analytics and Evaluation - SCALE lab
A group of students is invited to consider if it is possible to create an ethical surveillance system for analyzing crowd behaviour and detecting unusual activities from real-world data captured from multiple sensors, provided by the University of California, Irvine. Such a detection system might operate by using Smartphone data to classify distinct pedestrian movement in crowds into the context dependent categories of “normal” or “abnormal”. The system might rely on non-visual data for the purpose of simplicity and ease in deployment. Involved students might have an interest in community surveillance and civil security, ethics, and urban studies and knowledge of artificial intelligence, digital processing, and geomatics.Want to learn more? Click here!
Sustainable Development Goals
- urban studies