Abstract:
Acoustic Event Detection in Urban Environments is a software-based implementation that consists of sound detection, real-time acoustic analytics and deep learning algorithms to detect, classify and predict the environment. The said technology is able to identify audio intelligently and classify the detected sound for further actions. In this project we are aiming to develop real-time acoustic event detector with applications in smart cities like traffic flow regulation and crowd control. Urban security i.e. gunshot, screaming, shouting detection as well as environmental protection i.e. noise-level characterization in industrial areas and high-traffic zones will also be the main focus problems of this final year project. The report discusses, in detail, the problem statement, our proposed solution and applications followed by in detail analysis and coverage of the methodology/architecture used, milestones achieved and the future outlook of the project.
