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7a.010.UL - Event Detection and Classification from Live Video Streams

Project - Summary

Current Smart City developments target a narrow scope of what truly Smart City operations could be. This is largely due to lacking an interoperable infrastructure that is capable of handling large volumes of heterogeneous data and turning this data into actions. For example, monitoring/controlling traffic flow across the city requires significant streams of sensor data of varying formats, types, and volumes. While this poses significant challenges to any underlying infrastructure support in terms of storing, managing, modeling, learning, and securing such data, the true challenge lies in how to make such data actionable and useful in everyday scenarios. The massive amount of real-time sensor data generated in such scenarios will quickly outstrip human cognitive capabilities, thus presenting two technical challenges: (a) how to translate these data into semantically meaningful knowledge that can support decision- making processes and be converted into actionable outcomes, and (b) how the system can continuously learn to improve actions taken, reduce end-to-end response time, and effectively share knowledge between different system components.

Project - Team

Team Member Role Email Phone Number Academic Site/IAB
Khalid Elgazzar PI Not Available UL Lafayette
Magdy Bayoumi Co-PI (337) 482-5365 UL Lafayette
Twisampati Sarkar Student Not Available UL Lafayette
Mohamed Seliem Student Not Available Not Available UL Lafayette
Sumit Shah Project Mentor (202) 309-8790 CGI

Project - Novelty of Approach


Project - Deliverables

1 Data preprocessing and cleaning algorithms
2 Event Classification and Learning Techniques
3 Fully functional proof-of-concept prototype to demonstrate the feasibility and usability of the proposed technology

Project - Benefits to IAB

Research outcomes of this project will open up a vast opportunity to offer a wide range of new services across multiple domains, especially in smart city settings. The developed technology also will be of great value to public safety and emergency response services, disaster managements, urban sensing and law enforcements. The research outcomes of this project will help CGI and other IAB to pursue business opportunities across multiple civilian and defense federal agencies as well as state and local government, and commercial customers. Companies serving public sector will take advantage of these techniques to improve safety and emergency response time.

Project - Presentation Video

Project - Documents

projects/year7/7a.010.ul.txt · Last modified: 2021/06/02 16:35 by sally.johnson