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An Energy-efficient and Self-diagnostic Portable Edge-Computing Platform for Traffic Monitoring and Safety

Award Information
Agency: Department of Transportation
Branch: N/A
Contract: 6913G623P800056
Agency Tracking Number: DOT-23-FH2-015
Amount: $149,995.68
Phase: Phase I
Program: SBIR
Solicitation Topic Code: 23-FH2
Solicitation Number: 6913G623QSBIR1
Solicitation Year: 2023
Award Year: 2023
Award Start Date (Proposal Award Date): 2023-07-13
Award End Date (Contract End Date): 2024-01-12
Small Business Information
52 Gardenhouse Way
Irvine, CA 92620
United States
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: Yes
Principal Investigator
 Lianyu Chu
 (949) 864-6696
Business Contact
 Lianyu Chu
Title: Lianyu Chu
Phone: (949) 864-6696
Research Institution

Recent advances in technologies have shown great potential for widespread use of Artificial Intelligence (AI) techniques in real-time Intelligent Transportation Systems (ITS) applications. However, the massive amounts of data collected and generated from ITS sensors pose a major challenge in data processing and transmission. This requires a shift from centralized repositories and cloud computing to edge computing. This project proposes an integrated low-power edge-computing system to work with computation-intensive traffic sensors (e.g., video, high-resolution radar, and Lidar) and weather sensors. The system will be designed to be portable, have self-diagnostic capabilities through monitoring sensors and system operations, and send out alerts and data when necessary. The proposed system will include an edge server, which will be developed based on a System-on-Module (SoM) using the latest AI chip, and an innovative hybrid camera that integrates a regular video camera and a FLIR thermal image camera. The project will identify and implement in-situ information processing and extraction algorithms based on machine learning and deep learning techniques to classify vehicles and detect events such as vehicle crashes, the presence of stopped vehicles, pavement and environmental conditions, and wildlife. The prototype will be demonstrated at a California test site in collaboration with Caltrans.

* Information listed above is at the time of submission. *

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