Collaborative Research: SaTC: TTP: Medium: Securing Public Safety with WiFi-based In-baggage Suspicious Object Detection

Public safety has become an increasingly important issue in the United States due to the potential threat posed by hidden weapons and homemade bombs in public places where extensive security checks are not available. Traditional security systems, such as X-ray machine screening, are expensive and primarily deployed in high-security areas like airports and government buildings.

This project proposes to leverage the prevalent WiFi infrastructure in many public spaces to enable hidden object detection. The project team utilizes extracted WiFi signal features to identify the shape of hidden objects and determine their materials, and subsequently be able to detect suspicious items. The success of this project will greatly enhance public safety by offering easy to deploy and low cost detection systems at public venues (e.g., schools, theme parks, and sports stadiums), thereby addressing the urgent need for better safety in everyday public spaces.

Building upon the team's previous foundational work, this project investigates using received WiFi signal features to determine the types of materials of objects inside bags. Target identification models and domain adaptation frameworks based on deep learning techniques are designed to ensure a good identification accuracy in diverse environments. Robust shape reconstruction algorithm helps to recognize suspicious objects.

Additionally, new mechanisms using directional antennas are developed to mitigate the impact of the bag carrier's movements. The TTP project will create a prototype system and validate the system's functionality, accuracy, and robustness. The project team seeks to integrate the project's research efforts with educational activities such as developing graduate and undergraduate curricula.

The team will also recruit underrepresented students into the project. The team will work closely with technology collaborators for field trial and potential deployment into an operational environment.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.