2021 – Present
This project aims to tackle a significant gap in the Department of Homeland Security’s (DHS) capabilities for continuous threat detection. Specifically, it addresses the challenge of developing vapor detection systems that can operate without fatigue and can track a threat signature to its source, unlike trained canines, which require rest and ongoing training. The primary objective is to develop a portable vapor sensor system capable of continuous operation without human intervention to detect and track threats, such as explosives and gun oils, in densely populated areas.
This project employs a unique vapor sensor known as the Digital Dog Nose (DDN) to collect data from threat chemical samples and real-world tests at explosive ranges, with performance validated against state-of-the-art systems like mass spectrometers. The DDN utilizes small thermodynamic sensors mounted on mobile platforms or hidden in venues for detecting vapor-phase analytes like gun oils. These methods result in vapor detection that can be acted on by human operators. The project seeks to integrate its findings into real-world applications by offering a mobile sensor platform for use in venues like stadiums, malls, and transportation hubs. This platform could also be used by first responders, law enforcement, and military personnel to identify and track potential threats such as explosives or firearms, enhancing public safety by detecting non-invasive threats.
The project is advancing the current state of vapor detection by processing throughput 24 hours a day (300x compared to canines, who need to take breaks) and increasing the standoff distance required for detecting threats. These advancements allow for faster and more reliable detection in real-world environments, beyond what current systems like trained canines or existing vapor detection technologies can achieve.
In 2024, the project has focused on optimizing fluid flow simulations for its vapor delivery system and validating sensor performance through testing at explosives ranges. The team has also continued to improve their custom Schlieren camera system for better visualization of flow dynamics.
The project engaged key stakeholders such as the New York Fire Department (NYFD) support the project by exploring field trials for the DDN on robotic dogs used for counterterrorism. The project also benefits from partnerships with SENTRY stakeholders, including first responders, law enforcement, and government agencies for testing and deploying the technology. These partnerships help validate technology in real-world settings, offer access to necessary resources, and ensure the technology’s practical relevance. Collaborations with the NYFD and DHS enable field trials and provide critical feedback that informs future iterations of the sensor platform, helping to bridge the gap between research and deployment.