The broader impact/commercial potential of this I-Corps project is the development of a non-lethal building defense system that will guarantee that no one can draw a firearm without being immediately detected and disabled. In the time that it takes for first-time responders to arrive at an active shooting scene, the lives of many defenseless civilians may be taken. This technology seeks to eliminate this time delay and to render the assailant unconscious. The proposed technology has the potential of having high impact on society as mass killings of children and innocent civilians leave deep scars for many decades. This technology will allow people to feel safer in any building, decreasing stress and anxiety, and may result in greater productivity. Applications include houses of worship, stores, homes, and commercial businesses. In addition, the proposed technology will allow those who cannot afford security guards to be safe from shooters. For those who can afford security guards, this technology offers a higher level of defense that also will help eliminate shoot-outs.

This I-Corps project is based on the development of a two-component, non-lethal building defense system composed of a robust, accurate target detection and classification system and a highly maneuverable Miniature Air Vehicle (MAV). The proposed research is based on weapon detection using computer vision, artificial intelligence, and machine learning algorithms to develop a multistep and multilayer system that combines multi-sensor data streams that feed a real-time dynamic world model through an object fusion subsystem, a rule-based system for refinement, a risk assessment system to advise appropriate actions, and physics models. These multiple steps and multiple layers will increase the likeliness of correctly identifying a weapon and a threating situation. Research for the second component will focus on the design of a MAV that will be small enough and fast enough to be hard to defend against, while capable of removing the threat. The MAV will be equipped with advanced target tracking with a non-lethal disabling payload. This research will advance scientific and technological understanding of MAV and aerodynamic surfaces operating at Reynolds numbers below 50,000 and the understanding and achievement of autonomous systems with exceptionally low false positives.

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.

Project Start
Project End
Budget Start
2021-02-01
Budget End
2021-07-31
Support Year
Fiscal Year
2021
Total Cost
$50,000
Indirect Cost
Name
University of Massachusetts Lowell
Department
Type
DUNS #
City
Lowell
State
MA
Country
United States
Zip Code
01854