HEXWAVE is a weapons detection technology product that is being developed in response to the evolving needs of urban security in public spaces including sporting arenas, schools, malls, and places of worship. It is designed to improve threat detection and quicken the response time of security teams while minimizing interruption to the flow of daily life and foot traffic in these places.
It uses active 3D radar imaging and artificial intelligence (AI) to detect a range of threats, including both metallic and non-metallic weapons, in both indoor and outdoor environments.
By using AI rather than human assessment, the chances of a false detection due to human error are reduced. Further, no personally identifiable information is collected or viewed by security teams or other operations personnel, which helps protects the privacy and modesty of individuals.
Each HEXWAVE unit operates individually and can be combined with additional units that work together, making the system completely scalable to a facility’s unique security requirements. Additionally, each HEXWAVE unit is mobile and can be quickly deployed to a higher priority perimeter or entrance point based on crowd control or other operational factors.
What is HEXWAVE?
HEXWAVE is Liberty’s proprietary weapons detection product and consists of four major subsystems that work together:
- Antenna Array and Transceiver (captures real-time data)
- 3D Radar Image Generation (converts captured data into 3D radar images)
- AI and Deep Learning (interprets the data and 3D radar images to detect threats)
- Smart Interface Functionality (provides connectivity to existing security systems)
1. Antenna Array and Transceiver (captures real-time data)
Liberty has the exclusive global license for active 3D radar imaging technology from the Massachusetts Institute of Technology (MIT). In this design, a transceiver generates the low power radio frequency signal which is then sent through array antennas to illuminate the detection space. The array antennas receive the reflected signals containing the data.
2. 3D Radar Image Generation (converts captured data into 3D radar images)
This subsystem receives the data from the antenna array and converts it to a 3D radar image.
3. AI and Deep Learning (interprets the data and 3D radar images)
HEXWAVE uses AI and deep learning to recognize concealed weapons and predict the weapon type. This component of the technology uses artificial neural networks (ANN) which is an advanced AI method derived from how the human brain learns and recognizes objects. The actual training of the neural network is done at Liberty’s Engineering Centre of Excellence (COE) in Atlanta, Georgia.
4. Smart Interface Functionality (provides connectivity to existing security systems)
This enables HEXWAVE to interact with a facility’s existing security infrastructure such as surveillance and access control devices. It provides connectivity and internet of things (IoT) integration with IP surveillance devices and also provides both analytics and threat alerts that can be sent to surveillance and access control devices.
About Liberty Defense
Liberty Defense Holdings, Ltd. (“Liberty”) (TSXV:SCAN; FRANKFURT:LD2) provides security solutions for concealed weapon detection in high volume foot traffic areas and has secured an exclusive license from Massachusetts Institute of Technology (MIT), as well as a technology transfer agreement, for patents related to active 3D radar imaging technology that are packaged into the HEXWAVE product. The system is designed to provide discrete, modular and scalable protection to provide layered, stand-off detection capability. This is intended to provide a means to proactively counter evolving urban threats. The sensors with active 3D radar imaging and Artificial Intelligence (AI)-enhanced automatic detection are designed to detect metallic and non-metallic firearms, knives, explosives and other threats. Liberty is committed to protecting communities and preserving peace of mind through superior security detection solutions. Learn more: LibertyDefense.com
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