A plug and play system for improved threat detection performance at security sensitive infrastructure

This 18 months industrial research project will develop a SafetyNet device for interpretation of x-ray images from security scanners for carry-on, hold luggage and parcels using automated image interpretation with deep learning technology. The system will automatically determine the level of threat posed by the object under the scanner, and provide a safety net around the human operator decision making. The device output will be integrated with existing scanners and used to alert the operator to the presence of threat items. The device will be tested on dual energy x-ray equipment in laboratory and at customer sites. The device will have universal appeal, integrating to a number of scanner models, making it a perfect option for retrofitting and new product line integration. The underlying algorithms and detection technology will be based around the use of adaptive self-learning neural networks which use underlying principles of deep learning. Such systems will learn from millions of images scanned and tested by human operators in an online setting. Once trained these will be applied for threat detection to assist human decision making. As more data is scanned, these systems will have larger archives to learn from, and will continue to grow their intelligence over time. The systems are expected to markedly improve performance in terms of increased quality of threat detection, higher screening throughput and reduced false alarms and resulting delays. SafetyNet will be offered to potential customers as a combined hardware/software offering with a cloud backend to which the device will communicate data on system and operators, which can be used subsequently for delivering data services to customers to report on reducing the risk of visual fatigue and inadequate staff training. The target markets for such system will include stadiums, arenas, border control, ports, aviation, commercial head offices, data centres and defence applications.