TECHNOLOGY
IED (Improvised Explosive Device) detection imaging technology is a critical component of counter-terrorism and military operation to mitigate the threat of explosive devices that are often crafted from unconventional materials. Detecting (indirect) indicators of IEDs is crucial to prevent potential harm to vehicles and crews. Various imaging technologies and techniques are used for detection, such as: X-ray imaging, Magnetic Resonance Imaging (MRI), Millimeter-Wave Imaging (MMW), Ultrasonic Imaging, Radar Imaging, Sniffer Technologies, Acoustic Imaging and Infrared Imaging.
The choice of imaging technology depends on factors such as the required level of detail, penetration capabilities, safety considerations, and the specific operational environment. A combination of imaging technologies, radar and AI is often used to improve overall detection capabilities.
Nedinsco developed multispectral camera technology for the detection of (indirect) indicators of IED’s. A variety of IED indicators such as digging tracks, tool marks, changes in the terrain and unusual structures or items can be detected by special cameras.
Day sight cameras are combined with infrared cameras to support the visual analysis of the IED indicators.
Infrared sensors are very reliable detection devices, as thermal contrast is visible. IR cameras detect heat signatures emitted by objects. Infrared sensors can operate in low light or complete darkness, they are non-intrusive and can be used for remote detection. This technology can be used to identify irregularities or hidden objects that may be related to IEDs.
Often the same routes are driven multiple times on a patrol. That’s where change detection comes in. Change detection allows automatic detection of objects that were not there before. Images from the previous patrol are compared with images from the current patrol. Video surveillance combined with AI technology can be used to monitor and analyze video footage from patrols to identify potential threats. Change detection AI looks for non-natural objects and checks if these objects were there before. There are many challenges in using this technique because there are many more changes in each scene than just objects. There may be moving branches, leaves, weather conditions, light, shadow, etc.
The image on the right shows that a digging track of an Anti-Tank mine becomes much more visible with infrared.
Artificial intelligence (AI) plays an important role in improving the efficiency and accuracy detecting indirect indicators of IEDs. The use of AI in this context includes the application of machine learning algorithms and computer vision techniques to analyze data from various sensors and imaging technologies.
AI algorithms can be trained to recognize patterns associated with indirect indicators of IEDs in images and videos captured by surveillance cameras.
In military and security applications, AI is used to analyze data from various image sensors to detect indirect indicators of IEDs in inaccessible or dangerous areas. AI systems can adapt to changing environments and changing threat scenarios by continuously learning from new data.
It is important to note that a combination of a variety of technologies and methods is often used to improve the overall effectiveness of explosive threat detection systems. In addition, the capabilities of these detection systems are continuously improved through ongoing research and development within Nedinsco to stay ahead of changing threats.
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