&imwidth=800&imheight=600&format=webp&quality=medium "From sensors to soldiers, how AI is transforming battlefield intelligence")
Drones scan the skies. Thermal imagers search through darkness. Satellites photograph vast areas. Cameras monitor borders and critical installations. Radars and other sensors add still more streams of information. Modern battlefields are generating more information than soldiers and commanders can realistically watch. The problem is no longer simply collecting battlefield data. It is understanding it quickly enough.
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A commander could potentially receive feeds from dozens or even hundreds of drones and sensors. Human operators may be able to monitor a handful of them, but as the number increases, the actual information required can disappear inside an overwhelming volume of imagery. This is where artificial intelligence and computer vision are beginning to change surveillance.
Instead of requiring a person to continuously watch every feed, AI can analyse imagery, detect objects, identify movement and flag unusual activity. The objective is to transform raw surveillance into usable battlefield intelligence.
But military imagery presents challenges far beyond conventional CCTV. Camouflage can conceal equipment. Smoke and cloud cover can obscure targets. Weather can degrade imagery. An adversary can also deliberately attempt to deceive sensors and algorithms.
Atul Rai, CEO and co-founder of Staqu Technologies, believes the real value of AI lies in helping decision-makers navigate this flood of information. "AI is bringing the information to the decision maker," Rai said during a conversation on WION's Defence Pulse.
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But he also warned that the quality of the decision ultimately depends on the quality of information being processed. "If I consume wrong information, I'll make a wrong decision," he said, stressing that humans must remain closely involved in interpreting AI-generated intelligence.
The complexity increases when militaries combine information from different sensors. A normal CCTV camera largely works with conventional RGB imagery. Battlefield systems may simultaneously receive thermal imagery, satellite pictures and Synthetic Aperture Radar data. The same tank or vehicle can appear dramatically different across each sensor.
According to Rai, this makes data fusion one of the major challenges confronting military AI.
It would be a fair assessment that the next surveillance revolution will increasingly depend on whether AI can turn thousands of battlefield eyes into one coherent picture that a commander can trust and act upon.
