Tech Sgt. Nathaniel Jackson, 99th Civil Engineer Squadron explosive ordnance disposal technician, begins a roadside bomb clearing operation during a training event June 7, 2017 at the Nevada Test and Training Range.

Tech Sgt. Nathaniel Jackson, 99th Civil Engineer Squadron explosive ordnance disposal technician, begins a roadside bomb clearing operation during a training event June 7, 2017 at the Nevada Test and Training Range. U.S. Air Force photo by Senior Airman Joshua Kleinholz

Here’s How the US Military Wants to Counter ISIS Drones and Roadside Bombs

Predictive algorithms, deep machine learning, directed energy, and more are all on the Pentagon’s shopping list.

It’s tough for humans to spot explosives and other signs that deadly roadside bombs may lie ahead, but the Pentagon’s lead IED-hunters think computers might be able to help, using the same kind of technology being developed to sift through hours of drone video.

Lt. Gen. Michael Shields, who leads the Joint Improvised-Threat Defeat Agency, is looking for ways to integrate “deep machine learning algorithms and [artificial intelligence] to increase the efficiency” of its analysts. Speaking Tuesday at a National Defense Industrial Association conference in Bethesda, Maryland, Shields said the military is looking for “the ability to train the algorithms to do things like object classification.”

He gave an example of sending a robot into a building that can look around and spot bombs or booby traps. “The ability to train the algorithms to go in — to fly in or to drive in — and to classify things like aluminum powder, dual-use components, [motion] sensors, things of that nature… so we never have to put a serviceman in harm’s way if possible,” he said.

“The IED continues to be our adversary's strategic operational and tactical weapon of choice,” the general said. The Pentagon “and the U.S. government have to be more agile, collaborative and innovative in order to be proactive to stay in front of the enemy so they react to us instead of us reacting to them.”

More Here: The NSA Is Using Bomb-Defusing Software to Grow the Next Generation of Analysts 

The Pentagon’s New Algorithmic Warfare Cell Gets Its First Mission: Hunt ISIS

The Islamic State militants and insurgent groups elsewhere have rapidly adapted to IED countermeasures developed by the U.S. and other nations. More recently, these groups are turning to booby-trapping computers and home appliances so they explode when moved, said Michael Cardash, an analyst with Terrogence and former commander of the Israeli National Police Bomb Squad.

“We’re seeing them in Iraq, we’ve seen them in Syria and we’re starting to see them lately as well in the Sinai as well … and we’ve been seeing them in Libya too,” he said at the same conference. “I would expect to start seeing them in other places where ISIS are operating in the Indian subcontinent, lately in the Philippines as well.”

The latest twist: explosives deployed by consumer-grade drones. Shields called them “airborne IEDs.”

Cardash said that militants are now turning to larger, commercial drones that can carry up to four bombs, displaying pictures of a drone that he said was “knocked down” in the mountains between Lebanon and Syria in recent weeks. Smaller drones can only carry one bomb.

“We do expect the technology to expand and the larger the payloads, the bigger the problem,” Cardash said.

Further complicating matters, Shields said, there is “no one technology that can completely defeat” this mixed group of weapons.

“To mitigate risk, we must develop technologies that can sense, detect and neutralize, while anticipating dual-use technology,” he said. “We need to take advantage of 3-D printing, software-defined devices, smart learning systems, additive manufacturing and nanotechnology.”

The general also noted that “innovation and rapid prototyping … will be major keys to future success in mitigating our adversary’s use of commercial off-the-shelf technologies.”

He also mentioned directed energy as a possible tool to defeat IEDs.

“Future initiatives and solutions must take advantage of new and predictive algorithms, strengthened through deep machine learning, artificial intelligence, the integration of neural networks, autonomous systems and manned and unmanned teaming,” Shields said.

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