Start-up’s AI-enabled system teaches drones to help fight wildfires
By DRONELIFE Feature Editor Jim Magill
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When responding to wildfires, time is critical. Response commanders need to be able to rapidly access data to answer vital questions – where is the fire the hottest? What direction is the wind blowing? Are there any humans located in the danger zone – before making any decisions on fighting the fire.
A start-up software and drone company in Washington state has developed a system for answering these questions using artificial intelligence (AI) programs and highly stable and agile coaxial drones.
Launched in 2022 by three aviation industry experts, DataBlanket’s mission is to empower firefighters with new tactical tools and information.
“To me firefighting felt like a problem that has needed addressing for quite a few years,” DataBlanket Co-founder and CEO Omer Bar-Yohay said in an interview.
Bar-Yohay has an extensive record of serving in the Israeli military, as well as being a leader in the civilian defense electric aviation industries. He formed DataBlanket with Yair Katz, a long-time friend and colleague, and Gur Kimchi, who cofounded and led the Amazon Prime Air drone-delivery service.
After serving In the Israeli defense forces for 12 years, in 2015 he founded Eviation Aircraft, where DataBlanket’s co-founder, Katz served as chief operating officer. Eviation developed, built and flew the world’s largest all-electric commuter aircraft. Bar-Yohay left Eviation in March 2022 to form DataBlanket.
His military background, especially his work in special operations, led Bar-Yohay to believe that some of the technologies and tactics developed for Israel’s defense could be applicable to battling wildfires. “There needs to be more joint operations per se, more seamless exchanges of information between ground and air operations and better situational awareness in general,” he said.
The DataBlanket system employs coaxial drones, manufactured by Ascent AeroSystems. Ascent is an American company, whose products are approved for use by the U.S. military under the Blue sUAS program, a fact appreciated by many public service agencies looking to avoid the use of drones produced in China. The fast-flying and agile drones are capable in of operating in inclement weather conditions such as high winds, typically associated with wildfires.
“Large fire events tend to create their own weather challenges, with crazy inversions of winds,” Bar-Yohay said. “We want to be able to fly there even when other assets cannot be operated. The drones can operate in winds of over 50 miles an hour.”
To equip them for fighting wildfires, DataBlanket has equipped the Ascent drones with its own sensors and AI-driven technology. “On top of the Ascent platform, we’ve integrated a very significant number of sensors, obviously to see what’s going on, but also for sense-and-avoid and for airspace mitigation,” he said. The company also adds a platform developed by Santa Clara, California-based NVIDIA that runs all the computer-vision pieces, onto the drone.
The system is designed for quick deployment, with the incident commander being able to deploy as many as eight drones at once. “Those drones will look towards the area you’ve asked them to scan, identify major things like smoke, fire, stuff like that, and if you’re in search-and-rescue mode, they’ll actually map more accurately.”
Under the company’s firefighting management system, the AI technology assists in the operation of the drones, but does not have full operational control of them, Bar-Yohay said.
“So, there are very clear boundaries as to what the system is allowed and not allowed to do,” he said. “The management of the assets within those boundaries is very much non-deterministic and uses what you could call AI to optimize them.”
Once the drones are deployed, and the system receives input from the computer-vision software, it can make its own decisions based on an algorithm, which tells the system how deeply it should dig into the visual data before determining if that data is significant enough to require filing a report to the incident command.
“One of the most painful things in automated detection is false positives. You don’t want the whole system to go crazy for a cloud, if it’s not smoke. You don’t want the whole system to be thrown off because it identifies something that was hot, but was not fire,” Bar-Yohay said.
For example, if the system detects a figure walking upright within the fire zone, it could decide to focus more resources to take a closer look to determine if that figure is a lost person a or a frightened bear. The system could order a second drone to drop beneath the forest canopy to fly lower, or use thermal sensors to identify the mysterious figure.
The system uses its assets to augment the worldview that it perceives and to constantly create more and more knowledge about that worldview, “helping you, the operator, understand through the app, what’s out there to see: for real and what’s important. And we found that these are the two areas are slightly different, where AI algorithms really do pretty well.”
DataBlanket, which is in the pre-revenue phase of its corporate life, last December closed its seed round with lead investors: Breakthrough Energy Ventures, founded by Bill Gates, and Innovation Endeavors, which funds technological startups and which was co-founded by former Alphabet CEO Eric Schmidt. The company has also attracted investment from New Vista Funding as well as from family and friends of the co-founders.
Bar-Yohay said the company has secured one of the authorizations it needs to operate from the Federal Aviation Administration and has filed for critically needed authorization to conduct drone flights beyond the visual line of sight. “I suspect that it will still take a few months and a few more tests for the FAA to give us the full BVLOS capabilities that we’ve asked for but we’re on the right path there. I would say the FAA has been very, very conscious of what we’re doing and they’ve asked the right questions,” said.
He said DataBlanket has already received inquiries into the use of its system from firefighting agencies, such as in Orange County California and other jurisdictions across the West Coast. The company plans to begin conducting pilot programs in the field next year with a broader deployment of the technology in the late-2024, early- 2025 time frame.
Given his background, Bar-Yohay also expressed his deep concern over the fate of his countrymen during these fraught times in the Middle East.
“We just hope everything works out alright. Let’s hope it will end soon.” he said.
Jim Magill is a Houston-based writer with almost a quarter-century of experience covering technical and economic developments in the oil and gas industry. After retiring in December 2019 as a senior editor with S&P Global Platts, Jim began writing about emerging technologies, such as artificial intelligence, robots and drones, and the ways in which they’re contributing to our society. In addition to DroneLife, Jim is a contributor to Forbes.com and his work has appeared in the Houston Chronicle, U.S. News & World Report, and Unmanned Systems, a publication of the Association for Unmanned Vehicle Systems International.
Miriam McNabb is the Editor-in-Chief of DRONELIFE and CEO of JobForDrones, a professional drone services marketplace, and a fascinated observer of the emerging drone industry and the regulatory environment for drones. Miriam has penned over 3,000 articles focused on the commercial drone space and is an international speaker and recognized figure in the industry. Miriam has a degree from the University of Chicago and over 20 years of experience in high tech sales and marketing for new technologies.
For drone industry consulting or writing, Email Miriam.
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