GreenSight has confirmed that its WeatherHive sensing technology has been selected by the US Air Force and the Defense Innovation Unit for incorporation into a prototype system. The technology, which was developed with the aid of funding from the National Science Foundation, uses swarms of nano-sized drones to directly measure atmospheric conditions.
The WeatherHive system can transverse up to 50 square miles per flight, generating a dense 3d cube of measurements. It provides a number of advantages over weather balloons, which can only capture data along a rising path, are fairly expensive per flight, and can only be used once leading to waste and pollution. Full-size manned aircraft may be used for data collection, but are highly cost-prohibitive for gathering large amounts of data.
The palm-sized WeatherHive nano-UAS weigh less than 150 grams and are extremely inexpensive and safe, automatically launching and landing in their “hive” for recharging and reuse. Dozens or hundreds can be used at once to gather large quantities of data regularly. Remotely deployable and disposable, WeatherHive is able to gather data in remote or contested areas, providing the capability the USAF needs to properly forecast weather conditions and inform military decision makers.
WeatherHive data shows promise to enable new breakthroughs in weather forecasting and climate science. Armed with data from WeatherHive, weather forecasting models may be able to much more accurately predict tornado formation, severe storm behavior, wildfire movement and hurricane paths.
GreenSight is developing WeatherHive using a selection of technology building blocks from the company’s robotics services platform. This suite of custom robotics hardware and software systems facilitates the development of innovative and impactful robotics technologies operating out in the real world where conditions and connectivity are not assured. GreenSight has worked with over 100 government agencies and private companies to bring their robotics and AI visions to reality.
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