AiRXOS creates partnerships to create an “air operating system,” a five-month Canadian UAS BVLOS proof-of-concept trial, using drones to identify violent crowd behavior, and a chain of custody drone program for law enforcement.
AiRXOS is working with government agencies and others to help develop standard criteria for commercial drone operations. The company is a venture between GE Business Innovations (the corporate venture capital arm) and GE Aviation and is a wholly-owned subsidiary of GE.
AiRXOS (the “X” is silent) says they are “currently partnering with the FAA, FCC, NASA, ICAO, GUTMA and other industry stakeholders, to help define the architecture, standards, and implementation requirements necessary for the next generation of manned and unmanned potential.”
The Northeast UAS Airspace Integration Research Alliance (NUAIR) and AiRXOS previously announced a strategic initiative, and of the ten pilot programs under the Unmanned Aircraft Systems Integration Pilot Program (UAS IPP), AiRXOS was selected as a partner for three: the City of San Diego, the City of Memphis, and the Choctaw Nation of Oklahoma. Additionally, AiRXOS has been selected as a partner with DriveOhio’s UAS Center for UTM research, and AiRXOS is a partner with NASA’s Technical Capability Level (TCL) testing and the expansion of the LAANC service program (Low Altitude Authorization and Notification Capability).
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Canadian commercial drone operator IN-FLIGHT Data, drone-maker senseFly, and other partner organizations are starting a five-month “UAS BVLOS Proof-of-Concept Trial.” The goal is to demonstrate that BVLOS flights can be conducted safely and efficiently. The trial will run until early November and will collect a very large amount of geo-accurate data, across many types of long-range drone applications.
Researchers in the UK and India are developing an algorithm that analyzes drone video of crowds and indicates when violent behavior is occurring. The system uses a Parrot AR quadcopter, video over a real-time internet connection, and a “deep learning” algorithm that matches poses to violent postures, such as strangling, punching, kicking, shooting, and stabbing. Accuracy of the algorithm is an issue. See the Paper:
