Drone-Human Safety Protocols

Launching and landing unmanned aerial vehicles (UAVs) from a mobile location like a vehicle without exposing personnel to danger. The system has a protective enclosure mounted on the vehicle that stores and protects the UAVs. The UAV launch/land pad inside the enclosure raises and lowers the UAVs between storage and launch positions. The pad has articulating arms to fold for compact storage and unfolds for launch. The UAVs are remotely launched and operated from inside the vehicle without needing personnel outside.

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A system for increasing the flight safety of drones and other multicopters. The system uses a matrix of controllable lights on the drone body to indicate the drone's flight direction to observers. By illuminating patterns on the drone that show its current direction, like a moving arrow or color-coded frames, people nearby can be more aware of its flight path and avoid collisions. The lights are controlled based on the drone's internal flight direction sensors.

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Flight control system for unmanned aerial vehicles that enables safe passing of nearby aircraft. The system detects nearby aircraft and determines if passing is possible based on their trajectories and airspace conditions. If passing is possible, it controls the drone to perform a passing maneuver at a safe distance from the other aircraft.

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System for mid-air collision avoidance and traffic control between unmanned aerial platforms with different priority levels. The system involves CAS (collision avoidance system) units on each platform that intermittently transmit their locations. Higher-priority platforms can receive these transmissions and calculate collision risks. If the risk is high, the higher priority platform CAS unit generates and transmits steering commands to the lower priority platform to avoid a collision.

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Alerting people on the ground when a drone malfunctions and is likely to crash. The drone notifies a network node of the issue and estimated crash point. The network node then sends warning signals to devices in the area to clear out.

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Automated search and rescue system that uses drones to quickly locate survivors in disaster situations and relay vital information to rescuers. The drones are equipped with sensors to detect survivors buried in debris and a data link to transmit that information to a command center. This allows rapid deployment of drones to scan large areas and identify survivors without putting human rescuers at risk.

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Intelligent UAV group flight real-time monitoring and anti-interference safe emergency landing device based on information security. It uses encrypted wireless communication, positioning, and real-time environmental sensing to enable safe group drone flights. The device has drones with encrypted modules, an app, and edge computing. The app assigns flight positions, sequences, and triggers group flights. The drones transmit encrypted data. The edge device senses environment. If a drone deviates, loses control, or runs low on power, the edge alerts the app to initiate safe emergency landing for all drones.

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Unmanned aerial vehicle (UAV) that can release a warning alarm device when it detects an abnormality that may cause a crash. The UAV monitors its flight and when it senses an impending failure, it detaches and deploys an alarm device to warn people on the ground. The alarm device can have a parachute to slow its descent and stay airborne while sounding an alarm or displaying a warning message. This provides a way to alert people below about an imminent UAV crash so they can evacuate the area.

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Quantitative approach and departure risk assessment for aircraft flights to evaluate the danger posed to people on the ground in the event of a crash. The system calculates potential crash areas, crash footprints, and risk values based on population data along the flight path. This allows optimizing flight paths to minimize risk to people on the ground.

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Provisioning and coordinating flight paths for commercial drones that integrate with public airspace to enable safe and regulated drone flights. It involves generating flight paths and cross-sections based on drone capabilities, payloads, and locations. Drones are sent these pre-defined paths that they must fly within. This allows planning and enforcement of safe routes with deviations permitted. The system tracks flights and adherence to guidelines. It enables commercial drone operations through public airspace in a regulated manner while avoiding collisions and other risks.

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An automatic crop-spraying unmanned aerial vehicle (UAV) system that can improve safety by dynamically adjusting the early-warning range for staff and automatically pausing when someone enters that zone. The system analyzes video during spraying and if staff are detected in a calculated early-warning area around the spraying range, it pauses spraying until they leave.

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An unmanned aerial vehicle delivery system that notifies a recipient that their delivery has arrived at a transfer location. The system determines visibility at the transfer area using sensors on the delivery drone. If visibility is poor, it sends a notification to the recipient to not come to the transfer area. If visibility is good, it notifies the recipient to come pick up the delivery. This prevents recipients from traveling to the transfer area when conditions are unsafe.

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Dynamic supervisory control method for unmanned aerial vehicles (UAVs) to enable safe coexistence with manned aircraft in complex environments by adjusting the level of human involvement in threat avoidance based on changing conditions. The method involves a UAV monitoring threats and determining the appropriate level of human supervision required, ranging from full manual control to autonomous flight. Factors like threat distance, communication status, and uncertainty level are used to decide if the UAV can autonomously evade threats or needs human intervention. This adaptive supervision balances UAV autonomy and operator workload to mitigate issues like overloading operators and loss of situational awareness.

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Supervisory control method for obstacle avoidance of unmanned aerial vehicles (UAVs) by manned aircraft that dynamically adjusts the level of human supervision based on environmental conditions. The method involves having the UAV autonomously avoid known obstacles but seeking human guidance for unknown obstacles or when communication is interrupted. The UAV can also request human intervention if it cannot autonomously avoid obstacles. The human can provide updated obstacle information when necessary. This allows balancing UAV autonomy with human oversight for optimal obstacle avoidance while maintaining situational awareness.

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A drone operator status monitoring system that uses multi-sensor fusion to evaluate a drone operator's working status in real time. The system combines data from sensors like depth cameras, facial expression analyzers, eye trackers, heart rate monitors, and body temperature sensors to determine the operator's mood, fatigue, attention, and posture. This data is used to calculate a decision-making level that indicates how well the operator can safely and efficiently control the drone. The system aims to prevent "man-out-of-the-loop" events where the operator loses awareness or focus, by alerting or assisting them when fatigue or distraction is detected.

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