Drone Compliance Standards

Querying a database of geofences to efficiently enforce rules within them using drones and other devices. The geofences are defined by a plurality of geographic locations associated with unique IP addresses. Drones and devices can request geofence information for a location using the IP addresses. This enables accurate and fast geofence lookup and enforcement by drones without needing GPS or other positioning systems. The geofences can also have rules, licenses, and entitlements associated with them.

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Monitoring drone flights to detect unauthorized flights (aka "black flights") that have not been registered or approved. The monitoring involves comparing the known flight plans of registered drones against real-time drone locations. If a drone is detected flying outside its approved plan, it is flagged as a black flight. The monitoring is performed by supervision base stations that provide slicing services to drones. If a drone is flying black, the base station does not provide slicing to prevent it from using its services. This forces the drone to land or return to a legal flight path.

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Monitoring method for unmanned aerial vehicle (UAV) missions to improve success rate by predicting and mitigating risks during flight. The method involves determining factors and thresholds affecting UAV tasks, like environmental, equipment, and personnel factors. It collects real-time data on these factors during flight and uses prediction models to forecast future values. If forecasts exceed thresholds, it generates early warnings with improvement suggestions. If thresholds are not exceeded, it uses an evaluation algorithm to calculate a monitoring report based on the forecasts, weights, and operator quality. This provides proactive risk assessment and recommendations throughout the mission.

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Automated drone airport system for reliable and safe operation of drones in applications like solar panel inspection, reservoir monitoring, etc. The system includes separate components like a master control server, ground station, network communication, power supply, and battery management. It connects to an external server for task assignment. The server checks environmental suitability before releasing the drone. The ground station controls the drone remotely. The components like hatches, platforms, and positioning devices ensure safe drone entry/exit, landing, and recovery. The system enables automated drone deployment, operation, data transfer, and battery swapping.

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An authorization system for unmanned aerial vehicles (UAVs) that restricts the operation of UAVs and equipment based on the user's license. The system involves an off-board controller that checks the license, determines authorized equipment/software profiles, and selectively transmits that software to the UAV for installation. This prevents unauthorized equipment operation even if assembled on the UAV.

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Manage and restrict drone operations and equipment to prevent unauthorized use and avoid bad actors gaining access to restricted capabilities. It involves an off-board computer that checks user licenses and selectively provides equipment control software to the drone based on the license. If a license authorizes certain equipment, it will transmit the proper software to operate it. This ensures the drone cannot operate unauthorized equipment.

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Safe operation method for unmanned aerial vehicles (UAVs) that enables real-time monitoring and control of UAV flight safety. The method involves calculating flight risk parameters based on factors like UAV performance, environmental complexity, and task difficulty. This allows determining the current flight strategy to mitigate risks. The performance parameters are derived from UAV sensors and historical data. The environmental complexity is calculated using weather, terrain, etc. The task complexity is based on factors like distance, load, and number of flights. By dynamically assessing risk, the UAV can adapt flight plans to account for changing conditions and avoid unsafe situations.

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A system for tracking and analyzing unmanned aerial vehicle (UAV) flights to monitor compliance with regulations and identify illegitimate use. The system collects aircraft and flight data through web crawling and analysis to determine UAV flight purposes. It uses a radio frequency identification (RFID) module to compare flight patterns and classify flights as legitimate or illegitimate. If an unregistered UAV is detected, the system contacts authorities to monitor and track it.

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Risk management system for unmanned aerial vehicle (UAV) inspection operations to improve safety and efficiency. The system has three modules: airspace approval, flight planning, and comprehensive management. The airspace approval module reviews UAV inspection plans to assess risks. Flight planning generates detailed UAV routes based on inspection plans. Comprehensive management monitors real-time UAV flights against planned routes to detect deviations and abnormalities.

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Method, device, and system for supervising unmanned aerial vehicles (UAVs) that allows independent and reliable monitoring without relying on the UAV operator's cloud platform. The method involves obtaining reporting information from UAV operators that includes UAV ID, operator-provided UAV ID, and hardware ID. By cross-referencing the communication ID with the hardware ID provided by the network operator, compliance with regulatory flight requirements can be determined. This allows monitoring platforms to independently verify UAV compliance without relying on operator-reported data.

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Ensuring safe drone flights over public roads and other restricted/sensitive locations by having drones broadcast their flight paths and positions using vehicle-to-everything (V2X) messaging. Nearby vehicles, pedestrians, and other drones can then use this information to warn each other and adjust flight paths to avoid collisions. The drones can also detect proximity to roads based on signals from vehicles, devices, or infrastructure. If they are near roads with people, they can temporarily avoid flying over them.

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Collision avoidance system for multiple drones that alerts operators when drones are in proximity to each other to prevent mid-air collisions. The system has a central collision warning device that receives flight information from each drone's operator. It generates virtual zones around the drones based on their positions. It checks if these zones intersect with each other or with known obstacle zones. If so, it generates an alarm to alert the drone operators of potential collisions. This provides collision avoidance without needing cameras or expensive sensor systems on each drone.

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Monitoring and supervising unmanned aerial vehicles (UAVs) to ensure safe operation. The method involves using the UAV's own communication capabilities to transmit flight data to a central server. This allows real-time monitoring of UAV positions and flight parameters. The server can generate flight restriction instructions and warnings if regulations are violated. UAVs can also obtain local airspace restrictions. Offline UAVs can submit flight plans with parameters for approval.

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A system to identify, monitor, and control unregistered drones that have not gone through a registration process. The system uses communication between the drones and a base station to determine if a drone is registered or not. If unregistered, the base station can alert important facilities, monitor the drone, and prevent accidents. The drones provide real-time flight data like speed and altitude. The registration process involves providing flight details like purpose, equipment, and location to the base station.

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Monitoring method, device and user terminal for supervising and managing unmanned aerial vehicles (UAVs) using blockchain. The method involves receiving job broadcasts from UAVs on the blockchain network, verifying if the flight plans match locally stored ones, and broadcasting adjustment notifications if there are inconsistencies. This allows real-time monitoring and enforcement of UAV flight plans using blockchain as a shared ledger.

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Monitoring system for tracking and analyzing drone flights to identify unregistered drones and determine flight purposes. The system collects aircraft information like manufacturer, performance, and financing through web crawling. It also tracks flight data like location, speed, and altitude. This data is analyzed to classify flight purposes and identify unregistered drones. The system can also communicate with drones to trace them back if lost. By monitoring and classifying drone flights, it can detect unregistered drones and determine purposes for registered ones.

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Automated system for preparing safety cases for drone operations and dynamically generating flight plans to mitigate risks. The system uses data sources like public databases to gather parameters for a proposed drone flight without manual fieldwork. It analyzes the retrieved data to identify hazards and determine risks. A flight plan is then determined based on the risk level. This allows faster, less expensive safety case preparation compared to manual data gathering. The system optimizes the flight plan to minimize risks while meeting user objectives.

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Quantitative risk assessment framework for unmanned aerial vehicles (UAVs) that enables quantification of traditionally entered qualitative data. The framework takes inputs like flight plans, vehicle health, operator experience, etc. and maps them to numerical calculations for ground risk and airborne risk. These calculated scores are then used to reference predetermined categorizations for risk assessment and remediation actions. This provides quantitative, repeatable and predictable risk management for UAVs that addresses limitations of qualitative methods.

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Pilot management terminal and unmanned aircraft monitoring system to ensure safe and legal operation of unmanned aircraft. The system connects unmanned aircraft pilots and their drones using a central flight service platform. The pilot terminal collects pilot data and transmits it to the platform. The platform has an aircraft database, pilot database, and management module. This allows monitoring and management of both pilots and drones through the platform.

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Drone supervision method and system that enables identification and monitoring of drones to ensure safety and compliance. The method involves equipping drones with a unique ID code stored in a data unit. Before flight, the code is scanned to verify the drone's identity and bind it to a user. During flight, the drone transmits flight data while the server monitors compliance based on the bound user. This provides drone supervision from identification to flight status monitoring using a pre-flight unique code scan.

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