Drone Compliance Standards

Memory system that allows higher data transfer rate in read operations compared to write operations by using a higher clock frequency for read transfers. In the write operation, the memory controller sends data synchronized with a write clock. In the read operation, the controller sends a read enable signal synchronized with a read clock that is higher frequency than the write clock. The memory chip generates its own read strobe signal based on the read clock and transfers read data synchronized with that. This allows the memory chip to read data faster using the higher read clock without needing the controller to match the write clock frequency.

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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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Detecting and managing conflicts between different vehicles or entities using a partitioned airspace model to enable agnostic monitoring of heterogeneous airspace users. The airspace is divided into non-overlapping partitions. Vehicles provide their operating regions. These are mapped to partitions. Conflicts are detected when vehicles concurrently use the same partition. Notifications are provided.

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A data collection system for unmanned aerial vehicles (UAVs) to improve flight safety and prevent loss of UAVs. The system collects flight data, geographical data, and monitors for failures during UAV operation. It uses neural networks to analyze flight data to detect abnormalities and failures. It also collects geographical data to improve landing point accuracy. If abnormalities are detected or a failure occurs, the system initiates a return sequence. This prevents UAVs from exceeding control distances or crashing due to operator error or malfunctions.

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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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System to enable safe and efficient operation of multiple drones collaboratively in the same area without collisions. The system involves a ground control terminal communicating with the drones using unique identification codes. The drones send real-time flight data including position. The ground control analyzes the positions to identify drones within a safe distance of each other. These are flagged as high-risk and monitored more closely.

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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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A drone monitoring and early warning platform that uses a network of dedicated drones to detect, track, and respond to unauthorized drones near sensitive locations like airports and events. The platform consists of modules for resource management, early warning prompts, processing, visual presentation, data analysis, and dedicated drone management. It aims to improve drone security by providing informatized drone detection, early warning, and countermeasures using a network of dedicated drones.

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Centrally managing the operation of multiple unmanned aircraft of different types to simplify fleet management and enable efficient operation of mixed fleets. The system involves standardizing the format of flight status data transmitted from the unmanned aircraft to a central control device. This allows extracting and processing the necessary information consistently across different aircraft types without needing custom extraction for each format. The standardized flight status data provides a common set of flight parameters like position, speed, altitude, etc. that can be monitored and managed centrally for all aircraft.

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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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An automated system helps unmanned aerial vehicle (UAV) pilots plan and monitor flights to avoid airspace restrictions. The system uses a checklist of flight restriction conditions generated based on a planned flight area and time period. The system also monitors for changes to the restrictions and notifies the pilot before the flight if any restrictions have changed.

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Autonomous swarm control system for unmanned aerial vehicles (UAVs) that allows safe and efficient coordinated flight of multiple UAVs. The system has a ground control station that receives flight commands and generates fleet instructions. Each UAV receives instructions and checks for collisions. If collisions are detected, the UAV modifies the instructions to avoid them. This allows real-time collision avoidance while following commands. The ground control station also monitors UAV availability to ensure they can execute commands. If not, it notifies operators.

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Conflict detection and avoidance decision-making system for large unmanned aerial vehicles (UAVs) operating in congested airspace. The system helps UAV pilots maintain safe distances from other aircraft. It uses onboard sensors to monitor nearby traffic and provides guidance to prevent collisions. The system continuously updates avoidance maneuvers based on changing aircraft positions. It allows UAVs to fly safely in mixed manned-unmanned operations by providing local decision-making and avoiding global coordination requirements.

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Autonomous unmanned aerial vehicle (UAV) flight system that supports UAV operations in controlled airspace. The system receives cleared flight path instructions from air traffic control and determines specific lateral and vertical guidance modes required for the UAV to follow the instructions. The UAV engages these modes, which are independent of each other and follow instrument flight rules. This allows the UAV to fly autonomously in complex airspace by following authorized routes and procedures.

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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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