Emergency Response Control for Drones

A near-field sensing information transmission and pairing system for air-land unmanned vehicles to increase the emergency response capability of ground vehicles in autonomous driving scenarios. It works by having an aerial vehicle fly ahead of a ground vehicle and sense obstacles or traffic features on the road. If any are detected, it calculates and transmits an alternative route to avoid them. The ground vehicle receives the route change request and switches to the alternative route provided by the aerial vehicle. By having the aerial vehicle scout the road ahead, obstacles can be detected and avoided in real-time, compared to a ground-only vehicle reacting when it reaches the obstacle.

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Using moth antennae to equip a palm-sized autonomous drone with the ability to detect and track airborne chemical plumes. The drone uses a specialized antenna sensor from a moth to detect odors. It then autonomously navigates towards the odor source using a wind-oriented search pattern. The robotic insect can locate and map odors in confined spaces without GPS.

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A system for using drones to allow a person in distress to be rescued without requiring a helicopter to get close to buildings or cliffs. A drone is launched from a helicopter with a rope attached. The drone flies to the person and enables them to grab the rope. Once secured, the drone detaches from the rope and returns to the helicopter.

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A distributed network of unmanned aerial vehicles (UAVs) and ground stations that can rapidly deploy drones for public safety and incident response. The network consists of unmanned drone hangars on light poles connected to a central command center. The hangars house drones that can be dispatched on-demand. When a call for a drone comes in, the closest one is launched while others move closer to the incident area for faster response times. This allows a municipality to have full coverage from strategically located drone hangars without needing to deploy drones from a central location.

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Integrating drones with offroad vehicles to provide emergency assistance and secure guidance for vehicle occupants or other persons in the vicinity of the drone and/or vehicle. The drone scouts ahead of the vehicle to identify potential hazards or stranded persons. It relays data back to the vehicle to help the driver avoid dangers or locate missing people. The drone can also guide stranded persons back to the vehicle or call for emergency services. The drone communicates with the vehicle using sensors, cameras, and networks.

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A method and system for using drone swarms to quickly adapt to complex and changing disaster environments for emergency rescue. The method involves a central drone scanning to determine the target area needing rescue, then other drones in that area establish dynamic communications links to share perception and computation resources. This allows rapid, distributed perception and processing in dynamic environments where fixed infrastructure is limited or blocked.

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Optimizing deployment of emergency communication resources like vehicles and drones after a disaster to cover areas with limited network coverage. It involves determining the initial position of the emergency vehicle based on lost device locations and importance, then if some devices are still outside range, finding optimal drone deployment positions to cover them. This allows comprehensive coverage using fewer resources than just the vehicle.

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Non-contact injury assessment system for remote evaluation of casualties using drones and AI to analyze vital signs, wounds, and facial expressions to quickly and accurately assess injuries. The system involves a drone with cameras, sensors, and AI modules. The drone locates and assesses injuries by acquiring images and vital signs from the scene. It uses computer vision to identify wounds, deep learning to extract features, and LSTM to monitor vital signs. The drone transmits the assessment back to responders for triage and treatment guidance.

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Using drones to provide emergency assistance and search for people in tidal flats and valleys. The system involves a drone monitoring system that tracks drone locations, stations, sensors, and flight schedules. If a user gets into distress or goes missing in a tidal flat, the system uses the user's last known location to deploy a drone to search for them. It can also notify the user via their device if they enter dangerous areas. The drone monitoring system provides tidal flat maps with safety information like tide times and dangerous areas.

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Using drones to quickly respond to traffic accidents and handle them more efficiently than traditional methods. The system involves dispatching drones with specialized modules to accidents based on their type. For example, a drone with a crane module might be sent to clear obstructions after a collision, while a drone with a firefighting module would be dispatched to put out a vehicle fire. The drones have sensors, cameras, and communication to coordinate with a central server. This allows multi-drone teams to support each other in handling complex accidents. The drones can also investigate accidents and transmit images back to the server. The system aims to provide faster, more effective, and safer accident response compared to relying on ground vehicles.

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Drones equipped with specialized sensors for rapid and accurate detection of hazardous materials in emergency scenarios. The drones can quickly identify chemicals, radioactive materials, etc. using sensors like mass spectrometers, X-ray fluorescence scanners, etc. This allows immediate assessment of hazardous materials in emergencies, providing real-time data to responders for effective decision-making and response planning. The drones also have navigation systems, communication modules, and machine learning algorithms to enable autonomous flight and data transmission.

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Integrated multi-drone rescue system for urban fires that uses prediction of fire spread to guide the drones for efficient and safe search and rescue. The system has a central drone that analyzes initial fire and victim data, and sends an environment model to distributed drones. The distributed drones use their own sensors to update the model as they search. The central drone re-predicts fire spread based on feedback. This iterative prediction and communication allows the drones to adaptively plan paths that balance safety, distance, and collision avoidance.

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Disaster coordinated rescue system using drones to guide people during emergencies in complex environments. The system involves a processing unit that plans optimal guidance paths for drones based on disaster locations and exit points in a virtual 3D model. Drones then go to road nodes along the paths and display guidance signs. This allows accurate, real-time guidance for people in unfamiliar areas like buildings or forests during disasters. The system also dynamically adjusts paths as disasters evolve.

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Multi-UAV search and rescue communication method and system using intelligent clusters to improve collaboration between multiple UAVs and rescue efficiency. The method involves deploying UAVs in overlapping and non-blind areas to fully cover the search area. UAVs share information through protocols, exchange location data, and collaborate using algorithms to determine optimal paths and actions. The system has a base station, relay UAVs, client UAVs, and a processor running the method. It uses protocols, collaborative algorithms, and real-time adjustment to enhance UAV task coordination and coverage.

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Using traffic control drones for faster and more efficient accident response on highways. The system involves dispatching a traffic control drone equipped with cameras, sensors, and communication devices to an accident site when notified by a dispatch center. The drone autonomously navigates to the scene using SLAM mapping and onboard systems. It then provides visualization, warnings, and instructions using megaphones, strobes, and cameras to help rescue and cleanup efforts. The drone also collects evidence and sends data back to the dispatch center. A relay base station with power and communication links extends the drone's range. The system aims to speed up accident response compared to traditional methods by using drones for rapid, autonomous, and connected response.

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Collaborative search and rescue system for aircraft and boats using resource pre-allocation to improve response times and accuracy. The system involves coordinated search and rescue by unmanned aerial vehicles (UAVs) and unmanned boats. It leverages resource pre-allocation strategies and UAV cluster collaboration technology to rapidly allocate resources and rapidly identify and search for people who have fallen into the water. This improves efficiency compared to traditional methods. The system uses techniques like single target tracking and multi-target tracking with UAV clustering.

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Using unmanned aerial vehicles (UAVs) to improve rescue efficiency in natural disasters by providing real-time environmental information, locating survivors, and guiding rescuers. The UAVs can operate individually or in clusters. In single rescue mode, UAVs use cameras to photograph and mark survivor locations. In cluster mode, a lead UAV collects info and sends multi-modal data to divide the area into sub-regions. UAVs deploy to those sub-regions for targeted rescue. The UAVs can also carry supplies, communicate with survivors, and use submersibles for water rescues.

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Distributed UAV disaster area search and patrol method that enables efficient and reliable dynamic search and perception in UAV-assisted rescue, allowing real-time monitoring of dynamically changing disaster area conditions. The method uses a partition full coverage algorithm to allocate tasks and avoid backtracking during search, and consensus PBFT to achieve real-time updates and consistency among drones during patrol. This allows accurate tracking of searched targets and updating of probability maps for disaster distribution prediction to better serve rescue operations in dynamic disaster areas.

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UAV-assisted emergency communication system for collecting critical disaster data using drones to efficiently retrieve and transmit critical information from disaster sites where traditional communication infrastructure is damaged. The system involves using UAVs to relay and forward important sensor data from the disaster area to a base station drone. The UAVs deploy adaptively based on demand scenarios. They classify relay needs and optimize deployment to match. The UAVs also use environment sensing data to route messages through safe paths. This allows efficient and adaptive recovery of critical disaster data using drones.

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Assisting emergency vehicles in crossing intersections using drones for infrastructure-supported autonomous navigation. The method involves deploying drones with sensors at intersections to monitor traffic. When an emergency vehicle needs to cross, the drone data is analyzed to generate infrastructure-assisted autonomous driving commands for the vehicle. This provides real-time assistance for the emergency vehicle to navigate the intersection safely without the driver having to manually navigate. The drone monitors the intersection and sends data to the emergency vehicle for automated crossing guidance.

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