Description:Field of the Invention
The proposed system addresses key challenges in disaster management. Traditional methods often suffer from slow responses and limited access to hazardous areas. The system's use of autonomous drones equipped with sensors like cameras and thermal imaging addresses the problem of timely data collection. Advanced navigation algorithms enable drones to navigate complex environments and overcome obstacles, improving access to disaster-stricken areas. Wireless communication networks between drones and disaster centers solve communication breakdowns, historically hampering coordination. Overall, the system enhances disaster response by providing comprehensive data, enabling informed decisions, efficient resource allocation, and heightened public safety.
Objective of the Invention
The main objective of this invention is to create an autonomous drone fleet specifically designed for disaster response scenarios. The invention aims to achieve autonomous navigation, real-time data collection, and multi-sensor integration to enhance disaster management capabilities. By promptly assessing disaster-stricken areas and relaying vital information, the invention intends to assist rescue teams in making informed decisions and expediting response efforts, thereby minimizing risks and ensuring effective disaster mitigation
Background of the Invention
Traditional disaster response methods often face challenges in accessing remote or dangerous areas quickly. Drones equipped with various sensors, cameras, and communication technologies can be deployed to gather real-time data, assess the situation, and provide crucial insights to emergency responders. This innovation aims to enhance the speed, accuracy, and safety of disaster relief efforts, minimizing human risk and expediting rescue operations.
For instance, US9216745B2 describes collision avoidance for semi-autonomous vehicles using a grid map. A grid map represents an environment divided into a grid of cells, where each cell corresponds to a specific location in space. This map helps identify obstacles and other features in the environment. Sensors like LIDAR, depth cameras, and radar can be used to create the grid map. The vehicles' planner uses this map to generate a path that avoids obstacles. Additionally, the planner considers kinematic data, such as the velocity and position of nearby vehicles, to prevent collisions.
KR101827249B1 introduces a system where drones can be controlled via smartphones through a secure VPN network. Utilizing object recognition technology and wireless communication, the smartphones interact with drones, identifying objects using computer vision and enabling real-time tracking. This innovation has applications in surveillance, missing person searches, and even replacing traditional CCTV systems with smarter drone-based monitoring. The system's versatility and remote tracking capabilities make it a valuable tool for various scenarios, ensuring effective and intelligent object detection and control.
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US10175151B2 describe the environmental monitoring UAV system is to accurately measure and monitor environmental parameters. By using a drone with an air monitoring platform and sensors, air samples can be taken at specific locations when readings from the measurement sensors exceed a certain threshold. This allows for real-time monitoring and decision-making based on the concentration of impurities in the air. The use of reliable wireless protocols ensures low latency for efficient data collection and analysis.
WO201717137393A1 describes a system involving drones equipped with fire sensors to detect and monitor fire conditions in buildings. The system consists of drones equipped with fire sensors. As the drones fly through a building, their fire sensors continuously monitor the temperature levels. If the sensor detects a temperature rise, it triggers an alert. After detecting the fire, the drone sends alert data to the system controller. This data includes information about the location where the fire was detected. By using this data, a map is created that includes information like material flammability and burning rates. Once a fire condition is confirmed, the system controller generates a fire alert. This alert includes the fire's location and its stage.
Summary of the Invention
The "Autonomous Drone Fleet for Disaster Response" invention offers a transformative solution to the limitations of traditional disaster response methods. By deploying an autonomous fleet of drones equipped with advanced sensors, including cameras, thermal detectors, and gas sensors, the invention enables real-time data collection in disaster-stricken areas. The collected data is transmitted for swift analysis, aiding rescue teams in making informed decisions and coordinating effective responses.
The drones' autonomous navigation and collision avoidance capabilities enhance their safety and efficiency in hazardous environments. Through the integration of cutting-edge technologies such as robotics and wireless communication, the invention aims to minimize human risk while maximizing the speed and accuracy of disaster response efforts. Ultimately, this innovation has the potential to revolutionize the field of disaster management by streamlining data collection, analysis, and decision-making, leading to improved outcomes and enhanced public safety.
Brief Description of Drawings
The invention will be described in detail with reference to the exemplary embodiments shown in the figures wherein:
Figure-1: Work flow of the Autonomous Drone
Detailed Description of the Invention
An innovation poised to revolutionize disaster management. This transformative system addresses the limitations of conventional disaster response methods by harnessing the power of autonomous drones equipped with state-of-the-art sensors. These drones, armed with cameras, thermal detectors, and gas sensors, take to the skies to gather real-time data from
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disaster-stricken areas. This invaluable information is rapidly transmitted for analysis, empowering rescue teams to make well-informed decisions and orchestrate effective, coordinated responses.
With autonomous navigation and advanced collision avoidance capabilities, these drones are primed for safe and efficient operation in perilous environments. By fusing cutting-edge technologies like robotics and wireless communication, this invention boldly seeks to mitigate human risks while expediting and refining disaster response endeavors. The impact is profound: data collection, analysis, and decision-making streamlined to an unprecedented degree, leading to elevated outcomes and fortified public safety. The "Autonomous Drone Fleet for Disaster Response" stands as a testament to the potential of innovation in reshaping the landscape of disaster management as we know it.
The workflow is processed as below:
At the start, smart drones with special sensors fly to disaster zones. These drones use cameras, heat detectors, and gas sensors to collect information in real-time. This helps us understand what's happening and respond better to the emergency. Fig(1)
To avoid crashes and fly safely, the drones follow a clever plan. They make a map of the area using special sensors like LIDAR, depth cameras, and radar. This map shows where obstacles are. Then, the drones use this map to pick a path that avoids obstacles, like a video game where you avoid obstacles. They even consider how other nearby vehicles are moving to make sure they don't bump into anything. This helps the drones move around without any accidents.
Imagine using your smartphone to control drones, like playing a game. These drones and your phone talk securely using a special connection, like a secret code for safety. Your phone has a skill called computer vision that helps it understand what drones see. As drones fly, your phone can "see" through them. This smart technology is great for watching, finding people, and spotting things from up high.
Now, think of drones as air detectives. They carry special tools and sensors, like air detectors, to collect air samples. They take samples where sensors detect air might not be good. This helps us quickly decide if the air is safe. It happens in real time, so there's no waiting. The drones use strong wireless connections, gathering info well and fast. This tech helps us know about air quality and make safe choices
Imagine drones as fire protectors flying high, watching over buildings for any signs of fire. These drones have special sensors called ASD (Advanced Smoke Detection) and LHD (Linear Heat Detection). These sensors are like super noses, sniffing for heat or smoke. While flying around buildings, they always check how warm things are. If they notice the temperature going up, like when you're cooking on a stove, they quickly send a message. This message goes to a controller, which is like the boss, getting the news that there might be a fire. Using this information, they make a map that shows where the fire is and how fast it could spread, kind of like a map in a video game. Once they're sure there's a fire, the controller sends a quick message with exactly where it is and how bad it is. It's like the drones and their special tools work together to keep everyone safe from fires.
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all the important stuff that the drones gather, like what they see and sense, is sent right away to a central place called a "hub." This hub is like a big brain where experts study the information. These experts are like detectives, figuring out what's happening. Emergency helpers, like firefighters, get this information. They look at it really closely to understand what's going on and what they should do. They make smart choices based on this fast information to help in emergencies. And these clever drones work together with the experts to help rescue teams. This whole plan uses special tools, like the smartphone control, the sensors, and the smart analysis, to make sure we can deal with disasters as best as possible.
Advantages of the proposed model,
Swift Response and Real-time Data: Autonomous drones can swiftly reach disaster areas, providing real-time data from the ground. This enables quicker decision-making and better understanding of the situation's severity.
Enhanced Safety: Drones' collision avoidance system reduces the risk of accidents, ensuring the safety of both the drones and people in the disaster-stricken area.
Ease of Control: Smartphone control offers user-friendly operation, allowing personnel to direct the drones easily. Object recognition and real-time tracking enhance precision, making the system efficient and accessible.
Immediate Air Quality Assessment: Drones provide real-time air quality data, enabling quick decisions for safeguarding health and safety in disaster environments. Wireless protocols ensure timely and efficient data transmission.
Early Fire Detection: Drones equipped with fire sensors can detect fires early, triggering alerts for rapid response. Mapping material flammability and burning rates helps responders strategize effectively.
Rapid Information Dissemination: Real-time transmission of data to a central analysis hub allows decision-makers to gather insights promptly, facilitating quicker and well-informed responses.
Informed Decision-Making: Access to real-time data empowers emergency responders to make informed decisions based on the most current information available.
Efficient Coordination: Autonomous drones contribute to efficient rescue operations by providing data and situational awareness, optimizing the coordination of response efforts. , Claims:The scope of the invention is defined by the following claims:
Claims:
1. The autonomous disaster response system comprising:
a) A fleet of autonomous drones, each equipped with: a camera for capturing visual data and thermal detector for capturing thermal data; a gas sensor for capturing gas-related data;
b) The wireless communication module facilitating real-time data transmission from the drones and a central analysis unit configured to receive, process, and analyze the real-time data transmitted by the autonomous drones;
c) The decision support system integrated with the central analysis unit, generating informed decisions for orchestrating disaster response actions based on the analyzed data.
2. According to claim 1, wherein each autonomous drone is further equipped with collision avoidance sensors and autonomous navigation capabilities, enabling safe and efficient operation in hazardous environments.
3. According to claim 1, wherein the wireless communication module employs advanced communication protocols for real-time transmission of data from the autonomous drones to the central analysis unit.