AI-DRIVEN DISASTER RESPONSE SYSTEM WITH IOT-ENABLED DRONES USING LORAWAN FOR EMERGENCY SITUATIONS

Abstract

An ai-driven disaster response system with iot-enabled drones using lorawan for emergency situations comprises Environmental Monitoring Unit, which includes an STM32 Board, LoRaWAN Module, GPS Module, Gas Sensor, PMS5003 Air Quality Sensor, DHT11 Sensor, BMP280 Sensor, and Power Supply, allows monitoring of important environmental parameters in real time while sending messages to the central command, improving early detection of hazards and disaster management in a reactive manner the Central Command Unit commands a Jetson Nano Board and a LoRaWan Module, the information sensitive to the environment that is received is processed by artificial intelligence and represented in the form of solutions for the rapid response of relevant organs in emergency cases.

Specification

Description:FIELD OF THE INVENTION
This invention relates to ai-driven disaster response system with iot-enabled drones using lorawan for emergency situations.
BACKGROUND OF THE INVENTION
In this case, there is an automated emergency response system which is fully backed by Artificial Intelligence, makes use of a Swarm of drones and a decentralized off-site environmental core which monitors air quality and gas levels in a configurable manner automatically responding to emergency situations in real time. The system is composed of three units: the Environmental Monitoring Unit which is responsible for gathering key data on air, gas and weather conditions: The Central Command Unit features the processing and evaluation of this data; and last, the Drone Unit which has a location unit further attached to it with thermal imaging capability. Long-range, low-power wireless technology enables inter-unit communications, facilitating deployment of emergency alerts to the Drone Unit so that it is dispatched to the scene of the emergency without delay. In case of Emergency drone unit escorts a tele-operated drone to the relevant site in order to collect situational awareness information and facilitate the use of decision making artificial intelligence for quick disaster response. Their data is retrieved by authorized personnel using secure online dashboards further enhancing decision making speed and minimizing risk whilst attributing protection of life and property.
Recognizing the defenselessness of human and economic lives due lack of effective and timely help in case of disasters, this invention sustains the incapability in its response and does well in actively providing instant Artificial Intelligence (AI) assessments for problem solving. Current disaster management systems have been problematic in a timely resolution. The information gaps, which are often in most disaster management processes orchestrate a problem response chain that is delayed the same system meshes monitoring on a round-the-clock basis, to allow for depowering dispatch. This approach improves situation awareness by providing information in advance to avoid further escalation of the problem. This, allows for assistance to be time-activated. It also ensures, to the extent practicable, the number of people subject to threat is kept low. This approach proactively shifts the effort from reactive to preventative, hence improving disaster response times and capability of agencies/task forces.
US10659144B1: Massively distributed and low-cost Internet of things (IoT) gateways can be controlled by software-defined networking (SDN) protocols transferred via an autonomous mobile device (e.g., fly-by drone). The IoT gateways can comprise sensors that capture information that is transferred to the communication network via the autonomous mobile device. For example, the autonomous mobile device can wake the IoT gateways adaptively and perform data collection and/or configuration tasks. Further, the autonomous mobile device can deliver the collected data to network devices of the communication network and return for the next batch of IoT gateway data collections.
RESEARCH GAP: AI-driven disaster response with IoT-enabled drones and real-time environmental monitoring via LoRaWAN is the uniqueness of this innovation.
US20200364456A1: A drone with vehicular control system/sensors that can share data with other vehicles and that can communicate with the cloud to provide intelligent handling of the irrigation system. The drone can be used to dispense soil additives and to inspect plants/trees on the farm.
RESEARCH GAP: AI-driven disaster response with IoT-enabled drones and real-time environmental monitoring via LoRaWAN is the uniqueness of this innovation.
SUMMARY OF THE INVENTION
This summary is provided to introduce a selection of concepts, in a simplified format, that are further described in the detailed description of the invention.
This summary is neither intended to identify key or essential inventive concepts of the invention and nor is it intended for determining the scope of the invention.
To further clarify advantages and features of the present invention, a more particular description of the invention will be rendered by reference to specific embodiments thereof, which is illustrated in the appended drawings. It is appreciated that these drawings depict only typical embodiments of the invention and are therefore not to be considered limiting of its scope. The invention will be described and explained with additional specificity and detail with the accompanying drawings.
This AI based disaster management system integrates real time environment analysis, drone aircraft and analytical techniques to improve emergency response coordination and services. The system consists of three major components, the Environmental Monitoring Unit, Central Command Unit and the Drone Unit which complement to provide enhanced situational awareness and fast-response capability to a specific area. Wary of the limitations in the automated system, more drones would be dispatched to the distress site as warranted by the prevailing environmental circumstances. The technical concepts of the system revolves around the applications of IoT and communication systems design for the purpose of environmental hazard evaluation system. Upon arrival to the site where the action would take place, the drones transmit the images to the central command and control, processes the images and recommends action to take based on the analysis almost in real time. The role of the Environmental Monitoring Unit is to monitor and track emission changes in environmental parameters, including air quality, gas atmospheric areas and weather conditions. This unit contains different types of sensors which carry on measuring continuously the parameters for presence of fire, gas, air quality etc. The wireless data transfer is achieved by a long-distance low power wireless network that is reliable on data transmission over distances. The data if any is received by the Central Command Unit and using AI based algorithms, the incoming data is assessed and the presence of abnormalities or certain characteristics indicating a potential threat are searched. When a danger is identified, one alert is sounded and all the relevant zones are alerted to automatically instruct the Drone Unit to the relevant area for assessment.
BRIEF DESCRIPTION OF THE DRAWINGS
The illustrated embodiments of the subject matter will be understood by reference to the drawings, wherein like parts are designated by like numerals throughout. The following description is intended only by way of example, and simply illustrates certain selected embodiments of devices, systems, and methods that are consistent with the subject matter as claimed herein, wherein:
FIGURE 1: SYSTEM ARCHITECTURE
The figures depict embodiments of the present subject matter for the purposes of illustration only. A person skilled in the art will easily recognize from the following description that alternative embodiments of the structures and methods illustrated herein may be employed without departing from the principles of the disclosure described herein.
DETAILED DESCRIPTION OF THE INVENTION
The detailed description of various exemplary embodiments of the disclosure is described herein with reference to the accompanying drawings. It should be noted that the embodiments are described herein in such details as to clearly communicate the disclosure. However, the amount of details provided herein is not intended to limit the anticipated variations of embodiments; on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the scope of the present disclosure as defined by the appended claims.
It is also to be understood that various arrangements may be devised that, although not explicitly described or shown herein, embody the principles of the present disclosure. Moreover, all statements herein reciting principles, aspects, and embodiments of the present disclosure, as well as specific examples, are intended to encompass equivalents thereof.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments. As used herein, the singular forms "a"," "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises," "comprising," "includes" and/or "including," when used herein, specify the presence of stated features, integers, steps, operations, elements and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and/or groups thereof.
It should also be noted that in some alternative implementations, the functions/acts noted may occur out of the order noted in the figures. For example, two figures shown in succession may, in fact, be executed concurrently or may sometimes be executed in the reverse order, depending upon the functionality/acts involved.
In addition, the descriptions of "first", "second", "third", and the like in the present invention are used for the purpose of description only, and are not to be construed as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. Thus, features defining "first" and "second" may include at least one of the features, either explicitly or implicitly.
Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which example embodiments belong. It will be further understood that terms, e.g., those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
This AI based disaster management system integrates real time environment analysis, drone aircraft and analytical techniques to improve emergency response coordination and services. The system consists of three major components, the Environmental Monitoring Unit, Central Command Unit and the Drone Unit which complement to provide enhanced situational awareness and fast-response capability to a specific area. Wary of the limitations in the automated system, more drones would be dispatched to the distress site as warranted by the prevailing environmental circumstances. The technical concepts of the system revolves around the applications of IoT and communication systems design for the purpose of environmental hazard evaluation system. Upon arrival to the site where the action would take place, the drones transmit the images to the central command and control, processes the images and recommends action to take based on the analysis almost in real time. The role of the Environmental Monitoring Unit is to monitor and track emission changes in environmental parameters, including air quality, gas atmospheric areas and weather conditions. This unit contains different types of sensors which carry on measuring continuously the parameters for presence of fire, gas, air quality etc. The wireless data transfer is achieved by a long-distance low power wireless network that is reliable on data transmission over distances. The data if any is received by the Central Command Unit and using AI based algorithms, the incoming data is assessed and the presence of abnormalities or certain characteristics indicating a potential threat are searched. When a danger is identified, one alert is sounded and all the relevant zones are alerted to automatically instruct the Drone Unit to the relevant area for assessment.
The Drone Unit delivers valuable leeway in the field during operations. As soon as the alarm is received the drone goes into the defined zone and employs its thermal imaging and GPS knowledge to the area's conditions. The video footage in combination with the thermal datastream provides the responders covering the area with the information about the degree and the range of the threat. This data emerged to Central Command Unit whose situation is interpreted and appropriate information is given forth for the responders. The technology also cuts response times while improving safety for emergency personnel by identifying effective response strategies through AI-based analytics on monitoring and drone data. In the context of EGS functions, the necessity of this system is because of the traditional disaster response mechanisms that require timely response and accurate information. In most situations, the responders are delayed in time because of the lack of situational awareness and would need to move to a place that is insecure with little intelligence which poses a threat to their safety. This device tackles such issues by being able to detect hazards and respond to them before the situation escalates so that human risks and the effectiveness of the response to the emergency situation is greatly enhanced. The protected cloud dashboard enables authorized users to view real-time information collected by the environmental sensors and drones, making it possible for them to make decisions and coordinate activities from a distance. Such versatility ensures that important information is available to many actors in many locations so that response and coordination can be quicker.
BEST METHOD OF WORKING
The Environmental Monitoring Unit, which includes an STM32 Board, LoRaWAN Module, GPS Module, Gas Sensor, PMS5003 Air Quality Sensor, DHT11 Sensor, BMP280 Sensor, and Power Supply, allows monitoring of important environmental parameters in real time while sending messages to the central command, improving early detection of hazards and disaster management in a reactive manner.
The Central Command Unit commands a Jetson Nano Board and a LoRaWan Module, the information sensitive to the environment that is received is processed by artificial intelligence and represented in the form of solutions for the rapid response of relevant organs in emergency cases.
The Drone Unit contains a GPS called Drone, a Thermal Camera, and a LoRaWan Module, it is capable of being accurately placed to hazardous environments in response to alerts sent by the Environmental Monitoring Unit; this will provide current situation and evaluation information about the disaster area to facilitate effective management of the disaster.
The LoRaWAN Module which is integrated in the Environmental Monitoring Unit, Central Command Unit, and the Drone Unit provides reliable long distance wireless data communication that allows collection of data and information in different locations of a large area without interruption of communication for effective monitoring.
The GPS Module is the part of the Environmental Monitoring Unit and is incorporated in the Drone Unit. It helps the members in locating the hazards as well as in the navigation of the drone; this makes it easier for them to target particular response efforts and to improve the overall effectiveness of disaster interventions.
ADVANTAGES OF THE INVENTION
1. A gas sensor, a PMS5003 air quality sensor, a DHT11 sensor, and a BMP280 sensor contained in the Environmental Monitoring Unit are actively engaged in tracking air quality, concentrations of gases, and weather parameters, respectively, in order to avert or reduce consequences associated with potential emergencies due to environmental hazards.
2. Outfitted with a LoRaWAN Module, the units in both the Environmental Monitoring and the Central Command unit can reliably transfer data making it efficient in wide area coverage and disperses, which is crucial in monitoring threats in real time.
3. The on-ground use of a GPS-enabled drone fitted with a thermal capture device provides timely images and awareness in emergencies, allowing emergency responders to survey the environment from a reasonable distance. This way, targeted deployments will aid in responding based on real time intelligence without unnecessary delays.
4. The data acquired through the Central Command Unit's Jetson Nano Board, which receives incoming signals, is evaluated using AI for situational differences, and an appropriate response strategy is constructed, thus enhancing ideal management for emergency situations.
5. The Environmental Monitoring Unit with the GPS module and the Drone Unit with the GSM modem provide secured cloud based dashboards where authorized staff can fanatically view location coordinates and get notifications to maximise operational efficiency and ensure optimal decision making from any site.
, Claims:1. An ai-driven disaster response system with iot-enabled drones using lorawan for emergency situations comprises Environmental Monitoring Unit, which includes an STM32 Board, LoRaWAN Module, GPS Module, Gas Sensor, PMS5003 Air Quality Sensor, DHT11 Sensor, BMP280 Sensor, and Power Supply, allows monitoring of important environmental parameters in real time while sending messages to the central command, improving early detection of hazards and disaster management in a reactive manner.
2. The system as claimed in claim 1, wherein the Central Command Unit commands a Jetson Nano Board and a LoRaWan Module, the information sensitive to the environment that is received is processed by artificial intelligence and represented in the form of solutions for the rapid response of relevant organs in emergency cases.
3. The system as claimed in claim 1, wherein the Drone Unit contains a GPS called Drone, a Thermal Camera, and a LoRaWan Module, it is capable of being accurately placed to hazardous environments in response to alerts sent by the Environmental Monitoring Unit; this will provide current situation and evaluation information about the disaster area to facilitate effective management of the disaster.
4. The system as claimed in claim 1, wherein the LoRaWAN Module which is integrated in the Environmental Monitoring Unit, Central Command Unit, and the Drone Unit provides reliable long distance wireless data communication that allows collection of data and information in different locations of a large area without interruption of communication for effective monitoring.
5. The system as claimed in claim 1, wherein the GPS Module is the part of the Environmental Monitoring Unit and is incorporated in the Drone Unit, it helps the members in locating the hazards as well as in the navigation of the drone; this makes it easier for them to target particular response efforts and to improve the overall effectiveness of disaster interventions.

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