A REAL-TIME DISASTER INFORMATION AGGREGATION AND ANALYSIS SYSTEM

Abstract

A real-time disaster information aggregation and analysis system is disclosed. The system comprises N hardware sensor nodes configured to sense a disaster, N vision nodes configured to record and analyze a change in a physical structure of the site, a wireless data sensor configured to transmit data to a gateway using ZigBee, the gateway configured to transmit the data to a cloud server using LoRa, and the cloud server configured to store the data as a dataset using Wi-Fi. The system may further comprise a centralized server for data processing and predicting disaster and/or AI and ML algorithms to provide real-time alerts and notifications.

Specification

Description:FIELD OF THE INVENTION
This invention relates to real-time disaster information aggregation and analysis system.
BACKGROUND OF THE INVENTION
The Real-Time Disaster Aggregation and Analysis System addresses several critical problems that arise during natural and man-made disasters. People in affected areas often lack access to timely and accurate information about the disaster, its progression, and safety instructions. Delays in coordinating rescue operations and sending help to affected areas can cost lives. Poor communication and a lack of a central system to provide situational awareness exacerbate these delays. People in disaster-prone regions may not have access to emergency warnings, particularly in remote areas or during infrastructure failure.
CN103473112A The present invention relates to a real time disaster aggregation and analysis system. The invention provides a disaster backup information system simulation method based on two places and three centers. A simulated disaster backup information system is built according actual needs of a user. Disaster information system drilling processes, caused by a disaster, such as fault injection, fault repair, fault detection, data center switching and back-switching, data storage, and data validity verification are realized. Three signal states, namely a normal state, a fault state and a center replaced state exist in the system. System signals are utilized to realize disaster backup flow control, cost is lowered, work efficiency is increased, disaster backup data and
RESEARCH GAP:
Current system used the drone and repeater technology.
Current system uses the Bluetooth Technology.
Proposed solution: Overall architecture supports ZigBee, LoRa and Wi-Fi communication.
US20150099481A1 A method and system for providing various alert notifications to individuals. More specifically, the embodiments disclosed herein are directed to obtaining an alert notification from an external source and determining a geographic area associated with the alert notification. Once the geographic area has been determined the methods and systems described determine one or more users in the geographic area that meet one or more alert criteria. An alert notification is then generated and is provided to one or more users in geographic areas that meet the one or more alert criteria.
RESEARCH GAP:
Current system used the technology for implemented without LoRa.
Proposed solution:
N number of sensor nodes sense the N number of disaster alerts.
US11334794B2 Artificial-intelligence-based river information system. In an embodiment, a first training dataset is used to train a travel time prediction model to predict a travel time along the waterway for a given trip. In addition, a second training dataset is used to train a river level prediction model to predict a river level along the waterway for a given time. For each of a plurality of trips, a request is received that specifies the trip and a time of the trip, and, in response to the request, the travel time prediction model is used to predict a travel time for the trip.
RESEARCH GAP:
Proposed solution:
N numbers of Coordinator takes the data form wireless data sensor using ZigBee and transmit to gateway using LoRa Network.
Gateway sends the data on the cloud server for storing the dataset using Wi-Fi (Internet).
None of the prior art indicate above either alone or in combination with one another disclose what the present invention has disclosed. This invention relates to real-time disaster information aggregation and analysis system.
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.
A real-time disaster monitoring and analysis system utilizing a combination of vision nodes, sensors, and communication gateways. At the core of the system are Vision Nodes that collect data from various Sensors. Each vision node is equipped with different sensors, such as Geophones and Accelerometers for monitoring ground movements in one node, and Temperature and Air Pressure sensors in another. ZigBee is a low-power wireless protocol that works well for short-range communication between the vision nodes. With the use of a geophone, one may detect seismic activity by converting ground movement into voltage, which can then be recorded and evaluated. Geophones are extensively employed in seismic research, monitoring, and seismic exploration.
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. FRAMEWORK FOR REAL TIME DISASTER AGGREGATION & ANALYSIS SYSTEM
FIGURE 2: WIRELESS SENSOR DEVICE
FIGURE 3: VISION DEVICE (NODE)
FIGURE 4: GATEWAY
FIGURE 5: ALGORITHM OF ALL PROCESS
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.
A real-time disaster monitoring and analysis system utilizing a combination of vision nodes, sensors, and communication gateways. At the core of the system are Vision Nodes that collect data from various Sensors. Each vision node is equipped with different sensors, such as Geophones and Accelerometers for monitoring ground movements in one node, and Temperature and Air Pressure sensors in another. ZigBee is a low-power wireless protocol that works well for short-range communication between the vision nodes. With the use of a geophone, one may detect seismic activity by converting ground movement into voltage, which can then be recorded and evaluated. Geophones are extensively employed in seismic research, monitoring, and seismic exploration.
A gateway that supports both Wi-Fi and LoRa protocols receives the data collected from the sensors via ZigBee. The system can function across large distances, making it perfect for places that are prone to disasters. LoRa is utilized to facilitate long-range communication between the vision nodes and the gateway. Following its arrival at the gateway, the data is subsequently transmitted by Wi-Fi to a cloud server for additional processing, analysis, and archiving. When it comes to gathering information from various devices and offering guidance for making decisions in emergency situations, the cloud server is an essential component.
A Power Supply Unit at the system's base supplies the vision nodes and sensors with the power they require. The charger and DC outlet on this unit guarantee that the system will continue to function even in the event of power outages or changes, which is an essential feature for applications related to catastrophe monitoring. guaranteeing that the system is kept powered even when there is electrical instability, which frequently occurs during natural disasters. In order to adjust to the energy requirements of the different system components, the power supply also offers current modulation. Data collected by the vision nodes is transmitted to a Gateway which functions as the main hub of the system's communication architecture, receives data gathered by the vision nodes. Both WiFi and LoRa (Long Range) technologies are supported by the gateway. Because LoRa can transport data over long distances with low power consumption, it is an essential component of this architecture. Data may be transmitted from the vision nodes, which may be dispersed over broad areas, to the central gateway. For catastrophe monitoring systems, especially those that work with geographically distributed sensor networks, this long-range capacity is crucial. Upon arrival at the gateway, the data is transmitted via Wi-Fi to a Cloud Server, an enhanced bandwidth communication technique appropriate for transmitting substantial datasets or real-time data to distant servers for additional examination. An essential part that gathers the data from all linked devices is the Cloud Server. It gathers data from the many sensors, saves it, processes it, and analyzes it. Disaster management teams can forecast, give warnings, and keep an eye on situations in real time via one unified cloud platform. Through the use of cloud computing, the system can effectively handle big datasets and guarantee that vital data is available from any location, enabling remote monitoring and quicker decision-making in the event of a disaster. An integrated disaster monitoring and response system designed for real-time environmental data collection and transmission. a comprehensive disaster monitoring and response system made to gather and transmit environmental data in real time. This system is perfectly suited to operate in disaster-prone areas, helping to predict and mitigate the effects of natural calamities while ensuring reliable operation during power outages.
It combines low-power, long-range communication technologies with a robust cloud-based analytics platform. In regions where natural disasters like earthquakes, hurricanes, or fires are frequent, the method is extremely helpful. It obtains data from many sensors that detect air pressure, temperature, and ground movement, among other things. During power outages, which are frequent during natural catastrophes, the system is built to continue operating dependably. The power supply device guarantees that the vision nodes and sensors constantly have power because it has a DC outlet and a charger. In order to maintain optimal performance and resilience even during times of electrical instability, it also has current regulation, which adjusts to the differing energy requirements of various components.
Data regarding live emergencies is gathered, analyzed, and disseminated in real time via the Real Time Disaster Aggregation System. These systems are used to supply current information to support relief efforts, risk management, and disaster response. gathers and incorporates data continuously from a variety of sources, including social media, sensor networks, and weather APIs. To guarantee correctness and relevance, it processes and normalizes this data. The system groups related disasters according to location and intensity by using machine learning to categorize different types of disasters. When thresholds are surpassed, alerts are sent to notify authorities and users in a timely manner. Real-time decision-making and prompt response are made possible by the system's dashboard, which shows the most recent statistics and maps. The system's ability to predict disasters is improved by user feedback and ongoing data upgrades.
Wireless Sensor Device: The method for monitoring the environment and detecting disasters is the wireless sensor device (announced in figure 2). Data is collected from numerous sensors that are connected to a computing unit, which is the center of the system. They consist of a thermophone to monitor air conditions, accelerometers to measure motion, and geophones to detect vibrations in the earth. For the purpose of identifying changes in altitude or weather, there is also an Air Pressure/Altitude Sensor (BMP 180) that measures pressure variations.
Data from all sensors is processed by the computing unit and sent wirelessly ZigBee is a low-power communication protocol that is perfect for linking several devices in a network over long distances. It processes data from all sensors and sends it wirelessly. For disaster monitoring in particular geographic locations, the system's ability to track the position of the data being gathered is crucial. In order to provide early warnings and real-time responses to possible natural disasters, this system is made to effectively gather environmental data and transfer it to centralized monitoring centers.
Vision Device/Node: The Vision node (as shown in figure 3), The task of gathering and analyzing visual data, which might offer crucial information in disaster situations like floods or structure collapses, usually falls to a significant component. In catastrophe situations, it functions as a smart sensor node that offers real-time situational information to facilitate prompt decision-making and response. The vision node continuously scans the environment using depth sensors (like LiDAR) and cameras (like RGB, thermal, or infrared). It records pictures, videos, and three-dimensional maps of the affected area.
The vision node can produce 3D maps of the disaster region by integrating camera and LiDAR data. Instead of sending all raw data to a central system, it uses artificial intelligence (AI) to evaluate photos or videos in real-time. As a result, the node can produce alerts fast and with little delay, such as when it detects people who are stuck or dangerous regions. After a disaster, vision nodes can be used to evaluate the stability of infrastructure or structures. The ZigBee module is a crucial part of the system since it enables wireless communication via a low-power network with other sensors or devices. Additionally, the system is linked to a LoRa modem, which facilitates long-range communication and is perfect for transmitting data over vast distances, particularly in regions that are vulnerable to disasters. A camera and a LiDAR sensor are two more peripherals that are essential for gathering spatial and visual data. The LiDAR sensor helps in mapping and monitoring the environment by detecting depth and distance, while the camera records photos or video feeds in real time. The system also includes standard input/output devices, like a display to show processed data or alarms, and a keyboard and mouse for local system interaction. In order to ensure that the system can log data locally even in the event of a disruption in network connectivity, an SD card is connected for data storage. Because a battery or power supply powers the entire system, it can function independently in remote locations or during power outages.
Gateway in a real-time disaster aggregation and analysis system acts as a bridge between the sensor network vision nodes, IoT sensors, etc., and the central cloud server or data aggregation point. The disaster area's gateway gathers data from dispersed devices, processes it locally if necessary, and then transmits it to a centralized system or the cloud for additional analysis and decision-making. To collect data from Vision Node, the gateway microprocessor establishes a connection with the LoRa network. The gateway gathers this data and uses the WIFI network to deliver the data to the cloud for dataset generation and additional analysis. LoRa's extended transmission range makes this possible. LoRa works well for gathering data initially, and WIFI works well for moving that data to cloud databases. A memory device is used to store data for internal storage, and a battery powers the device.
Strong, scalable, and secure infrastructure that can manage massive volumes of data from several sources, analyze data in real-time, and guarantee quick connection with disaster response teams are prerequisites for a cloud server architecture for real-time disaster aggregation and analysis. A cloud server is a virtual machine that utilizes cloud computing infrastructure for operation. Users are able to deploy, maintain, and expand applications without the need for physical hardware because to its availability of scalable and flexible computing resources over the internet. The upkeep, security, and upgrades of cloud servers are handled by cloud service providers like AWS, Google Cloud, and IBM Cloud. To analyze and understand the collected data, derive predictive analytics, and extract useful information, sophisticated algorithms and machine learning models are implemented on the cloud server. These realizations help with resource allocation optimization, potential development predictions, and disaster dynamics understanding. Additionally, the server enables real-time data visualization by providing interactive dashboards and maps that show the disaster's current state as well as its emerging situations. It provides a thorough and cohesive picture of the crisis event by integrating and managing data from several nodes, such as sensors, cameras, and other monitoring equipment.
ADVANTAGES OF THE INVENTION
The system provides emergency services and authorities access to real-time information on disaster events, they can react more swiftly and effectively. By combining information from several sources, it provides a thorough picture of the calamity, enhancing resource management and strategic planning. The system processes data more correctly, decreasing mistakes and boosting the dependability of forecasts and effect evaluations by employing advanced analysis. The system's objective is to minimize damage and loss by proactively managing risks by spotting trends in the data and forecasting probable catastrophic outcomes. The system guarantees more coordinated and successful crisis response activities by promoting efficient communication and coordination amongst multiple stakeholders, including emergency responders, governmental organizations, and the general public. The system not only facilitates emergency operations but also raises public awareness by providing essential information and real-time updates. This helps people and communities make educated decisions about their safety and preparedness. It also facilitates scenario planning and impact analysis, which enables the assessment of response tactics and the development of future disaster management plans.
, Claims:1. A real-time disaster information aggregation and analysis system, comprising:
N hardware sensor nodes configured to sense a disaster;
N vision nodes configured to record and analyze a change in a physical structure of the site;
a wireless data sensor configured to transmit data to a gateway using ZigBee;
the gateway configured to transmit the data to a cloud server using LoRa; and
the cloud server configured to store the data as a dataset using Wi-Fi.
2. The system as claimed in claim 1, wherein the system uses a centralized server for data processing and predicting disasters.
3. The system as claimed in claim 1, wherein the system uses AI and ML algorithms to provide real-time alerts and notifications.
4. The system as claimed in claim 1, wherein the system supports ZigBee, LoRa, and Wi-Fi communication.

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