An integrated system for dam failure detection, early warning and evacuation support

Abstract

An integrated system for detecting dam breaches, as an early warning system and for evacuation assistance, consisting of: A geoinformatics analysis module comprising a modeling processor with a graphics processing unit, configured to: analyze spatial, hydrological, and topographic data of a dam and its downstream area; generate hydrological models using probable maximum rainfall (PMP) data to determine probable maximum flood discharge (PMF); generate hydraulic models to simulate flood propagation and determine flood depth, flood extent, flow velocity, and flood arrival time; create flood vulnerability models, vulnerability models, and flood hotspot models using a multi-criteria decision-making (MCDM) framework; and generate evacuation plans for high-risk zones based on the models. A sensor monitoring subsystem includes: a distributed fiber optic sensor (DFOS) configured to monitor the structural load and deformation of a dam, and a radar level gauge configured to measure the water level in the reservoir; a microcontroller unit configured to receive and process sensor data from the sensor monitoring subsystem, to detect dam breaches based on abnormal structural movements detected by the DFOS or sudden drops in water level below predefined thresholds detected by the radar level gauge; a communication module configured to transmit warning messages when dam breaches are detected; a warning system configured to: send SMS notifications to residents in downstream high-risk zones via a GSM communication module, generate real-time alerts via an IoT platform on user devices, and activate siren systems in villages to issue loud alarms and voice announcements; and an evacuation assistance platform configured to provide real-time evacuation assistance in emergencies due to dam breaks, displaying site maps with nearby emergency shelters, evacuation routes, hospitals, government buildings and aid centers, showing hydrological layers including flood extent, water depth, flow velocity and arrival time of the water, and enabling real-time location tracking in relation to safety zones and flood-prone areas.

Description

AREA OF INVENTION

[0001] The present disclosure relates to an integrated framework for dam failure detection, an early warning system, and an evacuation aid based on mobile applications. In particular, the present invention relates to an intelligent system for performing integrated dam failure analyses, real-time evacuations, and IoT-based early warning systems, wherein the system also includes a user interface. BACKGROUND OF THE INVENTION

[0002] Dam failures pose a significant risk to downstream communities. Worldwide, over 50 dam failures occur annually, causing economic losses of approximately one billion US dollars and an average of 100 fatalities per failure. These dam failures are caused by natural factors such as earthquakes, landslides, and extreme rainfall, as well as by anthropogenic factors such as structural defects, lack of maintenance, and operational errors. While dam failure disasters cannot be completely prevented, their impact can be significantly mitigated through real-time monitoring systems, early warning mechanisms, and structured evacuation plans. However, dedicated early warning systems and real-time evacuation assistance for dam failures are lacking or underdeveloped globally, leaving downstream populations severely vulnerable to sudden dam failures.

[0003] Existing dam monitoring systems lack the necessary integration between dam breach detection, real-time alarms, and evacuation guidelines. This leads to delayed response times and inadequate emergency preparedness. Current systems typically operate in isolation, without comprehensive spatial analysis, automatic sensor-based detection, or mobile evacuation assistance. This results in critical gaps in disaster relief.

[0004] There is a need for an integrated system that combines geoinformatics analytics, IoT-based real-time monitoring, automated early warning systems, and mobile, application-based evacuation assistance to provide comprehensive dam break detection and emergency response capabilities. Such a system would enable the timely detection of dam break events, automated alerting of at-risk populations, and real-time evacuation instructions to minimize human lives and economic losses during dam break emergencies. Summary of the invention

[0005] The present disclosure relates to a dam breach detection and early warning system. The present invention provides an integrated framework for dam breach detection, an early warning system, and application-based evacuation assistance, combining geoinformatics analysis, IoT-based sensor monitoring, automated alerts, and application-based evacuation assistance. The system utilizes distributed fiber optic sensors (DFOS) and radar level gauges to monitor the structural integrity and water level of the dam, processes sensor data via microcontrollers, and automatically triggers multi-channel warning systems upon breach detection, including SMS notifications, IoT platform alerts, and village siren systems. A mobile application platform provides real-time evacuation guidance with shelter maps, evacuation routes, and visualization of hydrological data to facilitate emergency response and minimize casualties in the event of dam breaches.

[0006] To provide a system for dam breach detection and early warning. The system includes a geoinformatics analysis module with a modeling processor and a graphics processing unit, enabling the following: analysis of spatial, hydrological, and topographic data of a dam and its downstream area; creation of hydrological models based on probable maximum rainfall (PMP) data to determine the probable maximum flood discharge (PMF); creation of hydraulic models to simulate flood propagation and determine flood depth, flood extent, flow velocity, and flood onset time; creation of flood vulnerability models, susceptibility models, and flood hotspot models using a multi-criteria decision-making (MCDM) system; and creation of evacuation plans for high-risk areas based on these models.The system also includes a sensor monitoring subsystem with a distributed fiber optic sensor (DFOS) for monitoring the structural stress and deformation of a dam wall and a radar level gauge for measuring the reservoir water level. The system further includes a microcontroller unit for receiving and processing sensor data from the sensor monitoring subsystem; it detects dam breaches based on abnormal structural movements detected by the DFOS or sudden drops in the water level below predefined thresholds detected by the radar level gauge. The system includes a communication module configured to send alerts when dam breaches are detected.The system also includes an alert dissemination system configured to: send SMS notifications to residents in downstream high-risk zones via a GSM communication module; generate real-time alerts on user devices via an IoT platform; and activate siren systems in villages to issue loud alarms and voice announcements. The system also includes an evacuation assistance platform configured to provide real-time evacuation assistance in the event of dam breaches, displaying maps showing the locations of emergency shelters, evacuation routes, hospitals, government buildings, and nearby aid centers; displaying hydrological levels including flood extent, water depth, flow velocity, and water arrival time; and enabling real-time location tracking of safe zones and flood-prone areas.

[0007] One objective of the present disclosure is to provide a system for the detection and early warning of dam breaks.

[0008] Another objective of the present disclosure is to provide an integrated real-time detection system for dam breaks, combining multiple sensor technologies with automated data processing and alarm generation functions to enable rapid identification and response to dam break events.

[0009] Another objective of this disclosure is the development of a comprehensive early warning and evacuation assistance system that automatically disseminates warnings via multiple communication channels and provides real-time guidance to the population downstream in the event of a dam breach.

[0010] Another objective of this disclosure is to create a geoinformatics-based framework for flood risk assessment that generates detailed hydraulic and hydrological models, vulnerability assessments and evacuation plans specifically for dam failure scenarios.

[0011] Another objective of this disclosure is to create a mobile application platform that serves as a digital evacuation assistant, providing real-time location tracking, information on emergency shelters, and visualization of hydrological data to improve situational awareness and coordination of emergency response.

[0012] To further clarify the advantages and features of the present disclosure, the invention is explained in more detail with reference to specific embodiments illustrated in the accompanying drawing. This drawing merely shows typical embodiments of the invention and is therefore not to be regarded as limiting its scope. The invention is described and explained in more detail with reference to the accompanying drawing. BRIEF DESCRIPTION OF THE FIGURE

[0013] These and other features, aspects, and advantages of the present disclosure will be better understood if the following detailed description is read with reference to the accompanying drawing, in which the same symbols consistently represent the same parts. The following applies: Fig. Figure 1 shows a block diagram of an integrated system for detecting dam breaks, an early warning system and an evacuation aid according to an embodiment of the present disclosure.

[0014] Experts will also recognize that the elements in the drawing are shown for the sake of simplicity and are not necessarily to scale. For example, the flowcharts illustrate the process by highlighting the main steps to enhance understanding of the aspects of this disclosure. Furthermore, with regard to the construction of the device, one or more components of the device may be represented in the drawing by conventional symbols. The drawing may show only the specific details relevant to understanding the embodiments of this disclosure, so as not to clutter the drawing with details that are readily apparent to those skilled in the art from the present description. DETAILED DESCRIPTION:

[0015] To facilitate understanding of the inventive principles, reference will now be made to the embodiment illustrated in the drawing, and this will be described in detail. However, this does not limit the scope of the invention. Changes and further modifications to the illustrated system, as well as further applications of the inventive principles, are possible, as would normally occur to a person skilled in the art in this field.

[0016] It is clear to the person skilled in the art that the preceding general description and the following detailed description are exemplary and explanatory of the invention and are not intended to limit it.

[0017] References in this specification to “an aspect”, “another aspect”, or similar expressions mean that a particular feature, structure, or property described in connection with the embodiment is included in at least one embodiment of the present disclosure. Therefore, occurrences of the expressions “in one embodiment”, “in another embodiment”, and similar expressions in this specification may all refer to the same embodiment, but need not.

[0018] The terms "includes," "comprehensive," or other variations thereof are intended to cover non-exclusive inclusion, so that a process or method that includes a list of steps may contain not only those steps but also further steps that are not expressly listed or inherent in that process or method. Likewise, the statement "includes... a" for one or more devices, subsystems, elements, structures, or components does not, without further qualification, exclude the existence of other devices, subsystems, elements, structures, components, or additional devices, subsystems, elements, structures, or components.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as understood by a person skilled in the art in the field of the invention. The systems, methods, and examples provided herein serve only for illustration and are not to be understood as limiting.

[0020] Embodiments of the present disclosure are described in detail below with reference to the attached drawing.

[0021] The functional units described in this specification are referred to as devices. A device may be implemented in programmable hardware such as processors, digital signal processors, central processing units, field-programmable gate arrays, programmable array logic systems, programmable logic devices, cloud processing systems, or the like. Devices may also be implemented in software for execution by various processor types. An identified device may contain executable code and consist, for example, of one or more physical or logical blocks of computer instructions, which may be organized, for example, as an object, procedure, function, or other construct.However, the executable file of an identified device does not need to be physically stored in the same location, but can consist of different commands stored in different locations which, logically linked together, form the device and fulfill its purpose.

[0022] The executable code of a device or module can consist of one or more instructions and may even be distributed across multiple code segments, different applications, and multiple storage devices. Similarly, operational data within the device can be identified and represented, and organized in any form and data structure. This operational data can be captured as a single data record or distributed across different locations, including various storage devices, and may exist, at least partially, as electronic signals within a system or network.

[0023] References in this description to “a selected embodiment”, “an embodiment”, or “an embodiment” mean that a particular feature, structure, or property described in connection with the embodiment is included in at least one embodiment of the disclosed subject matter. Therefore, the expressions “a selected embodiment”, “in an embodiment”, or “in an embodiment” appearing at different points in this description do not necessarily refer to the same embodiment.

[0024] Furthermore, the described features, structures, or properties can be combined in any way in one or more embodiments. The following description contains numerous specific details to enable a comprehensive understanding of the embodiments of the disclosed subject matter. However, those skilled in the art will recognize that the disclosed subject matter can also be implemented without these specific details or with other methods, components, materials, etc. In other cases, known structures, materials, or processes are not presented or described in detail so as not to obscure aspects of the disclosed subject matter.

[0025] According to the exemplary embodiments, the disclosed computer programs or modules can be executed in a variety of ways, for example, as an application in the memory of a device or as a hosted application running on a server and communicating with the device application or browser via various standard protocols such as TCP / IP, HTTP, XML, SOAP, REST, JSON, and other suitable protocols. The disclosed computer programs can be written in exemplary programming languages ​​that are executed from the device's memory or from a hosted server, such as BASIC, COBOL, C, C++, Java, Pascal, or scripting languages ​​such as JavaScript, Python, Ruby, PHP, Perl, or other suitable programming languages.

[0026] Some of the disclosed embodiments involve or otherwise involve data transmission over a network, for example, the transmission of various inputs or files over the network. The network may include, for example, the Internet, wide area networks (WANs), local area networks (LANs), analog or digital wired and wireless telephone networks (e.g., PSTN, Integrated Services Digital Network (ISDN), mobile networks, and Digital Subscriber Line (xDSL)), radio, television, cable, satellite, and / or other transmission or tunneling mechanisms for data transmission. The network may comprise multiple networks or subnetworks, each containing, for example, a wired or wireless data path. The network may include a circuit-switched voice network, a packet-switched data network, or another network for transmitting electronic communications.For example, the network can include networks based on the Internet Protocol (IP) or the Asynchronous Transmission Mode (ATM) and supporting voice communication via VoIP, Voice over ATM, or other comparable protocols. In one implementation, the network includes a cellular network configured for exchanging text or SMS messages.

[0027] Examples of networks include a Personal Area Network (PAN), a Storage Area Network (SAN), a Home Area Network (HAN), a Campus Area Network (CAN), a Local Area Network (LAN), a Wide Area Network (WAN), a Metropolitan Area Network (MAN), a Virtual Private Network (VPN), an Enterprise Private Network (EPN), the Internet, a Global Area Network (GAN), etc.

[0028] Fig. Figure 1 shows a block diagram of an integrated system (100) for dam breach detection, as an early warning system and for evacuation assistance according to an embodiment of the present disclosure.

[0029] Referring to Fig.1. The system (100) comprises: a geoinformatics analysis module (102) which includes a modeling processor with a graphics processing unit and is configured to: analyze spatial, hydrological, and topographic data of a dam and its downstream area; create hydrological models based on probable maximum rainfall (PMP) data to determine probable maximum flood discharge (PMF); create hydraulic models to simulate flood propagation and determine flood depth, flood extent, flow velocity, and flood arrival time; create flood vulnerability models, susceptibility models, and flood hotspot models based on a multi-criteria decision-making (MCDM) framework; and create evacuation plans for high-risk zones based on the models.The system (100) further comprises a sensor monitoring subsystem (104) which includes: a distributed fiber optic sensor (DFOS) (104a) configured to monitor the structural stress and deformation of a dam wall; and a radar level gauge (104b) configured to measure the reservoir water level. The system (100) also includes a microcontroller unit (106) configured to receive and process sensor data from the sensor monitoring subsystem (104); to detect dam breaches based on abnormal structural movements detected by the DFOS (104a) or on sudden drops in water level below predefined thresholds detected by the radar level gauge (104b). The system also includes a communication module (108) configured to send alerts when dam breaches are detected.The system also includes an alert dissemination system (110) configured to send SMS notifications to residents in downstream high-risk zones via a GSM communications module (112); to generate real-time alerts on user devices via an IoT platform; and to activate siren systems in villages to sound loud alarms and voice announcements. The system (100) also includes an evacuation assistance platform (114) configured to provide real-time evacuation assistance in the event of dam breaches; to display site maps showing emergency shelters, evacuation routes, nearby hospitals, government buildings, and aid centers; to present hydrological layers, including the extent of the flood, water depth, flow velocity, and arrival time of the water; and to provide real-time location tracking of safe zones and flood-prone areas.

[0030] In one embodiment, the geoinformatics analysis module (102) is also configured to: integrate remote sensing datasets including satellite imagery, precipitation data and digital elevation model (DEM) using Geographic Information System (GIS) tools; derive more than 15 topographic and hydrological indices to support the multi-criteria decision-making framework; and integrate geodatasets including road networks and building footprints to assess infrastructure vulnerability.

[0031] In one embodiment, the microcontroller unit (106) comprises: a NodeMCU (ESP8266) microcontroller (106a) configured to process and transmit sensor data; Z44 MOSFETs (106b) configured to perform switching operations; and optocouplers (106c) configured to provide electrical signal isolation.

[0032] In one embodiment, the IoT platform includes Ubidot's IoT platform, which is configured to enable the generation of real-time alerts on user devices.

[0033] In one embodiment, the DFOS (104a) is installed along the dam and is configured to: continuously monitor the structural load and deformation, detect abnormal movements or deviations from expected values, and interpret detected anomalies as possible signs of structural instability or the onset of a fracture.

[0034] In one embodiment, the radar level sensor (104b) is configured to measure the water level in the reservoir with high precision, detect sudden and unexpected drops in water level, and generate breakthrough indicators when the water level falls below predefined thresholds.

[0035] In one embodiment, the evacuation assistance platform (114) is configured as follows: a user-friendly interface with interactive tabs; a communication module with notification alarms, a chat interface and a help tab for emergency assistance requests; a real-time location tracker that allows users to monitor their position relative to safe zones and flood-prone areas; and a dynamic guidance function that provides evacuation assistance in real time.

[0036] In one embodiment, the alarm dissemination system (110) also comprises: the GSM communication module (112) configured to automatically send SMS notifications to residents in downstream high-risk areas upon detection of a violation; and siren systems installed in villages configured to be automatically triggered and to emit loud alarms and voice announcements instructing evacuation.

[0037] In one embodiment, the system (100) is configured to automatically activate an early warning protocol upon detection of dam breaches, provide comprehensive mapping of flood risk based on the integration of the flood vulnerability model, the susceptibility model and the flood hotspot model, and facilitate disaster risk mitigation through coordinated sensor monitoring, automatic alerting and real-time evacuation assistance.

[0038] The present invention relates to an integrated system for analyzing dam breaches and supporting IoT-based real-time evacuations. The system comprises an early warning component and a mobile application platform with a user interface. The system detects dam breaches and provides evacuation instructions and early warnings in real time. The integration of IoT technologies enhances the system's ability to support timely decision-making, improve public preparedness, and reduce the potential impact of devastating dam breaches.

[0039] In one embodiment, the system includes a geoinformatics analysis module that performs GIS-based hydrological and hydraulic analyses for dam breach scenarios. This module develops hydraulic models to simulate flood behavior following a dam breach and thus identify potentially vulnerable areas. The system calculates various topographic indices to analyze surface properties relevant to flood propagation. Because floods caused by dam breaches occur rapidly and dynamically with minimal response times, knowledge of the potential extent of flooding is a crucial function of the system. To support this, the geoinformatics analysis module uses GIS technologies to create predictive models for assessing flood vulnerability. Remote sensing datasets serve as important inputs for these GIS processes.The system runs both hydrological and hydraulic models to support the development of flood forecasting capabilities. A flood vulnerability model is created to identify areas that could be flooded by a dam breach, while a flood resilience model is built to assess the resilience of affected communities. Additionally, historical data is collected and analyzed to determine flood hotspots in downstream regions. With regard to evacuation planning, the system is also configured to use GIS analysis to identify the safest locations, including emergency shelters, evacuation points, and relief depots. It provides crucial support in determining the safest and most efficient evacuation routes for vulnerable populations.The geoinformatics analysis module supports real-time disaster relief with its routing functions by enabling the identification of safe routes.

[0040] In one implementation, the system includes a mobile application platform called SachiKavach, designed for evacuation support and early warning dissemination. This platform consists of two components: a mobile end-user application developed with Flutter, and a web-based administration area built with the MERN stack, which includes MongoDB, Express.js, React, and Node.js. Firebase acts as the central backend and real-time data interface, managing data storage, user authentication, and communication between the mobile and web interfaces. The mobile end-user application integrates the Esri API to display geospatial map layers. The platform's primary function is to provide users with access to map-based information and the ability to directly request assistance from government agencies.The web-based administration area allows authorized personnel to manage user accounts, monitor incoming help requests with geolocation data, and communicate with users in real time.

[0041] In another embodiment, the system features an integrated sensor monitoring system for dam breach detection. This system utilizes a combination of technologies, including a radar level sensor and distributed fiber optic sensors (DFOS) for continuous monitoring. The DFOS detects structural stresses along the dam, while the radar level sensor monitors changes in the reservoir water level. The system also incorporates IoT modules and microcontroller platforms, including the NodeMCU (ESP8266), which processes sensor data and enables communication. Real-time alerts and visualization are provided via the Ubidots IoT platform. Audible sirens provide physical alerting to surrounding communities. Additionally, Z44 MOSFETs are integrated for switching operations, and optocouplers ensure electrical signal isolation between components.Together, these electronic components enable precise detection of security breaches and allow for timely early warnings.

[0042] In one embodiment, the system includes a geoinformatics analysis module that constitutes the fundamental phase of dam breach prediction and planning. This module is configured to perform spatial, hydrological, and topographic analyses of the dam and its downstream areas. The analysis includes field-based investigations, such as dam site surveys, flood line delineation, flood hotspot identification, and historical flood area analysis. As part of the modeling workflow, historical meteorological data are statistically evaluated to estimate the probable maximum precipitation (PMP), which represents the highest potential rainfall for the area.Using this PMP data, a hydrological model is created to simulate rain-runoff processes and calculate the probable maximum flood (PMF), which indicates the maximum expected discharge from the dam outlet. The hydrological modeling is performed using HEC-HMS software. Subsequently, a hydraulic model is developed using HEC-RAS software to simulate flood propagation scenarios. The results of this hydraulic model include spatial layers representing flood depth, flood extent, flow velocity, and flood onset time. These results support the identification of vulnerable villages and infrastructure downstream. To enhance the modeling capabilities, the geoinformatics analysis module integrates remote sensing datasets such as satellite imagery, precipitation data, and digital elevation models (DEMs) using GIS tools.Over 15 topographic and hydrological indices are derived to support a multi-criteria decision-making (MCDM) framework for identifying safe locations. Additional geospatial datasets, including road networks and building footprints, are incorporated to assess infrastructure vulnerability. Based on these integrated analyses, the module develops several geospatial models, including a flood vulnerability model, a susceptibility model, and a flood hotspot model. The resulting models are combined to create a comprehensive flood risk map, which serves as the basis for developing targeted evacuation plans for high-risk areas.

[0043] In another embodiment, the system includes an electronic detection and early warning system that plays a crucial role in monitoring the dam's condition and alerting at-risk communities. This subsystem integrates multiple sensors and hardware components for real-time data acquisition and automatic alerting. The monitoring system comprises two main sensors. The first is a distributed fiber optic sensor (DFOS) installed along the dam wall that continuously monitors structural stress and deformation. Abnormal movements or deviations from standard values ​​are interpreted as potential indicators of structural instability or an impending failure. The second sensor is a radar level gauge that measures the reservoir's water level with high accuracy. Any sudden or unexpected drop in the water level below predefined thresholds is considered a possible sign of a dam breach.Upon detecting such anomalies, the system automatically initiates its early warning protocol. The GSM communication module sends SMS alerts to residents in high-risk downstream areas. Simultaneously, real-time notifications are generated via the Ubidots platform, an IoT platform, and displayed on mobile devices. To further support mass alerting, village siren systems are activated, producing loud alarms and voice announcements that prompt immediate evacuation. The system's hardware architecture includes a NodeMCU (ESP8266) microcontroller for data processing and transmission, Z44 MOSFETs for switching, and optocouplers for electrical signal isolation. Together, these components enable the system to provide rapid, automated, and reliable dam breach detection and early warning.

[0044] In another embodiment, the system includes a mobile application platform developed using computer science principles, which functions as a real-time evacuation assistant in the event of dam breaches. The mobile application, called SachiKavach, is activated as soon as a dam breach is detected and warnings are disseminated. While warnings alert the population to impending danger, the application is specifically designed to assist individuals in carrying out evacuations under time pressure. The application features a user-friendly interface with interactive tabs that present vital information, including maps showing emergency shelters, safe evacuation routes, nearby hospitals, government buildings, and designated aid centers.Additionally, the application displays hydrological data such as the extent of the flooding, predicted water depths, flow velocities, and estimated arrival times of the water. These features allow users to assess their situation in real time and make informed decisions. Integrated real-time location tracking enables users to continuously monitor their geographic position relative to safe and flood-prone areas. The application's communication module includes notifications, a chat interface, and a help tab through which users can request emergency assistance. Together, these features allow the mobile application to function as a digital evacuation assistant, significantly improving user awareness, safety coordination, and response capabilities in disaster situations.The SachiKavach platform therefore plays a vital role in supporting public safety and minimizing risks in the event of dam breaks.

[0045] In one embodiment, the system's geoinformatics analysis module is configured for dam failure analysis. The module's workflow includes input datasets, analysis operations, and the resulting outputs. The module is configured to develop the hydraulic model, utilizing multiple datasets, including satellite imagery, dam specifications, structural features, meteorological records, cadastral data, and historical flood information. These datasets are preprocessed and spatially integrated within a GIS (Geographic Information System) environment to create a consolidated geodatabase for analysis. Within this environment, geospatial analyses are performed to derive key topographic and hydrological parameters.Simultaneously, machine learning algorithms are being implemented in meteorological datasets to analyze temporal trends, detect anomalies, and improve the forecast accuracy of precipitation and flood events. The integration of these analytical processes strengthens the hydrological and hydraulic simulations that form the basis for assessing dam failure scenarios. The final results include high-resolution maps depicting flood zones, water depth, flow velocity, arrival times, and impact zones. These results serve as important resources for flood risk assessment, early warning systems, and evacuation planning.

[0046] In another embodiment, the hydrological component of the system is developed using HEC-HMS software to simulate rainfall-runoff behavior in the dam's catchment area. Input datasets for this model include digital elevation models (DEMs) for terrain mapping, meteorological records such as rainfall and temperature data, and satellite imagery reflecting land use and surface features. These inputs are preprocessed in a GIS framework to delineate catchments, river networks, and subdivisions into basins. The HEC-HMS model generates a hydrograph that depicts the temporal response of runoff to specific rainfall events. The output is presented graphically and in tabular form, containing time-runoff data essential for creating the inflow hydrograph for downstream hydraulic modeling.The hydraulic simulation of dam breach scenarios is performed using HEC-RAS software. This phase of the system requires extensive input data, including DEMs for accurate terrain representation, structural details of the dam, dam specifications, and geometric features of the river and adjacent floodplains. These datasets are processed in a GIS environment to define the model geometry, including river cross-sections and boundary conditions. The HEC-RAS hydraulic model simulates the dynamic behavior of floodwater following a dam breach and generates output planes describing water depth, flow velocity, arrival time, water level, and flood extent. These results are crucial for risk assessment, identifying at-risk zones, supporting evacuation planning, and integration into real-time early warning systems.

[0047] In one implementation, the system uses spatial overlay techniques within a GIS framework to identify affected villages and infrastructure. The results of the hydraulic model, such as flood extent, water depth, and arrival time, are overlaid on administrative boundary maps and settlement location datasets. This spatial correlation enables the precise identification of villages in flood-prone areas. Based on this identification, the system facilitates the strategic deployment of targeted early warning components in these settlements and ensures that each at-risk location receives tailored warnings in the event of a breach. To support this, the system implements a multi-channel communication protocol for disseminating early warnings.The warning system is configured to send alerts via multiple redundant channels to maximize reach and ensure that messages reach all affected areas. This includes activating high-decibel sirens, sending SMS alerts to mobile phones via GSM modules, delivering push notifications through the SachiKavach mobile application, and disseminating messages via social media, radio, and television networks. By utilizing this multi-source alert infrastructure, the system ensures that residents of high-risk areas receive prompt, reliable, and actionable information in the event of a dam breach. This multi-layered communication strategy enhances public preparedness, facilitates orderly evacuations, and minimizes potential loss of life and property.

[0048] In one embodiment, the system is equipped with a geoinformatics analysis module that facilitates the identification of the safest locations to serve as emergency shelters in the event of a dam breach. Since flooding caused by a dam breach is significantly more severe than typical river flooding, the system emphasizes precise spatial analysis to minimize casualties and ensure the safety of downstream populations. The integrated geodata framework incorporates various datasets from relevant authorities, including satellite imagery, digital elevation models (DEMs), weather records, soil properties, and road and river networks. From these datasets, the system derives a range of topographic and spatial indices, such as slope, elevation, runoff accumulation, and proximity to infrastructure, to assess the suitability and accessibility of the terrain.Based on this analysis, the system identifies optimal evacuation zones and creates safe and efficient evacuation routes, thereby improving the flood resilience of at-risk areas. The system incorporates a range of topographic, spatial, and spectral indices for developing geospatial models to assess flood-related hazards and vulnerabilities. These indices include elevation, slope, aspect, curvature, Topographic Wetness Index (TWI), drainage density, Topographic Position Index (TPI), Topographic Unevenness Index (TRI), Stream Power Index (SPI), Watershed Runoff Index, and Sediment Transport Index (STI). Furthermore, the system integrates spectral indices such as land use and land cover (LULC), Normalized Difference Vegetation Index (NDVI), and Normalized Difference Water Index (NDWI), as well as proximity indicators such as distance to rivers and roads, and meteorological variables such as precipitation distribution.These indices are calculated using remote sensing data, digital elevation models, and meteorological inputs, and processed in the GIS environment of the geoinformatics analysis module. The derived parameters are used in a multi-criteria decision analysis (MCDA) framework to generate a range of spatial models, including a flood vulnerability model, a flood susceptibility model, and a flood hotspot model. These models form the geospatial intelligence core of the system, enabling the accurate identification of high-risk zones and supporting evacuation planning and flood risk management. To support the development of the flood vulnerability and flood susceptibility models, the system includes a multi-criteria decision analysis framework capable of integrating topographic, hydrological, environmental, and infrastructural data layers.The system's analysis engine employs advanced decision support algorithms, including Analytic Hierarchy Process (AHP), Artificial Neural Networks (ANN), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Fuzzy AHP, and Logistic Regression. These algorithms enable the system to assign appropriate weights to each contributing index, assess their spatial influence, and generate composite flood risk scores. Historical flood data and ground-based observations validate the generated spatial models, ensuring a high degree of accuracy and reliability in flood risk assessment. The system's integrated flood vulnerability model identifies flood-prone zones based on a combination of surface morphology, hydrological behavior, meteorological data, and environmental conditions.The model incorporates several indices, such as elevation, slope, curvature, drainage density, TWI, SPI, NDVI, and NDWI, to assess the interaction between surface features and flood movement. This spatial layer, generated by the model, reflects the variability of flood vulnerability across the terrain and provides a detailed understanding of areas likely to experience water accumulation, high velocities, and flooding. This model serves as a crucial input for flood risk assessment, infrastructure planning, and strategic disaster management. The system also includes a flood vulnerability model that evaluates the extent of flood risk to populations, infrastructure, economic assets, and ecological systems. This model is based on three main components: exposure, sensitivity, and adaptive capacity.Hazard captures the concentration of people and assets in flood-prone areas; sensitivity assesses the likelihood of these elements being affected; and adaptability reflects their ability to withstand and recover from flood impacts. The model integrates a variety of vulnerability indicators, including social variables (e.g., population density, literacy, housing type), agricultural factors (e.g., crop types, land productivity), proximity to infrastructure (e.g., access to roads, hospitals, and schools), and economic indicators (e.g., income levels, employment patterns). By integrating geospatial and statistical data, the model generates a spatially explicit vulnerability level that supports targeted strategies for flood risk reduction, resource allocation, and resilience planning.The system's embedded Flood Hotspot Model highlights locations with a history of frequent or recurring flooding events. This model is based on the spatial and temporal analysis of historical flood data, including documented extents, recurrence intervals, and associated impacts. By identifying zones of persistent flood activity, the model helps prioritize areas for damage mitigation, infrastructure strengthening, and emergency preparedness. All spatial models developed by the system, including the Flood Vulnerability Model, the Flood Sensitivity Model, and the Flood Hotspot Model, are further integrated with datasets representing critical infrastructure such as road networks, hospitals, public buildings, emergency shelters, and government facilities.This integrated geospatial analysis enhances the system's ability to identify safe locations, plan optimal evacuation routes, locate designated aid depots, and pinpoint the nearest health facilities. These comprehensive spatial layers are not only used for disaster preparedness and evacuation coordination but are also embedded in the mobile application platform, allowing end users to access this information in real time during floods. This integration ensures dynamic, location-based guidance and improves the responsiveness of evacuation and relief efforts.

[0049] In one embodiment, the system's mobile application architecture is designed as a client-server backend framework, with Firebase serving as the central backend service for data storage, real-time communication, and user authentication. The system includes a mobile application platform called SachiKavach, developed with Flutter and running on both Android and iOS mobile devices. This end-user application integrates the Esri API directly to display spatial map layers, including hydrological and risk-related data. It connects to Firebase to submit help requests, receive real-time messages from administrators, and manage user authentication and profile information.

[0050] In one implementation, a web-based admin panel is integrated into the system, based on the MERN stack (MongoDB, Express.js, React, Node.js). Access to the admin panel is via a browser interface, and it communicates with Firebase through the Firebase Admin SDK, which is implemented in the Node.js backend. Administrators can query and manage user data, view help requests with associated geolocations, and send targeted messages to specific users. While MongoDB can be used to store admin-specific records, primary application data such as user profiles, help requests, and messages are stored in Firebase. The admin interface also provides a user management function that displays a list of all registered users by retrieving authentication and profile data from Firebase authentication and the Firestore or real-time database.The system also incorporates Firebase functionality as a central backend infrastructure, providing cloud data storage (via Firestore or the real-time database), user authentication services, and real-time data synchronization between the mobile application and the admin panel. Firebase ensures that updates such as new messages or help requests are immediately displayed on both the client and administration interfaces. The Esri API is specifically used in the mobile application to provide geospatial visualization capabilities. It supports the display of various map layers, such as base maps and hydrographic layers, and enables spatial functions like zooming and panning. While the Esri API is not used by the admin panel, it remains a core component of the end-user application's visual interface.

[0051] In one implementation, the system's mobile application includes several key features to assist users in dam breach emergencies, including: a multi-map view that allows the display of various geospatial interfaces and layers via the Esri API. This includes base maps and hydrological layers such as water depth, elevation, and the expected arrival time of the flood; a help request function, accessible via a dedicated "Help" button on the user interface, which allows users to transmit their current location (latitude and longitude) along with a distress signal to administrators; and a notification system that displays messages sent from the admin panel to end users in real time. Additionally, the mobile application's user interface includes: a registration function for new users and a login function for existing users.A central dashboard provides access to the locations of relief operations (e.g., hospitals, public assembly halls), mapped risk zones with flood-prone villages, and interactive hydrological layers with real-time data such as water depth, height, and flood arrival time. Together, these components enable the system to provide integrated early warning, evacuation assistance, real-time communication, and spatial awareness during flood disasters resulting from dam breaches.

[0052] In one embodiment, the system comprises a central main unit configured for dam breach detection, data processing, and multi-channel alert dissemination. This central system integrates several electronic and communication components to ensure real-time monitoring and automated response to potential dam breaches.

[0053] The system includes a radar level gauge installed above the reservoir that continuously monitors the water level by calculating the distance between the sensor and the water surface. A shorter measured distance corresponds to a higher water level. The system incorporates a predefined threshold to detect sudden and unusual drops in water level, which could indicate a dam breach or structural damage. Along the dam, the system integrates distributed fiber optic sensors (DFOS), either embedded or externally mounted, to provide continuous, high-resolution strain monitoring. These sensors can detect subtle anomalies such as increased strain, structural cracks, seepage, or vibration disturbances. Strain data is collected and compared to predefined thresholds.If these limits are exceeded, the system interprets this as an indication of possible instability or failure of the dam.

[0054] A NodeMCU (ESP8266) microcontroller acts as the system's processing unit. It receives real-time data from the radar level gauge and the DFOS sensors. If the NodeMCU detects conditions that exceed safety thresholds, such as a sudden drop in water level or abnormal stress, it initiates several response measures. It activates a Z44 MOSFET, which acts as a switching mechanism and triggers connected warning systems such as sirens. Simultaneously, the NodeMCU sends warning data to the Ubidots IoT platform via Wi-Fi and transmits emergency notifications via SMS to registered mobile phone numbers using a GSM module.

[0055] The Z44 MOSFET is configured to receive a HIGH signal from the NodeMCU under critical conditions. This signal closes the circuit and activates a connected siren, which triggers a loud alarm, alerting the surrounding communities to the emergency. The siren draws its power directly from a mains source and is electrically isolated via the MOSFET to ensure safe operation.

[0056] The GSM module, connected to the NodeMCU via serial communication pins, enables SMS-based alerting. Upon detection of a breach, the NodeMCU sends AT command sequences to the GSM module, which in turn sends pre-configured emergency messages to individuals in downstream high-risk areas.

[0057] The system also includes cloud-based monitoring capabilities through integration with Ubidots' IoT platform. The NodeMCU communicates with Ubidots via HTTP or MQTT protocols over Wi-Fi, sending real-time data on water level and load. Ubidots processes and displays the data using visual dashboards, charts, and status indicators. This configuration enables remote monitoring of the dam's condition from any location via the Ubidots web or mobile dashboard.

[0058] The electrical configuration of the system includes the following connections: • Radar level sensor to NodeMCU: VCC to 3.3 V, GND to GND, TRIG to D1, ECHO to D2 • DFOS to NodeMCU: VCC to 3.3V, GND to GND, TRIG to D1, ECHO to D2 • Z44 MOSFET to NodeMCU and Siren: Gate to D5, Drain to Siren (-), Source to GND • Siren on Z44: Positive terminal to power supply (+), negative terminal to drain of Z44 • GSM module to NodeMCU: TX (GSM) to RX (D7), RX (GSM) to TX (D8), VCC to power supply (+), GND to GND

[0059] Together, this integrated hardware architecture enables the system to continuously monitor the integrity of the dam, detect potential failure conditions, and initiate automatic early warning measures via sirens, SMS notifications, and cloud-based monitoring interfaces.

[0060] In one implementation, the initial system configuration involves setting up the Ubidots IoT platform by creating a device within which a variable named `play_alert` is added, serving as a control flag. This variable has two possible values: a value of 0 indicates that no alarm condition exists, while a value of 1 triggers the playback of an audio alarm. The `play_alert` variable can be toggled via the main system interface on the Ubidots dashboard. After Ubidots is set up, the NodeMCU microcontroller (ESP8266) connects to a specified Wi-Fi network and establishes communication with the Ubidots platform. Once connected, the NodeMCU sends HTTP GET requests to retrieve the current value of the `play_alert` variable. This allows the system to continuously monitor whether an alarm condition has been triggered.When the value of the variable `play_alert` is detected as 1, NodeMCU triggers an optocoupler circuit that simulates a button press on the siren speaker system, specifically emulating either a "Play" or "Next" button press to start audio playback. In situations where the Bluetooth speaker is configured to automatically play the first audio file when a USB drive is inserted, the system simply turns on the speaker and inserts the USB device to start the siren playback. Alternatively, NodeMCU can also simulate a button press using an optocoupler or relay to replay the sound if needed. For button simulation, the contacts of the "Play" or "Next" buttons on the speaker's printed circuit board (PCB) are identified. Wires are then connected from these button contacts to a relay or optocoupler controlled by the NodeMCU.The microcontroller activates the relay or optocoupler for a short duration, usually between 500 and 1000 milliseconds, simulating a brief physical button press and triggering playback of the audio alarm stored on the USB stick.

[0061] The proposed integrated system for dam breach analysis, IoT-based real-time evacuation, and early warning is designed to detect dam breaches and provide evacuation instructions and early warnings in real time. The integration of IoT technologies enhances the system's ability to support timely decision-making, improve public preparedness, and reduce the potential impact of devastating dam breaches.

[0062] The drawing and the preceding description show examples of embodiments. Those skilled in the art will recognize that one or more of the described elements can be combined to form a single functional element. Alternatively, certain elements can be divided into several functional elements. Elements of one embodiment can be added to another embodiment. For example, the sequence of the processes described here can be changed and is not limited to the manner described here. Furthermore, the actions of a flowchart need not be performed in the sequence shown; nor does it necessarily have to be performed all actions. Actions that are not dependent on other actions can also be performed in parallel with the other actions. The scope of the embodiments is in no way limited by these specific examples.Numerous variations are possible, whether explicitly stated in the specification or not, such as differences in structure, dimensions, and material use. The range of embodiments is at least as broad as specified in the following claims.

[0063] Advantages, further benefits, and problem solutions have been described above with reference to specific embodiments. However, the advantages, benefits, problem solutions, and all components that can lead to an advantage, benefit, or solution occurring or becoming more apparent are not to be construed as critical, necessary, or essential features or components of individual or all claims. REFERENCES 100 An Integrated System for Dam Break Detection, Early Warning System and Evacuation Assistance. 102 Geoinformatics Analysis Module 104 Sensor monitoring subsystem 104a Distributed Fiber Optic Sensor (DFOS) 104b Radar level gauge 106 Microcontroller Unit 106a Nodemcu (ESP8266) Microcontroller 106b Z44 MOSFETS 106c Optocoupler 108 Communication module 110 warning system 112 GSM communication module 114 An evacuation assistance platform

Claims

[1] An integrated system for dam breach detection, early warning and evacuation assistance, consisting of: A geoinformatics analysis module comprising a modeling processor with a graphics processing unit, configured to: analyze spatial, hydrological, and topographic data of a dam and its downstream area; generate hydrological models using probable maximum rainfall (PMP) data to determine probable maximum flood discharge (PMF); generate hydraulic models to simulate flood propagation and determine flood depth, flood extent, flow velocity, and flood arrival time; create flood vulnerability models, vulnerability models, and flood hotspot models using a multi-criteria decision-making (MCDM) framework; and generate evacuation plans for high-risk zones based on the models. A sensor monitoring subsystem includes: a distributed fiber optic sensor (DFOS) configured to monitor the structural load and deformation of a dam, and a radar level gauge configured to measure the water level in the reservoir; a microcontroller unit configured to receive and process sensor data from the sensor monitoring subsystem, to detect dam breaches based on abnormal structural movements detected by the DFOS or sudden drops in water level below predefined thresholds detected by the radar level gauge; a communication module configured to transmit warning messages when dam breaches are detected; a warning system configured to: send SMS notifications to residents in downstream high-risk zones via a GSM communication module, generate real-time alerts via an IoT platform on user devices, and activate siren systems in villages to issue loud alarms and voice announcements; and an evacuation assistance platform configured to provide real-time evacuation assistance in emergencies due to dam breaks, displaying site maps with nearby emergency shelters, evacuation routes, hospitals, government buildings and aid centers, showing hydrological layers including flood extent, water depth, flow velocity and arrival time of the water, and enabling real-time location tracking in relation to safety zones and flood-prone areas. [2] System according to claim 1, wherein the geoinformatics analysis module is further configured to: integrate remote sensing datasets including satellite imagery, precipitation data and digital elevation model (DEM) using Geographic Information System (GIS) tools; derive more than 15 topographic and hydrological indices to support the multi-criteria decision-making framework; and integrate geodatasets including road networks and building footprints to assess infrastructure vulnerability. [3] System according to claim 1, wherein the microcontroller unit comprises: a NodeMCU (ESP8266) microcontroller configured to process and transmit sensor data; Z44 MOSFETs configured to perform switching operations; and optocouplers configured to provide electrical signal isolation. [4] System according to claim 1, wherein the IoT platform comprises Ubidots IoT platform configured to enable the generation of real-time alerts on user devices. [5] System according to claim 1, wherein the DFOS is installed along the dam and configured to: continuously monitor the structural load and deformation, detect abnormal movements or deviations from expected values, and interpret detected anomalies as possible signs of structural instability or incipient failure. [6] System according to claim 1, wherein the radar level sensor is configured such that it: measures the water level in the reservoir with high precision, detects sudden and unexpected drops in water level, and generates breakthrough indicators when the water level falls below predefined thresholds. [7] System according to claim 1, wherein the evacuation aid platform is configured as follows: a user-friendly interface with interactive tabs; a communication module with notification alerts, a chat interface and a help tab for emergency assistance requests; a real-time location tracker that allows users to monitor their position in relation to safe zones and flood-prone areas; and a dynamic guidance function that provides real-time evacuation assistance. [8] System according to claim 1, wherein the alarm dissemination system further comprises: the GSM communication module configured to automatically send SMS notifications to residents in downstream high-risk areas upon detection of a breach; and siren systems installed in villages configured to be automatically triggered and to emit loud alarms and voice announcements instructing evacuation. [9] System according to claim 1, wherein the system is configured to: automatically activate an early warning protocol upon detection of dam breaches; provide comprehensive mapping of flood risk based on the integration of the flood vulnerability model, the susceptibility model and the flood hotspot model; and facilitate disaster risk reduction through coordinated sensor monitoring, automatic alerting and real-time evacuation assistance.

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