Anti-drowning monitoring method and system based on multi-source positioning data

Abstract

The invention relates to the technical field of anti-drowning monitoring, and particularly discloses an anti-drowning monitoring method and system based on multi-source positioning data, and the method comprises the steps: wading environment multi-source data collection, positioning fusion and state marking, virtual safety area dynamic modeling, positioning safety dynamic evaluation and multistage linkage rescue response. By integrating satellite positioning, indoor positioning, wearable equipment and environment scanning equipment, the position, physiological state and environment data of a wading person are collected in real time, a dynamic reliability weight calculation and space-time alignment compensation technology is adopted, a fusion positioning coordinate is generated, an elastic virtual safety area boundary is constructed, and the safety of the wading person is improved. And finally, evaluating the risk through a safety scoring algorithm, and triggering a multi-level linkage rescue response, including wearable device alarm, sound-light alarm, unmanned aerial vehicle scheduling and first-aid system linkage. According to the method, the timeliness and the accuracy of drowning risk discovery are remarkably improved, and the rescue resource scheduling efficiency and the emergency response quickness are optimized.

Description

Technical Field

[0001] This invention belongs to the field of drowning prevention monitoring technology, and relates to a drowning prevention monitoring method and system based on multi-source positioning data. Background Technology

[0002] The field of water safety monitoring involves technologies for tracking the location of people in water, monitoring their physiological state, and identifying environmental risks. Conventional systems rely on satellite positioning, wearable sensing devices, and fixed scanning devices to collect user behavior data. However, a key problem is that multi-source signals are easily interfered with by water reflection and spatial obstruction, leading to location deviations or misjudgments of vital signs. Furthermore, static methods of dividing safety zones are ill-suited to responding to new risks arising from fluctuations in water levels and dynamic changes in population density.

[0003] Current mainstream solutions employ a single signal source-dominated positioning model, such as using Global Navigation Satellite System coordinates as the primary positioning basis, supplemented by heart rate abnormality thresholds triggered by wearable devices to activate local alarms. Safe zone management relies on fixed geofences, with boundaries statically set based on historical water level mapping data. Risk response mechanisms follow preset rules; when vital signs exceed thresholds or locations cross boundaries, a unified level of audible and visual alarms and manual rescue procedures are triggered.

[0004] The aforementioned solutions are prone to generating incorrect location labels in multi-source signal conflict scenarios due to fixed weight allocation, and location drift in weak signal environments may mask the true dangerous posture. Static safety fences cannot adapt to the instantaneous changes in risk patterns caused by sudden rainstorms or tourist congestion, resulting in misalignment between restricted area boundaries and actual threat areas. The response mechanism lacks a risk quantification and tiered design; low-level false alarms consume lifesaving resources, while complex high-risk events may delay the initiation of critical rescue actions because they do not trigger multi-level response thresholds. Summary of the Invention

[0005] In view of this, in order to solve the problems mentioned in the background technology, a drowning prevention monitoring method and system based on multi-source positioning data is proposed.

[0006] The objective of this invention can be achieved through the following technical solution: The first aspect of this invention provides a drowning prevention monitoring method based on multi-source positioning data, including: S1, multi-source data acquisition of water-related environment: acquiring real-time environmental perception data packets of users in water-related areas, wherein the environmental perception data packets include absolute position coordinates generated by satellite positioning signals, relative position coordinates generated by indoor positioning base station signals, motion state quantities and vital sign parameters transmitted by wearable devices, and temperature distribution matrix and visibility index collected by environmental scanning devices.

[0007] S2. Positioning Fusion and Status Labeling: Calculate dynamic reliability weights for the positioning signal sources in the environmental perception data packet, perform spatiotemporal alignment compensation to generate fused positioning coordinates, and output associated status labels. The status labels include water safety status, underwater activity status, and equipment detachment abnormal status.

[0008] S3. Dynamic Modeling of Virtual Safe Zones: Load the preset electronic base map of the water area, combine it with real-time water level monitoring data, user distribution thermal data and historical accident area markers, and construct the boundary of the virtual safe zone, which includes elastic thresholds and scaling rules.

[0009] S4. Dynamic assessment of positioning security: The fused positioning coordinates are compared with the boundary of the virtual security zone in a spatial overlay, and a dynamic security score is generated based on the duration of triggering rules A, B and C.

[0010] S5. Multi-level linkage rescue response: Based on the gradient range of the dynamic safety score, activate the multi-level linkage rescue signal chain, triggering wearable device vibration alarm, sound and light alarm device activation, water surface drone dispatch or emergency system transmission.

[0011] The second aspect of the present invention provides a drowning prevention monitoring system based on multi-source positioning data, comprising: a multi-source data acquisition module for water-related environments, which acquires real-time environmental perception data packets of users in water-related areas, wherein the environmental perception data packets include absolute position coordinates generated by satellite positioning signals, relative position coordinates generated by indoor positioning base station signals, motion state quantities and vital sign parameters transmitted by wearable devices, and temperature distribution matrix and visibility index acquired by environmental scanning devices.

[0012] The positioning fusion and status labeling module calculates dynamic reliability weights for the positioning signal sources in the environmental perception data packet, performs spatiotemporal alignment compensation to generate fused positioning coordinates, and outputs associated status labels, including water safety status, underwater activity status, and equipment detachment abnormal status.

[0013] The virtual safety zone dynamic modeling module loads a preset electronic map of the water area and combines it with real-time water level monitoring data, user distribution thermal data, and historical accident area markers to construct a virtual safety zone boundary that includes elastic thresholds and scaling rules.

[0014] The location security dynamic assessment module performs spatial overlay comparison between the fused location coordinates and the virtual security zone boundary, and generates a dynamic security score based on the duration of triggering rules A, B and C.

[0015] The multi-level linkage rescue response module activates the multi-level linkage rescue signal chain based on the gradient range of the dynamic safety score, triggering wearable device vibration alarm, sound and light alarm device activation, water surface drone dispatch or emergency system transmission.

[0016] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: (1) The present invention, through the collaborative work of multiple sensors, can collect and comprehensively process the user's location information, physical condition and surrounding environment data in real time. This multi-source information deep integration technology breaks through the limitations of a single signal source and can keenly capture the abnormal dynamic change trend of the user, such as continuous sinking or sudden deterioration of vital signs, which significantly improves the timeliness and accuracy of discovering potential drowning risks.

[0017] (2) This invention overcomes the rigidity of traditional fixed safety zone management by creatively adjusting the virtual safety zone boundaries in the electronic map based on real-time water level changes, population density, and historical lessons learned. This generates a flexible spatial control measure, enabling the identification and prevention measures of dangerous areas to respond flexibly to environmental dynamics and population behavior patterns, effectively reducing the risk of safety blind spots caused by sudden environmental changes or overcrowding.

[0018] (3) This invention innovatively designs a safety scoring algorithm based on location tag and behavior pattern matching. By conducting in-depth comparative analysis between the user's real-time status and predefined multi-dimensional risk rules, the algorithm can continuously calculate and accumulate to generate a quantitative dynamic safety score. This enables the identification and real-time tracking of the degree of danger faced by an individual, providing an objective and refined decision-making basis for subsequent graded responses.

[0019] (4) This invention constructs a tiered rescue response process based on risk scoring levels. Once the risk assessment reaches a specific level, the corresponding rescue action chain is automatically triggered, from alerting users at the device end to activating audible and visual alarms in the area, from guiding lifeguards to accurate positioning to mobilizing surface drones to stand by, and finally coordinating the emergency medical system to respond in a coordinated manner at the highest risk level. This tiered response architecture significantly optimizes the scheduling efficiency of rescue resources and the speed of emergency response. Attached Figure Description

[0020] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a schematic diagram of the method steps of the present invention.

[0022] Figure 2 This is a schematic diagram of the system structure connection of the present invention.

[0023] Figure 3This is a schematic diagram of the status tag output steps of the present invention. Detailed Implementation

[0024] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0025] See also Figure 1 As shown, the first aspect of the present invention provides a drowning prevention monitoring method based on multi-source positioning data, including: S1, multi-source data acquisition of water-related environment: acquiring real-time environmental perception data packets of users in water-related areas, wherein the environmental perception data packets include absolute position coordinates generated by satellite positioning signals, relative position coordinates generated by indoor positioning base station signals, motion state quantities and vital sign parameters transmitted by wearable devices, and temperature distribution matrix and visibility index collected by environmental scanning devices.

[0026] It should be noted that the deployment in this water-affected area includes satellite positioning receivers, indoor positioning signal base stations, wearable devices worn on the user's body, and environmental scanning equipment installed on the shore. When a user enters the monitored water area, the synchronization modules of all devices are activated to ensure that the timestamps of each signal acquisition are aligned. The satellite positioning receivers continuously analyze the radio signals broadcast by the Global Navigation Satellite System to generate absolute position coordinates including longitude, latitude, and altitude. The indoor positioning signal base stations use ultra-wideband or Bluetooth technology to measure the round-trip time difference between the user's wearable device and at least three base stations to calculate the relative position coordinates with centimeter-level accuracy. The wearable device has a built-in accelerometer... The temperature sensor records the three-dimensional movement speed and direction changes of the limbs to form motion state quantities. The integrated heart rate sensor and blood oxygen sensor detect blood pulsation characteristics through photoelectric detection and output the heart rate per minute and hemoglobin oxygen saturation as vital sign parameters. The environmental scanning device uses a thermal radiation imager to receive infrared rays emitted by the human body to form a temperature distribution matrix. At the same time, it uses an active millimeter-wave radar to emit electromagnetic waves and capture the reflected signals of obstacles to analyze the visibility index. The data aggregation unit packages the above-mentioned absolute position coordinates, relative position coordinates, motion state quantities, vital sign parameters, temperature distribution matrix and visibility index on a periodic basis to form a standardized environmental perception data package.

[0027] It should be further explained that the absolute position coordinates refer to the geographical location values ​​based on the WGS-84 Earth coordinate system, calculated by decoding the carrier phase and pseudorange information transmitted by the Global Navigation Satellite System and applying the trilateration principle; the relative position coordinates refer to the three-dimensional rectangular coordinate data calculated by solving a system of geometric hyperbolic equations, using time difference of arrival positioning technology, by measuring the time difference of arrival of radio pulse signals transmitted by the wearable device through at least three indoor positioning signal base stations located at fixed positions on the ceiling or wall of the pool; the motion state quantity refers to the displacement change calculated by integrating the X-axis, Y-axis and Z-axis acceleration values ​​recorded by the three-axis accelerometer in the wearable device within the sampling period and combining it with the gyroscope angular velocity data, with the dimension of meters per second.

[0028] Furthermore, it should be noted that the vital signs parameters refer to the percentage of blood oxygen saturation calculated using a ratio method based on the difference in absorption rate of hemoglobin to different wavelengths of light emitted by the optical sensing module of the wearable device in contact with the skin, which emits nano-red light and nano-infrared light; and the number of heartbeats per minute converted by detecting the photoplethysmogram peak interval. The temperature distribution matrix refers to the dot matrix data composed of 14-bit digital temperature values, in degrees Celsius, formed by the uncooled infrared focal plane array in the environmental scanning device scanning the target area at a fixed frequency and converting the infrared radiation energy received by each pixel into a dot matrix. The visibility index refers to the scattering coefficient of nano-green light by suspended particles in the air at a height of 1 meter above the water surface, calculated by millimeter-wave radar based on the Doppler effect by measuring the frequency offset between the transmitted pulse and the received echo signal. A value greater than 50 indicates good visibility, and a value less than 20 indicates poor visibility.

[0029] S2. Positioning Fusion and Status Labeling: Calculate dynamic reliability weights for the positioning signal sources in the environmental perception data packet, perform spatiotemporal alignment compensation to generate fused positioning coordinates, and output associated status labels. The status labels include water safety status, underwater activity status, and equipment detachment abnormal status.

[0030] See also Figure 3 As shown, in a specific embodiment of the present invention, the specific process of outputting the associated status tag is as follows: S21, calculate the dynamic reliability weight based on the satellite positioning signal reception strength, the indoor positioning base station line-of-sight obstruction mark, the immersion depth of the wearable device, and the visibility index.

[0031] S22. Using absolute position coordinates as a reference, perform a weighted average on conflicting position data to generate fused positioning coordinates.

[0032] S23. Analyze the characteristics of abrupt changes in vital sign parameters and the trends of motion state quantities, and output state labels.

[0033] It should be noted that the central processing unit receives periodically transmitted environmental awareness data packets and performs feature decoupling on the absolute position coordinates, relative position coordinates, and vital sign parameters within the packets. A dynamic reliability weight calculation model is established for each positioning signal source. This model generates a reliability score from 0 to 1 based on four environmental interference parameters: satellite signal reception strength, indoor base station line-of-sight obstruction markers, wearable device immersion depth data, and environmental visibility index. The score quantification formula is as follows: ,in, Indicates the first The reliability score of each signal source. These are the normalized weighting coefficients calibrated through experiments. The current satellite signal reception strength is obtained through measurements at the physical layer of the satellite receiver, in units of... , This represents the line-of-sight obstruction flag value for indoor base stations. A value of 0 indicates obstruction between the indoor base station and the wearable device if there is reinforced concrete obstruction, and a value of 1 indicates no obstruction. Immersion depth measured by a pressure sensor on a wearable device, in centimeters. The visibility index fed back by the millimeter-wave radar is a value normalized to the range of 0-1. and These represent the satellite signal reception strength and the immersion depth of the wearable device, respectively, and their values ​​were obtained through experimental data. Indicates the signal source number. Then, using the absolute position coordinates as the reference coordinate system, all positioning data timestamps are aligned with second-level precision. A weighted average is then calculated for multiple positioning points with spatial conflicts. The weights are dynamically allocated based on the reliability score using the following formula: ,in, For the The original three-dimensional coordinates of the signal source The system integrates location coordinates and analyzes vital signs parameters, including blood oxygen saturation. When the pulse signal disappears and blood oxygen saturation is 0, an abnormal status label for the device is triggered. When the wearable device's accelerometer detects continuous downward acceleration along the Z-axis and the integrated location coordinates are located in the underwater area, it is marked as an underwater activity state. In other cases, it is marked as a safe state on the water. Finally, the system outputs integrated location coordinates and status labels that combine location information and safety assessment.

[0034] It should also be noted that the dynamic reliability weight calculation model specifically refers to the mathematical relationship established based on the physical layer signal state and environmental parameters. The indoor base station line-of-sight obstruction marker is determined by collision detection using a pre-established three-dimensional spatial topology map of the base station and real-time user location rays. The immersion depth data of the wearable device is measured by the device's built-in water pressure sensor. The environmental visibility index is a normalized value obtained by looking up an empirical mapping table based on the millimeter-wave radar echo intensity and frequency broadening characteristics. Spatiotemporal alignment compensation specifically refers to adding nanosecond-level timestamps to all location data using a unified UTC time base. Within the calculation period, linear interpolation is used based on a time window to fill the position drift between sampling intervals. The compensation mechanism is triggered when the horizontal difference between the absolute position coordinates of the global navigation satellite system and the relative position coordinates of the indoor base station exceeds 3 meters.

[0035] In a specific embodiment of the present invention, the device detachment abnormality status tag specifically refers to the device detachment warning state triggered when no heartbeat signal is detected from the wearable device for 10 consecutive sampling cycles and the tissue blood oxygen saturation characteristics detected by the optical sensor disappear, while the thermal imaging of the environmental scanning device shows a heat source signal that does not match the wearable device number. This state has the highest judgment priority. The underwater activity status tag specifically refers to the water pressure value detected by the wearable device pressure sensor being greater than the local atmospheric pressure by 5 kPa for more than 3 seconds, while the Z-axis value of the fused positioning coordinates is lower than the water surface reference plane. This reference plane is determined in real time by updating the water level line coordinates of the water area electronic bottom map. The water safety status tag specifically refers to the default safety label assigned when the vital signs parameters are within the normal range, blood oxygen saturation is above 90%, and the pulse waveform is continuously present, even if the conditions for determining the device detachment abnormality status or underwater activity status are not met.

[0036] S3. Dynamic Modeling of Virtual Safe Zones: Load the preset electronic base map of the water area, combine it with real-time water level monitoring data, user distribution thermal data and historical accident area markers, and construct the boundary of the virtual safe zone, which includes elastic thresholds and scaling rules.

[0037] In a specific embodiment of the present invention, the specific process of constructing the virtual safe zone boundary including elastic threshold and scaling rules is as follows: S31, calculate the offset of the pool bottom boundary based on real-time water level monitoring data, and dynamically adjust the depth and shallow partitions of the water area electronic map.

[0038] S32. Generate user distribution thermal data based on fused positioning coordinate density to drive the expansion of the warning zone boundary.

[0039] In a specific embodiment of the present invention, the method for generating user distribution thermal data based on fused positioning coordinate density is as follows: in the plane coordinate system of the water electronic base map, each grid cell is divided with a set unit area, the number of fused positioning coordinates falling into each grid cell is counted, and the ratio between the number of fused positioning coordinates in each grid cell and the area of ​​the grid cell is used as the thermal value of each grid cell.

[0040] S33. Set an absolute restricted area elastic threshold based on the frequency of historical accident area markings.

[0041] It should be noted that the water area management terminal loads the water area electronic base map data from the storage medium. This base map is a pre-set two-dimensional vector map, including the pool bottom elevation line, fixed equipment coordinate points, and initial shallow and deep zone boundaries. Simultaneously, it accesses the fused positioning coordinate stream output from step S2 and uses a map coordinate spatial density algorithm to count the number of users per unit area, generating user distribution heat map data. This is combined with historical accident area marker data stored in the database, i.e., geographical location records of historical slips, cramps, and drowning incidents. The processor overlays the water level elevation information onto the pool bottom elevation line of the electronic base map, shifting the shallow water zone boundary towards the deep water zone by an offset amount. According to the formula Calculate, where, For real-time water level monitoring data, This is the baseline water level for the dry season. The slope angle of the pool bottom is obtained from the electronic base map survey data.

[0042] It should also be noted that the electronic base map of the water area specifically refers to a vector format map file constructed using a geographic information system, containing the three-dimensional structural coordinates of the swimming pool marked with actual measurement data, including the coordinates of the pool wall vertices, the elevation values ​​of the points where the pool bottom slope changes, the coordinates of the drain outlets, and the initial safety zone boundaries. Real-time water level monitoring data specifically refers to the water pressure values ​​collected by pressure transmitters installed on the side walls of the shallow water area of ​​the pool, after temperature compensation. Converting hydrostatic formulas into water level elevation values Take the density of water as 1000 kg / m³. The acceleration due to gravity is taken as 9.8 m / s². Historical accident area markings specifically refer to the storage of these areas in the database in the form of geographic coordinates. Each accident record includes the event type and timestamp; the system automatically clusters accident coordinate points and generates high-risk hotspot weight values. According to the formula Calculate, where N is the total number of accidents within the set range.

[0043] It should also be noted that the elastic threshold is a dynamic adjustment mechanism set for the radius of the absolute restricted area. When the frequency of historical accidents in the associated area reaches the set frequency, the base radius is expanded from the predetermined value to a radius value with a reasonable increase. At the same time, the accident records are reviewed at fixed intervals, and the threshold is automatically updated based on the review results.

[0044] For example, when the frequency of historical accidents in the associated area reaches 2 per month, the basic radius is expanded from the predetermined value of 3 meters to 4.5 meters after a reasonable increase, and the accident records are reviewed weekly.

[0045] It should also be noted that the warning zone expansion rule specifically refers to the mechanism of dynamically adjusting the safety margin based on user distribution thermal data. When the thermal value of a certain grid cell reaches the set reference thermal value, the area warning boundary of that grid cell automatically expands outward by a certain distance. According to the formula Calculation, where The empirical coefficient is set to 0.25. The current heat value, To set a safe density threshold, a value of 60 people per 100 square meters is used, and a reference thermal value of 80 people per 100 square meters can be set.

[0046] S4. Location security dynamic assessment: The fused location coordinates are spatially overlaid and compared with the virtual security zone boundary, and a dynamic security score is generated based on the duration of the trigger rule combination A / B / C.

[0047] In a specific embodiment of the present invention, the triggering rules A, B and C specifically refer to: Rule A: The fused positioning coordinates enter the absolute forbidden zone and the motion state quantity triggers a continuous sinking action marker.

[0048] Rule B: The fused positioning coordinates remain in the warning zone and the vital signs parameters exceed the critical rate of change.

[0049] Rule C: The status label indicates an abnormal device detachment and no matching coordinate set of the shore safety zone is detected.

[0050] In a specific embodiment of the present invention, the method for generating dynamic security scores is as follows: when rule A is triggered, a first weight score is accumulated; when rule B is triggered, a second weight score is accumulated; when rule C is triggered, a third weight score is accumulated; and a superposition algorithm is used to synthesize a score signal for concurrent rules. The third weight score is greater than the first weight score and the second weight score.

[0051] It should be noted that the fused positioning coordinates are mapped to the electronic base map coordinate system of the water area to detect their spatial inclusion relationship with the elastic threshold boundary of the absolute restricted area. When the coordinate point is located within the absolute restricted area, rule A is activated, and the determination engine analyzes the continuous downward acceleration value in the Z-axis direction of the motion state variables. If the acceleration is lower than the standard value of gravitational acceleration for N consecutive sampling cycles, a continuous sinking action marker is triggered. Next, the fused positioning coordinates are scanned to see if they are within the coverage area of ​​the warning zone scaling rule. When the continuous stay exceeds a set time threshold, rule B is activated, and the determination engine calculates the mutation rate formula for vital sign parameters as follows: ,in This is the current blood oxygen saturation sample value. This is the previous sampled value. The sampling interval time is when When the critical rate of change is exceeded, a sudden drop in vital signs is recorded; when the status label shows the abnormal state of the device being detached from the device, rule C is triggered again to determine whether the engine detects and fuses the positioning coordinates to see if they are outside the preset shore safety zone coordinate set and continue to exceed the shore timeout threshold; when rule A is triggered, the processor establishes a dynamic safety score accumulation model and increases the score value by one point per second. When rule B is triggered, it increases by 1 / 2. When rule C is triggered, it increases by 1 / 2. The scoring weights satisfy For scenarios that simultaneously satisfy multiple rules, a weighted superposition algorithm is used to finally output a dynamic safety score signal that accumulates over time, with the numerical range corresponding to five levels of danger.

[0052] It should also be noted that the spatial positional relationship calculation specifically refers to using the ray casting method to determine the positional relationship between a point and a polygon. A closed polygon is constructed using the virtual safety zone boundary coordinate data. The number of intersections between the horizontal projection point of the fused positioning coordinates and the polygon's edge determines whether it is located inside or outside the absolute restricted or warning zone. This calculation relies on the unified coordinate system benchmark of the water area electronic base map. The continuous sinking motion marker specifically refers to a motion state quantity where the Z-axis acceleration value is consistently less than the standard value of gravitational acceleration within the sampling period, accompanied by a monotonically increasing depth value detected by the wearable device's pressure sensor. When continuous sampling conforms to this pattern, a descent process is triggered, confirming that the marker possesses a continuous time-dimensional characteristic.

[0053] In a specific embodiment of the present invention, the critical rate of change specifically refers to a personalized threshold obtained through training with the user's historical health data. The critical rate of change for healthy people is set to a decrease of 15% in blood oxygen saturation per minute, while a conservative threshold of 10% decrease per minute is used for users with a history of respiratory diseases.

[0054] It should also be noted that the coordinate set of the shore safety zone specifically refers to the landing platform area marked on the electronic base map of the water area. The dynamic safety score accumulation model specifically refers to the use of a non-reset integrator structure, which accumulates the score rule with a fixed increment when the rule is triggered, maintains the current score when the triggering stops, and resets it to zero after a continuous safety period of T seconds in the absence of rule triggering. The integration time constant is positively correlated with the duration of danger.

[0055] For example, the weighted stacking algorithm specifically refers to a score synthesis method in multi-rule concurrent scenarios. If rule A and rule B are activated simultaneously, the score increases by [number] points per second. If all three rules are activated simultaneously, the increase per second... .

[0056] In one specific embodiment of the present invention, the specific scores in the weighted superposition algorithm should be comprehensively determined based on the actual needs of the system, security standards, risk assessment results, and historical data analysis. The selection of these scores aims to ensure that, in the event of multiple concurrent rules, the degree of danger faced by the user can be accurately and reasonably reflected, and that corresponding levels of alarms and rescue measures are triggered. In this invention, the values ​​include, but are not limited to, 1.5.

[0057] S5. Multi-level linkage rescue response: Based on the gradient range of the dynamic safety score, activate the multi-level linkage rescue signal chain, triggering wearable device vibration alarm, sound and light alarm device activation, water surface drone dispatch or emergency system transmission.

[0058] In a specific embodiment of the present invention, the specific method for activating the multi-level linkage rescue signal chain is as follows: S51, when the dynamic safety score exceeds the first-level threshold, a vibration alarm signal is sent to the wearable device and a location prompt message is pushed to the management platform.

[0059] S52. When the dynamic safety score exceeds the level 2 threshold, activate the audible and visual alarm device, send a rescue guidance package containing an electronic map of the water area to the lifeguard terminal, and activate the surface drone to fly to the fused positioning coordinates.

[0060] In a specific embodiment of the present invention, the rescue guidance package is generated in the following manner: extracting vector slices centered on fused positioning coordinates from the electronic base map of the water area, and superimposing absolute no-go zone markers and real-time virtual safe zone boundaries to form a rescue guidance package.

[0061] S53. When the dynamic safety score exceeds the level 3 threshold, control the drainage outlet to close and the emergency lighting to focus, and generate a structured rescue request package containing vital signs parameters and water level monitoring data to be transmitted to the emergency rescue system.

[0062] In one specific embodiment of the present invention, the specific values ​​of the primary, secondary, and tertiary thresholds need to be determined based on the actual needs of the system, safety standards, and historical data analysis. In practical applications, these thresholds may be optimized through system testing and adjustments to ensure that the drowning prevention monitoring system can accurately and promptly trigger corresponding levels of alarms and rescue measures at different risk levels.

[0063] It should be noted that when the dynamic safety score first crosses the preset first-level threshold, a vibration alarm command is automatically generated and sent to the user's wearable device via Bluetooth Low Energy protocol. The motor drive unit triggers regular vibrations and simultaneously writes a location alert message containing the fused positioning coordinates and a status tag text to the management platform display. When the dynamic safety score continues to rise and crosses the second-level threshold, the audible and visual alarm device located in the corresponding grid area at the boundary of the virtual safety zone is activated, generating flashing lights and alarm sounds at specific frequencies. At the same time, a coordinate map with absolute restricted area markings is generated by calling up the electronic base map slices of the water area. This coordinate map is then overlaid with the user's real-time fused positioning coordinates to form a rescue guidance package, which is sent to the lifeguard's handheld terminal to trigger navigation path display. Simultaneously, a fused positioning coordinate command containing Z-axis elevation data is sent to the surface drone dispatch system, which adjusts its flight altitude based on the visibility index of the real-time environmental scanning equipment in the flight time prediction formula. , Calculate the planar distance based on the coordinate difference. For the maximum safe speed of the drone, The value of the headwind compensation is obtained based on experimental data. When the dynamic safety score exceeds the level 3 threshold, a shutdown command is sent to the pool drain controller to cut off the power to the water pump, control the emergency lighting equipment to turn on the high-intensity light mode, and generate a structured rescue request package containing vital signs parameters and water level monitoring data, which is then transmitted to the emergency rescue system.

[0064] In one specific embodiment of the present invention, the target area of ​​the audible and visual alarm device is defined by pre-storing the spatial mapping relationship of all fixedly installed alarm devices within a radius of 15 meters centered on the fused positioning coordinates in the coordinate layer of the electronic base map device. The rescue guidance package specifically refers to a geographic data message compressed into JSON format, containing a geographic tile centered on the current user's location on the electronic base map of the water area. This tile uses vector tile technology to draw and label dynamically updated virtual safety zone boundaries and deep-water contour data.

[0065] It should also be noted that the specific operational procedure for the surface drone to arrive at the coordinate point and wait is as follows: the drone plans its flight path based on the latitude and longitude information of the fused positioning coordinates. During flight, it identifies the positioning beacon emitted by the environmental scanning equipment through its onboard camera, thereby achieving hovering positioning. The Z-axis elevation data of the fused positioning coordinates specifically refers to the value representing the vertical height in the output three-dimensional coordinates. This data, combined with the water level datum of the electronic base map of the water area, calculates the minimum release height for the drone to drop the lifebuoy. The specific formula for predicting the water flight time is as follows: ,in The current coordinates of the drone. To fuse the horizontal component of the target's positioning coordinates, This is the upper limit of the airspeed of drones. This is the real-time wind speed value from the weather station. This is the wind resistance compensation coefficient, and its specific value is obtained from experimental data.

[0066] Reference Figure 2 As shown, the second aspect of the present invention provides a drowning prevention monitoring system based on multi-source positioning data, including: a multi-source data acquisition module for water-related environments, a positioning fusion and status marking module, a virtual safety zone dynamic modeling module, a positioning safety dynamic assessment module, a multi-level linkage rescue response module, and a database.

[0067] It should be noted that the database is used to store historical accident area marker data, namely, the geographical location records of historical slip, cramp, and drowning incidents.

[0068] The water-related environment multi-source data acquisition module is connected to the positioning fusion and status marking module, the positioning fusion and status marking module is connected to the virtual safe zone dynamic modeling module, the virtual safe zone dynamic modeling module is connected to the positioning safety dynamic assessment module, the positioning safety dynamic assessment module is connected to the multi-level linkage rescue response module, and the virtual safe zone dynamic modeling module is connected to the database.

[0069] The multi-source data acquisition module for the water-related environment acquires real-time environmental perception data packets for the user in the water-related area. The environmental perception data packets include absolute position coordinates generated by satellite positioning signals, relative position coordinates generated by indoor positioning base station signals, motion state quantities and vital sign parameters transmitted by wearable devices, and temperature distribution matrix and visibility index collected by environmental scanning devices.

[0070] The positioning fusion and status labeling module calculates dynamic reliability weights for the positioning signal sources in the environmental perception data packet, performs spatiotemporal alignment compensation to generate fused positioning coordinates, and outputs associated status labels. The status labels include water safety status, underwater activity status, and equipment detachment abnormal status.

[0071] The virtual safety zone dynamic modeling module loads a preset electronic map of the water area and, in conjunction with real-time water level monitoring data, user distribution thermal data, and historical accident area markers, constructs a virtual safety zone boundary that includes elastic thresholds and scaling rules.

[0072] The location security dynamic assessment module performs spatial overlay comparison between the fused location coordinates and the virtual security zone boundary, and generates a dynamic security score based on the duration of triggering rules A, B, and C.

[0073] The multi-level linkage rescue response module activates the multi-level linkage rescue signal chain based on the gradient range of the dynamic safety score, triggering wearable device vibration alarm, sound and light alarm device activation, water surface drone dispatch, or emergency system transmission.

[0074] The above content is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, and all such modifications and additions should fall within the protection scope of the present invention.

Claims

1. A drowning prevention monitoring method based on multi-source positioning data, characterized in that, include: S1. Multi-source data acquisition of water-related environment: Acquire real-time environmental perception data packets of the user in the water-related area. The environmental perception data packets include absolute position coordinates generated by satellite positioning signals, relative position coordinates generated by indoor positioning base station signals, motion state quantities and vital sign parameters transmitted by wearable devices, and temperature distribution matrix and visibility index collected by environmental scanning devices. S2. Positioning Fusion and Status Labeling: Calculate dynamic reliability weights for the positioning signal sources in the environmental perception data packet, perform spatiotemporal alignment compensation to generate fused positioning coordinates, and output associated status labels. The status labels include water safety status, underwater activity status, and equipment detachment abnormal status. S3. Dynamic Modeling of Virtual Safety Zones: Load the preset electronic base map of the water area, combine it with real-time water level monitoring data, user distribution thermal data and historical accident area markers, and construct the boundary of the virtual safety zone, which includes elastic thresholds and scaling rules. S4. Dynamic assessment of positioning security: The fused positioning coordinates are compared with the boundary of the virtual security zone in a spatial overlay, and a dynamic security score is generated based on the duration of triggering rules A, B and C. S5. Multi-level linkage rescue response: Based on the gradient range of the dynamic safety score, activate the multi-level linkage rescue signal chain, triggering wearable device vibration alarm, sound and light alarm device activation, water surface drone dispatch or emergency system transmission.

2. The drowning prevention monitoring method based on multi-source positioning data according to claim 1, characterized in that: The specific process for outputting the associated status label is as follows: S21. Calculate dynamic reliability weights based on satellite positioning signal reception strength, indoor positioning base station line-of-sight obstruction markers, wearable device immersion depth, and visibility index. S22. Using absolute position coordinates as a reference, perform a weighted average on conflicting position data to generate fused positioning coordinates; S23. Analyze the characteristics of abrupt changes in vital sign parameters and the trends of motion state quantities, and output state labels.

3. The drowning prevention monitoring method based on multi-source positioning data according to claim 1, characterized in that: The specific process for constructing the virtual safe zone boundary, which includes elastic thresholds and scaling rules, is as follows: S31. Calculate the offset of the pool bottom boundary based on real-time water level monitoring data, and dynamically adjust the depth and shallow zoning of the electronic base map of the water area; S32. Generate user distribution thermal data based on fused positioning coordinate density to drive the expansion of the warning zone boundary; S33. Set an absolute restricted area elastic threshold based on the frequency of historical accident area markings.

4. The drowning prevention monitoring method based on multi-source positioning data according to claim 3, characterized in that: The specific method for generating user distribution thermal data based on fused positioning coordinate density is as follows: in the plane coordinate system of the water electronic base map, each grid cell is divided with a set unit area, the number of fused positioning coordinates falling into each grid cell is counted, and the ratio between the number of fused positioning coordinates in each grid cell and the area of ​​the grid cell is used as the thermal value of each grid cell.

5. The drowning prevention monitoring method based on multi-source positioning data according to claim 1, characterized in that: The triggering rules A, B, and C specifically refer to: Rule A: The fused positioning coordinates enter the absolute restricted area and the motion state quantity triggers a continuous sinking action marker; Rule B: The merged location coordinates remain within the warning zone and vital signs parameters exceed the critical rate of change; Rule C: The status label indicates an abnormal device detachment and no matching coordinate set of the shore safety zone is detected.

6. The drowning prevention monitoring method based on multi-source positioning data according to claim 5, characterized in that: The specific method for generating dynamic security scores is as follows: when rule A is triggered, the first weight score is accumulated; when rule B is triggered, the second weight score is accumulated; when rule C is triggered, the third weight score is accumulated. For concurrent rules, an overlay algorithm is used to synthesize the score signal. The third weight score is greater than the first weight score and the second weight score.

7. The drowning prevention monitoring method based on multi-source positioning data according to claim 1, characterized in that: The specific method for activating the multi-level linkage rescue signal chain is as follows: S51. When the dynamic safety score exceeds the first-level threshold, a vibration alarm signal is sent to the wearable device and a location prompt message is pushed to the management platform. S52. When the dynamic safety score exceeds the level 2 threshold, activate the audible and visual alarm device, send a rescue guidance package containing an electronic map of the water area to the lifeguard terminal, and activate the surface drone to fly to the fused positioning coordinates. S53. When the dynamic safety score exceeds the level 3 threshold, control the drainage outlet to close and the emergency lighting to focus, and generate a structured rescue request package containing vital signs parameters and water level monitoring data to be transmitted to the emergency rescue system.

8. The drowning prevention monitoring method based on multi-source positioning data according to claim 7, characterized in that: The rescue guidance package is generated by extracting vector slices centered on fused positioning coordinates from the electronic base map of the water area, and superimposing absolute no-go zone markers and real-time virtual safe zone boundaries to form the rescue guidance package.

9. A drowning prevention monitoring system based on multi-source positioning data, characterized in that, include: The multi-source data acquisition module for water-related environments acquires real-time environmental perception data packets for users in water-related areas. The environmental perception data packets include absolute position coordinates generated by satellite positioning signals, relative position coordinates generated by indoor positioning base station signals, motion state quantities and vital sign parameters transmitted by wearable devices, and temperature distribution matrix and visibility index collected by environmental scanning devices. The positioning fusion and status labeling module calculates dynamic reliability weights for the positioning signal sources in the environmental perception data packet, performs spatiotemporal alignment compensation to generate fused positioning coordinates, and outputs associated status labels, including water safety status, underwater activity status, and equipment detachment abnormal status. The virtual safety zone dynamic modeling module loads a preset electronic water map and combines it with real-time water level monitoring data, user distribution thermal data, and historical accident area markers to construct a virtual safety zone boundary that includes elastic thresholds and scaling rules. The location security dynamic assessment module performs spatial overlay comparison between the fused location coordinates and the virtual security zone boundary, and generates a dynamic security score based on the duration of triggering rules A, B and C. The multi-level linkage rescue response module activates the multi-level linkage rescue signal chain based on the gradient range of the dynamic safety score, triggering wearable device vibration alarm, sound and light alarm device activation, water surface drone dispatch or emergency system transmission.

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