Student drowning prevention method and system based on smart student card

Abstract

The present invention relates to the technical field of student safety monitoring, and more specifically, to a student drowning prevention method and system based on a smart student card, which has the advantages of simple calculation, accurate monitoring, low equipment cost and high safety and reliability. The method and system are characterized in that the method and system comprise the following steps: obtaining user location information and dangerous water boundary information; obtaining the shortest distance d, comparing the shortest distance d from the user location information to the dangerous water with a preset dangerous distance threshold d', and judging whether the wearer is in the dangerous water according to the comparison result. Compared with the prior art: (1) the drowning prevention control method provided by the present invention has high calculation efficiency, further reducing equipment cost and personnel cost; (2) based on the calculation and comparison of the wearer location data and the marked dangerous water boundary data, a circular safety area is delineated, and when the wearer moves in the safety area, it is not necessary to repeat the calculation multiple times, thereby further improving the efficiency of drowning prevention control.

Description

Technical Field

[0001] The invention relates to the technical field of student safety monitoring, and in particular to a student drowning prevention method and system based on a smart student card, which has simple calculation, accurate monitoring, low equipment cost requirement, and high safety and reliability. Background Art

[0002] In recent years, children's wearable devices have been used to track students' locations and monitor drowning prevention behaviors. For example, patent document CN109920207A discloses a method and device for reminding users to stay near water areas. The technical solution obtains user location information and water boundary data, and then determines whether the user stays near water areas based on the location information and water boundary data. If the user is determined to stay near water areas, a reminder message is sent to a preset contact. In this technical solution, water boundary data is obtained from the data of map service providers. However, my country has complex topography and changeable climate conditions. Water boundaries will change significantly during the rainy season. For map data service providers that focus on traffic information collection, it is often impossible to update water boundary data in real time, resulting in monitoring failure.

[0003] In order to further improve the reliability of near-water safety monitoring, patent document CN111275930A discloses a wearable anti-drowning device control system and method, which obtains the specific parameters of the drowning risk function by calculating the distance d between the user's position and the dangerous waters. The algorithm is relatively complex, with low computational efficiency and high requirements for transportation equipment and personnel, resulting in high equipment and labor costs. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention proposes a student drowning prevention method and system based on a smart student card, which has simple calculation, accurate monitoring, low equipment cost requirement and high safety and reliability.

[0005] The present invention is achieved by the following measures:

[0006] A method for preventing students from drowning based on a smart student card, characterized in that it comprises the following steps:

[0007] Step 1: Obtain user location information and dangerous water boundary information: The smart student card management cloud platform obtains the wearer's precise positioning point p' through the location data P uploaded by the smart student card, and the dangerous water boundary is obtained through the ordered point set P = {p 1 , p 2 ,.....p n-1 , p n}express;

[0008] Step 2: Get the shortest distance d: Calculate p' and p respectively 1 、p 2,......p n-1 、p n The line segment distances between the two are compared to obtain the shortest distance d, and the real-time width and depth of the water area are dynamically mapped and tracked to update the dangerous water area boundary data. When the dangerous water area boundary information is updated, step 1 is repeated;

[0009] Step 3: Compare the shortest distance d from the user's location information to the dangerous waters with the preset dangerous distance threshold d', and determine whether the wearer is in dangerous waters based on the comparison result. If d≤d', the wearer is in dangerous waters and an active intervention mechanism is promptly adopted for rescue. If d>d', proceed to step 4;

[0010] Step 4: Set up a safe zone and monitor the relative position of the user to the safe zone:

[0011] Step 4-1: With p' as the center and d-d' as the radius r, define the circular area D as the safe area;

[0012] Step 4-2: Continuously track the wearer, where the wearer's position will be continuously tracked and updated after the wearer moves, and the wearer's latest position information can be obtained more accurately by modifying the positioning interval. After the wearer moves, first determine the relationship between the positioning point after movement and the circular area D: compare the coordinate value p'' of the positioning point after movement with the shortest straight-line distance d'' of the center point p' and the radius r. If it is greater than r, it exceeds the circular safety area D and re-enters step 1. If d''≤r, the user is in the circular area D and repeats step 4-2.

[0013] In step 3 of the present invention, the threshold d' is set to 10 meters.

[0014] The real-time width and depth of the water area described in step 2 of the present invention are dynamically mapped based on the characteristics of sudden changes in the surface spectrum caused by reservoir water storage, and the time series remote sensing mutation detection algorithm (BFAST: the full name is BreaksFor Additive Season and Trend, which automatically decomposes the time series into trend terms, seasonal terms and residual terms by detecting jump points, thereby dynamically predicting water area changes) is used to extract the spatial and temporal distribution of surface MODIS NDVI / NDWI time series mutations, and combine medium and high resolution images with digital elevation models to extract the spatiotemporal parameters of the reservoir. An automatic identification and cataloging method for newly built reservoirs integrating high time-frequency remote sensing image sequences and high spatial resolution images is developed, as follows:

[0015] Step 2-1: According to the noise level and seasonal term amplitude in the GPS time series, simulate the GPS time series, add jump points of different magnitudes at different locations, and the BFAST (Breaks For Additive Season and Trend) algorithm automatically decomposes the time series into trend terms, seasonal terms and residual terms through the jump points, fitted linear trend terms and seasonal terms in the GPS time series, so as to realize the dynamic prediction of water area changes;

[0016] Step 2-2: Use the surface reflectance of the first band and the second band of MODIS data to form the normalized value vegetation index to extract water bodies from the MODIS image. The calculation formula is: NDVI =(R CH2 -R CH1 ) / (R CH2 +R CH1 ), where R CH1 is the surface reflectance of the first band of MODIS data, R CH2 is the surface reflectance of the second band of MODIS data. In the generated NDVI image, the I NDVI The value is negative, while the I of vegetation and soil NDVI The value is higher and positive, which makes it easy to distinguish water bodies from vegetation and soil;

[0017] Step 2-3: Combine medium- and high-resolution images with digital elevation models to extract spatiotemporal parameters of the reservoir;

[0018] Step 2-4: Based on the above-mentioned automated detection, we selected river basins with densely distributed reservoirs and high artificial storage intensity, established a spatiotemporal catalog of reservoirs, integrated remote sensing, digital terrain analysis and GIS spatial analysis methods, quantified the water storage and regulation capacity of reservoirs of different sizes at the river basin scale, and their temporal characteristics at the interannual and seasonal scales, dynamically quantified and updated the water area with high precision, and based on the dynamic mapping results, the drone collected an ordered point set P'' each time it flew, replacing the ordered point set P of the original water area.

[0019] The user location information in the present invention includes GPS positioning information, WiFi positioning information or UWB positioning information uploaded by the smart student card.

[0020] The active intervention mechanism described in step 3 of the present invention includes: the smart student card management cloud platform notifies the preset contact of the electronic student card through SMS or APP, the smart student card management cloud platform controls the smart student card to automatically dial the preset number and cyclically dial each preset number until the preset contact answers, informs the smart student card wearer to stay away from dangerous waters, or pushes the rescue request to the nearby emergency management department to request manual rescue.

[0021] In step 4-2 of the present invention, after the wearer moves, the wearer's position will be continuously tracked and reported for update, and the wearer's latest position information can be more accurately obtained by modifying the positioning interval. Specifically: the smart student card platform determines the distance to the dangerous waters based on the positioning information reported by the smart student card. When it is less than or equal to 100 meters, the positioning interval is modified to less than 2 minutes; when it is greater than 100 meters, the positioning interval is modified to 2-10 minutes. The positioning interval data will establish a data path with the smart student card through the communication module, and notify the terminal to modify the positioning data reporting interval. After the setting is successful, the smart student card will report the positioning data according to the interval set by the user.

[0022] A system for running the above-mentioned drowning prevention control method based on a smart student card, characterized in that it includes a smart student card management cloud platform and at least one smart student card, wherein:

[0023] The smart student card is provided with a main controller and voice input and output modules, a positioning chip and a wireless communication module respectively connected to the main controller, wherein the wireless communication module is used to communicate with the smart student card management cloud platform, wherein the voice input and output module is used to make calls with a preset number, and the positioning chip is a GPS positioning chip or a WiFi positioning chip or a UWB positioning circuit;

[0024] The smart student card management cloud platform is provided with a main control module and a communication module, a positioning data processing module, a management module and a personnel information module respectively connected to the main control module. The communication module establishes a data path with the smart student card to complete the data push to the smart student card, including SMS or APP notification push, the initiation of the smart student card to automatically dial a preset number or the sending of a rescue request; the positioning data processing module is used to convert the base station information, WIFI information, GPS data information or UWB positioning data reported by the smart student card into Gaode longitude and latitude and detailed location data, and deduplicate the same longitude and latitude points to The smart student card wearer is accurately positioned; the management module is used to complete the number preset of the smart student card, the marking of the dangerous water boundary data and the setting of the safe area; the personnel information module is used to manage and store personnel information data; after the communication module establishes communication with the smart student card, it receives the positioning data uploaded by the smart student card and sends the positioning data to the positioning data processing module, the precise position information of the smart student card obtained by the positioning data processing module is sent to the management module, and the management module combines the obtained precise position information of the smart student card with the dangerous water boundary information to execute the above-mentioned anti-drowning method based on the smart student card.

[0025] The management module of the present invention is provided with a dangerous water area boundary information acquisition module, and the dangerous water area boundary information acquisition module is provided with a dangerous water area boundary information dynamic update module, and the dangerous water area boundary information dynamic update module executes the data update means of the above step 2.

[0026] Compared with the prior art, the present invention: (1) The anti-drowning control method provided by the present invention is relatively simple and has high computational efficiency, thereby improving the prevention efficiency of drowning and greatly improving safety, and has low requirements on equipment and personnel, thereby further reducing equipment costs and personnel costs; (2) Based on the calculation and comparison of the wearer's position data and the marked dangerous water boundary data, a circular safe area is delineated. When the wearer moves in the safe area, it is not necessary to repeat the calculation multiple times, thereby further improving the efficiency of anti-drowning control. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Attached Figure 1 It is a flow chart of the present invention.

[0028] Attached Figure 2 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0029] The present invention will be further described below in conjunction with the accompanying drawings and embodiments. Example

[0030] This example provides a student drowning prevention method based on a smart student card, including the following steps:

[0031] Step 1: Obtain user location information and dangerous water boundary information: The smart student card management cloud platform obtains the wearer's precise positioning point p' through the location data P uploaded by the smart student card, and the dangerous water boundary is obtained through the ordered point set P = {p 1 , p 2 ,.....p n-1 , p n} indicates that the user location information includes GPS location information, WiFi location information or UWB location information uploaded by the smart student card;

[0032] Step 2: Get the shortest distance d: Calculate p' and p respectively 1 、p 2 ,......p n-1 、p n The line segment distances between the two are compared to obtain the shortest distance d, and the real-time width and depth of the water area are dynamically mapped and tracked to update the dangerous water area boundary data. When the dangerous water area boundary information is updated, step 1 is repeated;

[0033] The real-time dynamic mapping of the width and depth of the water area is specifically based on the characteristics of the sudden change of the surface spectrum caused by the water storage of the reservoir, and the time series remote sensing mutation detection algorithm (BFAST: the full name is Breaks For Additive Season and Trend, which automatically decomposes the time series into trend terms, seasonal terms and residual terms by detecting jump points, so as to dynamically predict the changes in the water area) is used to extract the spatial and temporal distribution of the surface MODIS NDVI / NDWI time series mutations, and combine medium and high resolution images with digital elevation models to extract the spatiotemporal parameters of the reservoir. The automatic identification and cataloging method of newly built reservoirs integrating high time-frequency remote sensing image sequences and high spatial resolution images is developed, as follows:

[0034] Step 2-1: According to the noise level and seasonal term amplitude in the GPS time series, simulate the GPS time series, add jump points of different magnitudes at different locations, and the BFAST (Breaks For Additive Season and Trend) algorithm automatically decomposes the time series into trend terms, seasonal terms and residual terms through the jump points, fitted linear trend terms and seasonal terms in the GPS time series, so as to realize the dynamic prediction of water area changes;

[0035] Step 2-2: Use the surface reflectance of the first band and the second band of MODIS data to form the normalized value vegetation index to extract water bodies from the MODIS image. The calculation formula is: NDVI =(R CH2 -R CH1 ) / (R CH2 +R CH1 ), where R CH1 is the surface reflectance of the first band of MODIS data, R CH2 is the surface reflectance of the second band of MODIS data. In the generated NDVI image, the I NDVI The value is negative, while the I of vegetation and soil NDVI The value is higher, usually positive, which makes it easy to distinguish water bodies from vegetation and soil;

[0036] Step 2-3: Combine medium- and high-resolution images with digital elevation models to extract spatiotemporal parameters of the reservoir;

[0037] Step 2-4: Based on the above-mentioned automated detection, we selected river basins with dense reservoir distribution and high artificial regulation intensity, established a spatiotemporal catalog of reservoirs, integrated remote sensing, digital terrain analysis and GIS spatial analysis methods, quantified the water storage and regulation capacity of reservoirs of different sizes at the river basin scale, and their temporal characteristics at the interannual and seasonal scales, dynamically quantified and updated the water area with high precision, and based on the dynamic mapping results, the drone collected an ordered point set P'' each time it flew, replacing the ordered point set P of the original water area;

[0038] Step 3: Compare the shortest distance d from the user's location information to the dangerous waters with the preset dangerous distance threshold d', where the threshold d'=10 meters. Determine whether the wearer is in dangerous waters based on the comparison result. If d≤d', the wearer is in dangerous waters and adopts an active intervention mechanism for rescue in a timely manner. If d>d', proceed to step 4.

[0039] Step 4: Set up a safe zone and monitor the relative position of the user to the safe zone:

[0040] Step 4-1: With p' as the center and d-d' as the radius r, define the circular area D as the safe area;

[0041] Step 4-2: Continuously track the wearer, where the wearer's position will be continuously tracked and updated after the wearer moves, and the wearer's latest position information can be obtained more accurately by modifying the positioning interval. After the wearer moves, first determine the relationship between the positioning point after movement and the circular area D: compare the coordinate value p'' of the positioning point after movement with the shortest straight-line distance d'' of the center point p' and the radius r. If it is greater than r, it exceeds the circular safety area D and re-enters step 1. If d''≤r, the user is in the circular area D and repeats step 4-2.

[0042] The active intervention mechanism described in step 3 in this example includes: the smart student card management cloud platform notifies the preset contact of the electronic student card through SMS or APP, the smart student card management cloud platform controls the smart student card to automatically dial the preset number and cyclically dial each preset number until the preset contact answers, informing the smart student card wearer to stay away from dangerous waters, or pushing the rescue request to the nearby emergency management department to request manual rescue;

[0043] In step 4-2 of the present invention, after the wearer moves, the wearer's position will be continuously tracked and reported for update, and the wearer's latest position information can be more accurately obtained by modifying the positioning interval. Specifically: the smart student card platform determines the distance to the dangerous waters based on the positioning information reported by the smart student card. When it is less than or equal to 100 meters, the positioning interval is modified to less than 2 minutes; when it is greater than 100 meters, the positioning interval is modified to 2-10 minutes. The positioning interval data will establish a data path with the smart student card through the communication module, and notify the terminal to modify the positioning data reporting interval. After the setting is successful, the smart student card will report the positioning data according to the interval set by the user. Example

[0044] This example provides a student drowning prevention system based on smart student cards, in which a smart student card management cloud platform as described in Example 1 and more than two smart student cards are provided. When more than two smart student cards report multiple data in parallel, the smart student card management cloud platform adopts a load balancing configuration multi-node strategy to disperse data pressure, and uses a message queue to queue and execute large amounts of data in sequence;

[0045] When there is a large amount of traffic, load balancing can be used to distribute multiple requests to multiple servers, which is equivalent to handing over the load that one server needs to bear to multiple servers to handle, thereby improving the system's throughput. In addition, if one of the servers fails, other servers can still provide services normally, thereby improving the scalability and reliability of the system.

[0046] The smart student card management platform has Core (core module), Handlers (processor module), Filters (filter module), and Proxies (proxy module); when working, it performs the following operations:

[0047] A. HTTP request is received.

[0048] B.Nginx selects an appropriate handler based on the location in the configuration file.

[0049] C. The Handlers module needs to reverse proxy the request to the backend server, so it needs to become another type of module: load-balancers (load balancing module).

[0050] D. The load balancing module is configured with a set of backend servers. When an HTTP request comes in, it decides which server should receive the request.

[0051] E. After processing is complete, filters are called. Each request can be compressed into blocks and passed through multiple filters in sequence. The order of their execution is determined at compile time. The filter chain efficiently sends responses to the client in a pipeline manner. Each filter will not wait for the previous filter to complete, just like an assembly line.

[0052] F. Finally, send the response to the client, which is the electronic student card.

[0053] Compared with the prior art, the present invention: (1) The anti-drowning control method provided by the present invention is relatively simple and has high computational efficiency, thereby improving the prevention efficiency of drowning and greatly improving safety, and has low requirements on equipment and personnel, thereby further reducing equipment costs and personnel costs; (2) Based on the calculation and comparison of the wearer's position data and the marked dangerous water boundary data, a circular safe area is delineated. When the wearer moves in the safe area, it is not necessary to repeat the calculation multiple times, thereby further improving the efficiency of anti-drowning control.

Claims

1. A method for preventing students from drowning based on smart student cards, characterized in that: The following steps are involved: Step 1: Obtain user location information and dangerous water boundary information: The smart student card management cloud platform obtains the wearer's precise positioning point p' through the location data P uploaded by the smart student card, and the dangerous water boundary is obtained through the ordered point set P = {p 1 , p 2 ,.....p n-1 , p n }express; Step 2: Get the shortest distance d: Calculate p' and p respectively 1 、p 2 ,......p n-1 、p n The line segment distances between the two are compared to obtain the shortest distance d, and the real-time width and depth of the water area are dynamically mapped and tracked to update the dangerous water area boundary data. When the dangerous water area boundary information is updated, step 1 is repeated; Step 3: Compare the shortest distance d from the user's location information to the dangerous waters with the preset dangerous distance threshold d', and determine whether the wearer is in dangerous waters based on the comparison result. If d≤d', the wearer is in dangerous waters and an active intervention mechanism is promptly adopted for rescue. If d>d', proceed to step 4; Step 4: Set up a safe zone and monitor the relative position of the user to the safe zone: Step 4-1: With p' as the center and d-d' as the radius r, define the circular area D as the safe area; Step 4-2: Continuously track the wearer, wherein the wearer's position will be continuously tracked and updated after the wearer moves, and the wearer's latest position information can be obtained more accurately by modifying the positioning interval. The positioning interval data will establish a data channel with the smart student card through the communication module, and notify the terminal to modify the positioning data reporting interval. After the setting is successful, the smart student card will report the positioning data according to the interval set by the user; after the wearer moves, first determine the relationship between the positioning point after movement and the circular area D: compare the coordinate value p" of the positioning point after movement with the shortest straight-line distance d" of the center point p' and the radius r. If it is greater than r, it exceeds the circular safety area D and re-enters step 1. If d"≤r, the user is in the circular area D and repeats step 4-2.

2. A method for preventing students from drowning based on a smart student card according to claim 1, characterized in that: The real-time width and depth of the water area described in step 2 are dynamically mapped based on the characteristics of the sudden change of the surface spectrum caused by the reservoir water storage. The time series remote sensing mutation detection algorithm is used to extract the spatial and temporal distribution of the surface MODIS NDVI / NDWI time series mutation, and the spatiotemporal parameters of the reservoir are extracted by combining medium and high resolution images with digital elevation models. The automatic identification and cataloging method of newly built reservoirs integrating high time-frequency remote sensing image sequences and high spatial resolution images is developed as follows: Step 2-1: According to the noise level and seasonal term amplitude in the GPS time series, the GPS time series is simulated, and jump points of different magnitudes are added at different locations. The BFAST (Breaks For Additive Season and Trend) algorithm automatically decomposes the time series into trend terms, seasonal terms and residual terms through the jump points in the GPS time series, the fitted linear trend terms and seasonal terms, and realizes the dynamic prediction of water area changes; Step 2-2: The surface reflectance of the first band and the second band of the MODIS data is used to form the normalized value vegetation index to extract water bodies from the MODIS image. The calculation formula is: I NDVI =(R CH2 -R CH1 ) / (R CH2 +R CH1 ), where R CH1 is the surface reflectance of the first band of MODIS data, R CH2 is the surface reflectance of the second band of MODIS data. In the generated NDVI image, the I NDVI The value is negative, while the I of vegetation and soil NDVI The value is higher, usually positive, which makes it easy to distinguish water bodies from vegetation and soil; Step 2-3: Combine medium- and high-resolution images with digital elevation models to extract spatiotemporal parameters of the reservoir; Step 2-4: Based on the above-mentioned automated detection, we selected river basins with dense reservoir distribution and high artificial storage intensity, established a spatiotemporal catalog of reservoirs, integrated remote sensing, digital terrain analysis and GIS spatial analysis methods, quantified the water storage and regulation capacity of reservoirs of different sizes at the river basin scale, and their temporal characteristics at the interannual and seasonal scales, dynamically quantified and updated the water area with high precision, and based on the dynamic mapping results, the drone collected an ordered point set P" each time it flew, replacing the ordered point set P of the original water area.

3. A method for preventing students from drowning based on a smart student card according to claim 2, characterized in that: User location information includes GPS location information, WiFi location information or UWB location information uploaded by the smart student card.

4. A method for preventing students from drowning based on a smart student card according to claim 3, characterized in that: The active intervention mechanism described in step 3 includes: the smart student card management cloud platform notifies the preset contact of the electronic student card via SMS or APP, the smart student card management cloud platform controls the smart student card to automatically dial the preset number and cyclically dial each preset number until the preset contact answers, informs the smart student card wearer to stay away from dangerous waters, or pushes the rescue request to the nearby emergency management department to request manual rescue.

5. A system for running the anti-drowning control method based on a smart student card as claimed in any one of claims 1 to 4, characterized in that: It includes a smart student card management cloud platform and at least one smart student card, wherein: The smart student card is provided with a main controller and voice input and output modules, a positioning chip and a wireless communication module respectively connected to the main controller, wherein the wireless communication module is used to communicate with the smart student card management cloud platform, wherein the voice input and output module is used to make calls with a preset number, and the positioning chip is a GPS positioning chip or a WiFi positioning chip or a UWB positioning circuit; The smart student card management cloud platform is provided with a main control module and a communication module, a positioning data processing module, a management module and a personnel information module respectively connected to the main control module. The communication module establishes a data path with the smart student card to complete the data push to the smart student card, including SMS or APP notification push, the initiation of the smart student card to automatically dial a preset number or the sending of a rescue request; the positioning data processing module is used to convert the base station information, WIFI information, GPS data information or UWB positioning data reported by the smart student card into Gaode longitude and latitude and detailed location data, and deduplicate the points with the same longitude and latitude. To achieve precise positioning of the wearer of the smart student card; the management module is used to complete the number preset of the smart student card, the marking of the dangerous water boundary data and the setting of the safe area; the personnel information module is used to manage and store personnel information data; after the communication module establishes communication with the smart student card, it receives the positioning data uploaded by the smart student card, and sends the positioning data to the positioning data processing module, and the precise position information of the smart student card obtained by the positioning data processing module is sent to the management module, and the management module combines the obtained precise position information of the smart student card with the dangerous water boundary information to execute the drowning prevention method based on the smart student card.

6. The system of the drowning prevention control method based on smart student card according to claim 5, characterized in that: The management module is provided with a dangerous water area boundary information acquisition module, and the dangerous water area boundary information acquisition module is provided with a dangerous water area boundary information dynamic update module, and the dangerous water area boundary information dynamic update module executes the data update means of the above step 2.

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