Beacon signal transmission pattern optimization system and method

Abstract

The application discloses a kind of position mark signal transmission mode optimization system and method, it is related to intelligent position mark technical field, position mark signal transmission mode optimization system mainly includes data acquisition module, pre-processing module, decision engine module, execution control module and power management module;Data acquisition module is used to collect electric quantity index, the life sign value of personnel falling into water, ship automatic identification system data and global positioning system data;Pre-processing module is used to carry out noise suppression and data standardization to the data collected, output normalization vector;Decision engine module is used to select communication mode, transmission frequency and transmission information content according to the normalization vector;Execution control module is used to carry out signal scheduling and transmission control;Power management module is used to carry out power consumption dynamic regulation and control.The position mark signal transmission mode optimization system and method provided by the application can prolong the endurance of the position mark and efficiently output the rescue signal.

Description

Technical Field

[0001] This invention relates to the field of intelligent beacon technology, and more specifically, to a beacon signal transmission mode optimization system and method. Background Technology

[0002] With the rapid development of global marine economic activities, maritime accidents are frequent, making the continuous and accurate location of people in the water crucial for the success of search and rescue operations. Previously, the positioning buoys worn by people in the water typically transmitted signals at fixed frequencies and in fixed ways, and were one-way communication devices. This resulted in short buoy endurance, low efficiency, and the inability of the person in the water to receive feedback, hindering rescue efforts during prolonged operations. Therefore, there is an urgent need for an intelligent dynamic optimization model algorithm for transmission frequency and communication methods, incorporating two-way communication to extend the buoy's endurance and efficiently output rescue signals. This would ensure that the rescue center is aware of the emergency while reducing the psychological burden on the person in the water, providing more comprehensive and longer-lasting support for successful search and rescue operations. Summary of the Invention

[0003] The purpose of this invention is to provide a system and method for optimizing the signal transmission mode of a position beacon, which can extend the range of the position beacon and efficiently output rescue signals.

[0004] This invention provides a system for optimizing the transmission mode of a position beacon signal, comprising a data acquisition module, a preprocessing module, a decision engine module, an execution control module, and a power management module; The data acquisition module is used to collect data on power index, vital signs of people who have fallen into the water, data from the Automatic Identification System (AIS) and the Global Positioning System (GPS). The preprocessing module is used to suppress noise and standardize the collected data, and output a normalized vector. The decision engine module is used to select the communication method, transmission frequency, and transmission information content based on the normalized vector; The execution control module is used for signal scheduling and transmission control; The power management module is used for dynamic power consumption control.

[0005] Furthermore, the preprocessing module is configured to: perform Kalman filtering on the collected data to remove noise; standardize the noise-removed data to the [0,1] interval; estimate the ocean current trend based on coordinates and time; and determine the environmental friendliness based on the Automatic Identification System (AIS) data.

[0006] Furthermore, the normalized vector includes normalized values ​​for vital sign intensity, electrical charge, time of fall into water, distance from rescue, and AIS environmental friendliness.

[0007] Furthermore, the decision engine module is configured as follows: If the vital signs of the person who fell into the water are confirmed to be weak, give them the highest priority and activate emergency frequency and multi-channel synchronous broadcasting. The vital signs of the person who fell into the water have been confirmed to be normal. Once the normalized power value is confirmed to be less than the preset power threshold, the low-frequency transmission frequency is activated. If the time of falling into the water is confirmed to be greater than the preset time of falling into the water, or the rescue distance is greater than the preset rescue distance, the intermediate frequency transmission frequency will be activated. Calculate the overall priority score based on the normalized vector; Different transmission frequencies are activated based on the comprehensive priority score.

[0008] Furthermore, the formula for calculating the overall priority score is as follows: Priority Score=w1·(1-L)+w2·(1 B)+w3·T+w4·D w5·E, Among them, PriorityScore is the overall priority score; L is the normalized value of vital signs intensity; B is the normalized value of battery power; T is the normalized value of time in the water; D is the normalized value of distance from rescue; E is the AIS environmental friendliness; w1, w2, w3, w4 and w5 are weighting coefficients.

[0009] Furthermore, the method for initiating different transmission frequencies based on the comprehensive priority score is as follows: When the overall priority score is greater than 0.8, the emergency frequency is activated; When the overall priority score is 0.6~0.8, the high-frequency transmission frequency is activated; When the overall priority score is between 0.4 and 0.6, the intermediate frequency transmission frequency is activated; When the overall priority score is less than 0.4, the low-frequency transmission frequency is activated.

[0010] Furthermore, the decision engine module is also configured as follows: Confirm that at least three nearby vessels are using AIS communication. After confirming that the message was successfully sent and receiving a reply from the rescue platform, reduce the sending frequency; After confirming that the rescue personnel are gradually approaching, increase the frequency of sending location information.

[0011] Furthermore, the decision engine module is also configured as follows: Once the battery level is confirmed to be ≥80%, the Automatic Identification System (AIS) is activated to transmit at high frequency, and a standard distress message is continuously broadcast. The GPS is activated to continuously track the ship and report its location once at regular intervals. If the battery level is confirmed to be between 80% and 30%, activate the Automatic Identification System (AIS) by broadcasting at a reduced frequency once or by using a carrier listening strategy. This means remaining silent during normal times, but immediately increasing the transmission frequency when an AIS signal is detected nearby. Switch the GPS to periodic inspection and reporting of the location once and disable continuous tracking mode, using single positioning and single transmission instead. Once the battery level is confirmed to be 10% ≤ 30%, the Automatic Identification System (AIS) is turned off, and the Global Positioning System (GPS) is activated using a combination of periodic and trigger modes. Specifically, the frequency is adjusted to wake up and send coordinates every 1-3 hours, and to wake up and send a message immediately when vital signs show extreme abnormalities. Once the battery level is confirmed to be less than 10%, switch the transmission mode to heartbeat mode, which sets the frequency to an extremely low value and transmits once every 8 hours.

[0012] Furthermore, the system is also equipped with a BeiDou short message communication module. Upon receiving a response from search and rescue personnel, this module provides voice prompts, sends location and vital signs information, receives search and rescue information, and obtains rescue feedback. Specifically, in standby mode, it sends a short message containing its own ID and status to the BeiDou satellite every 1-3 hours; upon activation of the personnel-in-water beacon, it immediately initiates BeiDou high-precision positioning to obtain accurate coordinates better than 10 meters, while simultaneously sending a standard distress message; it continuously sends distress messages every 1-5 minutes, waiting for the rescue center to receive the alarm and then sending a confirmation message to the beacon via BeiDou satellite; it sends the beacon's real-time location and trajectory to nearby rescue vessels via short messages, and sends more detailed information to the rescue vessels via AIS; and it receives commands from approaching rescue personnel to disable the alarm or switch to beacon mode and cease operation.

[0013] The present invention also provides a method for optimizing the transmission mode of a position beacon signal, which optimizes the transmission mode of the position beacon signal using the above-mentioned position beacon signal transmission mode optimization system.

[0014] The system and method for optimizing the transmission mode of a position indicator signal provided by this invention have the following beneficial effects: This invention employs an algorithm for intelligent dynamic optimization of the signal transmission mode and introduces a two-way communication function, extending the range of the position beacon and efficiently outputting rescue signals. This ensures that the rescue center is aware of the danger while reducing the psychological burden on the person who has fallen into the water, providing more comprehensive and longer-lasting support for successful search and rescue.

[0015] The core innovation of this invention lies not in the improvement of a single module or the fact that the various technical modules are not simply superimposed, but in the construction of a closed-loop, adaptive, system-level optimized intelligent launch control system, which forms a close synergistic relationship between data flow and control flow. First, a real-time closed loop and dynamic balance between perception, decision-making, and execution: The system coordinates "multi-dimensional" data acquisition with "precise" preprocessing. It not only collects state of charge (SOC) data but also simultaneously acquires vital signs of the person in the water, AIS environmental data, and GPS / BeiDou positioning. The preprocessing module eliminates sensor noise through Kalman filtering and uses coordinate and time information to estimate ocean current trends and quantify AIS environmental friendliness. This transforms the raw data into a normalized vector containing vital sign strength, SOC, time of fall into the water, rescue distance, and environmental friendliness. This process provides the decision engine with a high signal-to-noise ratio and clearly defined physical meaning, forming the cornerstone of all subsequent intelligent decisions. Without this high-quality fusion perception, decision-making would be unsustainable. The decision engine is driven by both "rules" and "models." It does not rely on a single algorithm. On one hand, it follows hard priority rules such as "vital signs first" (e.g., immediately forcing entry into emergency mode if vital signs are weak) to ensure absolute reliability in critical moments. On the other hand, under normal conditions, it runs a lightweight weighted linear scoring model (Priority). Score = w1·(1-L) + w2·(1 B)+w3·T+w4·D w5·E), mapping multidimensional normalized vectors to a comprehensive priority score, and smoothly switching transmission frequency levels accordingly. This hybrid architecture of "rule-based safety and model optimization" ensures security while achieving refined and adaptive strategies. The "linked optimization" of execution control and power management involves the execution control module dynamically scheduling the working status (transmit / silent, frequency, power) of multiple radio frequency units such as AIS, BeiDou short message, and VHF according to the instructions of the decision engine, while the power management module monitors and coordinates throughout the process. When the decision is to select high-frequency transmission, the power management ensures energy supply at peak power consumption; when the decision is to select low frequency or silence, the power management initiates strategies such as deep sleep and dynamic voltage-frequency regulation (DVFS) to reduce the average power consumption of the system to the extreme. This linkage ensures that "intelligent transmission decision" truly translates into "effective extended endurance," avoiding strategy failure due to excessive decision power consumption. Secondly, intelligent switching and complementarity between near-field (AIS) and far-field (BeiDou) communication: based on environmental awareness, the system uses the AIS receiver to perceive the number of surrounding ships in real time. The decision engine prioritizes AIS / VHF intermediate frequency broadcast when at least three nearby vessels are detected, leveraging its high real-time performance within line of sight to instantly detect nearby vessels and shore base stations. When AIS environmental friendliness is low (no vessels) or the rescue distance is far, it seamlessly switches to the BeiDou short message satellite link, overcoming line-of-sight limitations and reporting distress information to rescue coordination centers hundreds or even thousands of kilometers away. The clever energy-saving "carrier listening" strategy is effective when battery power is moderate (80%-30%) and the AIS environment is unclear. The system employs a "carrier listening" strategy, where the AIS remains silent to conserve power, but immediately increases its transmission frequency once an AIS signal is detected nearby (i.e., a ship appears). This strategy achieves "on-demand transmission," significantly reducing the basic and transmission power consumption of the AIS module when no ships are passing by, while ensuring timely acquisition when ships are present. It is a model of energy-saving and effective synergy in near-field communication. Thirdly, it integrates local intelligence (edge ​​AI) with cloud collaboration (search and rescue platform): local real-time decision-making, lightweight AI models (such as TensorFlow Lite deployed on the MCU) achieve millisecond-level inference at the beacon, and adjust the transmission strategy in real time based on local sensor data to cope with the ever-changing maritime environment without relying on a continuous network connection.Remote cloud-based control, via the BeiDou short message bidirectional channel, allows the search and rescue platform to send mode commands (such as MODE_URGENT emergency mode, MODE_TRACKING tracking mode, and MODE_HOMING homing mode) to the positioning beacon. The platform then optimizes the beacon's transmission frequency and information content based on the search and rescue progress (wide-area search, close-range tracking, visual homing), transforming the beacon from a "passive broadcast source" into an "interactive search and rescue node." This "edge-cloud collaboration" upgrades single-point intelligence to systemic intelligence, significantly improving the efficiency of the entire search and rescue network.

[0016] This invention not only solves known problems but also produces some remarkable technical effects that exceed conventional expectations and even counterintuitive ones through system design. Firstly, it achieves "irrational" energy allocation under the principle of "absolute priority of vital signs"—maximizing the probability of survival: Under traditional energy-saving logic, when the battery level is extremely low (<10%), the system should enter a "heartbeat mode" with the lowest power consumption to extend the final survival time. However, this invention stipulates that even if the battery level is <10%, once vital signs are determined to be "weak," an emergency frequency will still be forcibly activated for full-channel broadcasting until it is exhausted. This seemingly "irrational" power consumption behavior has the core objective of striving for the possibility of being discovered at all costs in the final moments of life-threatening situations. It completely prioritizes "saving lives" over the secondary objective of "extending equipment operating time." This is an engineering implementation based on the highest principle of life value, producing an unexpected yet reasonable life-saving effect of "a last-ditch effort, seeking survival from the brink of death." Secondly, the shift from "one-way broadcasting" to "two-way interaction" brings about a psychological and search and rescue paradigm change: Traditional beacons are purely "black box" transmitters; those in the water have no idea whether a signal has been sent or whether rescue has been initiated, easily leading to despair. This invention achieves two-way communication through BeiDou short messages. For those in the water, receiving a "confirmed receipt" feedback message from the search and rescue center via BeiDou satellite, or a voice prompt from rescuers, greatly alleviates their panic and helplessness. A stable psychological state is crucial for maintaining vital signs. This is not only a technical function but also a humanistic concern. For the search and rescue system, the platform can proactively inquire about vital signs and issue instructions (such as "switch to beacon mode" to stop the alarm), achieving controllable, visual, and interactive management of the distressed target. This completely changes the previous "blind search, one-way reception" search and rescue model, ushering in a new paradigm of "precise command and collaborative interaction." Third, "environmental friendliness" is used as a negative weighting factor to achieve precise allocation of communication resources: When calculating the comprehensive priority score, AIS environmental friendliness (E) is introduced with a negative weight (-w5), meaning that the more ships in the vicinity, the lower the comprehensive score. This seemingly counterintuitive design has a deeper logic: when there are many nearby ships (high E value), the success probability of near-field AIS communication is already very high, and the system can "confidently" reduce its dependence on long-range satellite channels, thus reserving valuable power for more critical long-range reporting or vital sign monitoring; conversely, in isolated island areas (low E value), the priority of satellite channels must be increased. This achieves "on-demand allocation" and "dynamic relocation" of communication resources, avoiding the waste of power caused by "over-transmission" in densely populated ship areas and the decrease in detection probability caused by "under-transmission" in isolated island areas.Fourthly, the "reverse mode control of the search and rescue platform" integrates the beacon into a dynamically optimized search and rescue closed loop: This invention not only optimizes the beacon's own transmission but also incorporates the search and rescue platform's behavior into the decision-making cycle. The platform can proactively issue mode commands based on the search phase (wide-area, short-range, visual), forcing the beacon to change its behavior. This forms a positive feedback closed loop of "beacon reporting position → platform narrowing the range → platform issuing more refined commands → beacon improving reporting accuracy / frequency." Search and rescue efficiency no longer depends on the beacon's "blind" transmission but is dynamically scheduled and optimized by the platform based on global information, realizing the transformation from "people searching for signals" to "signals cooperating with people to find signals," greatly improving the positioning efficiency in the last few nautical miles of critical areas.

[0017] In summary, this invention achieves a fundamental innovation over the traditional fixed, unidirectional, and inefficient transmission mode of position beacons through the deep integration of multi-source data fusion, intelligent dynamic decision-making engine, multimodal communication collaboration, and refined power management. The core beneficial effects of this invention stem from the deep system integration of five technological pillars: intelligent perception, dynamic decision-making, collaborative communication, refined management, and bidirectional interaction. It not only significantly improves direct indicators such as extended endurance and increased detection probability, but also, through disruptive bidirectional interaction, cloud-based collaborative control, extreme scenario fault tolerance, and environmentally-aware resource optimization allocation, upgrades maritime personal distress safety equipment from a passive, isolated, and inefficient alarm device into an active, interconnected, and intelligent search and rescue collaborative node, fundamentally improving the success rate of search and rescue for people falling overboard at sea and increasing the chances of survival for those in the water. Attached Figure Description

[0018] The present invention will be further described below with reference to the accompanying drawings and embodiments. In the accompanying drawings: Figure 1 This is a block diagram of the position beacon signal transmission mode optimization system provided by the present invention. Detailed Implementation

[0019] To provide a clearer understanding of the technical features, objectives, and effects of the present invention, specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0020] Figure 1 A schematic diagram of the position beacon signal transmission mode optimization system of this embodiment is shown. In this embodiment, the position beacon signal transmission mode optimization system includes a data acquisition module, a preprocessing module, a decision engine module, an execution control module, and a power management module; The data acquisition module is used to collect data on power index, vital signs of people who have fallen into the water, data from the Automatic Identification System (AIS) and the Global Positioning System (GPS). The preprocessing module is used to suppress noise and standardize the collected data, and output a normalized vector. The decision engine module is used to select the communication method, transmission frequency, and transmission information content based on the normalized vector; The execution control module is used for signal scheduling and transmission control; The power management module is used for dynamic power consumption control.

[0021] In one exemplary embodiment, the preprocessing module is configured to: perform Kalman filtering on the collected data to remove noise; normalize the noise-removed data to the [0,1] interval; estimate the ocean current trend based on coordinates and time; and determine the environmental friendliness based on the Automatic Identification System (AIS) data.

[0022] In one exemplary embodiment, the normalized vector includes normalized values ​​for vital signs intensity, battery level, time in the water, distance to rescue, and AIS environmental friendliness.

[0023] In one exemplary embodiment, the decision engine module is configured as follows: If the vital signs of the person who fell into the water are confirmed to be weak, give them the highest priority and activate emergency frequency and multi-channel synchronous broadcasting. The vital signs of the person who fell into the water have been confirmed to be normal. Once the normalized power value is confirmed to be less than the preset power threshold, the low-frequency transmission frequency is activated. If the time of falling into the water is confirmed to be greater than the preset time of falling into the water, or the rescue distance is greater than the preset rescue distance, the intermediate frequency transmission frequency will be activated. Calculate the overall priority score based on the normalized vector; Different transmission frequencies are activated based on the comprehensive priority score.

[0024] In one exemplary embodiment, the formula for calculating the comprehensive priority score is as follows: Priority Score=w1·(1-L)+w2·(1 B)+w3·T+w4·D w5·E, Among them, PriorityScore is the overall priority score; L is the normalized value of vital signs intensity; B is the normalized value of battery power; T is the normalized value of time in the water; D is the normalized value of distance from rescue; E is the AIS environmental friendliness; w1, w2, w3, w4 and w5 are weighting coefficients.

[0025] In one exemplary embodiment, the method for initiating different transmission frequencies based on the comprehensive priority score is as follows: When the overall priority score is greater than 0.8, the emergency frequency is activated; When the overall priority score is 0.6~0.8, the high-frequency transmission frequency is activated; When the overall priority score is between 0.4 and 0.6, the intermediate frequency transmission frequency is activated; When the overall priority score is less than 0.4, the low-frequency transmission frequency is activated.

[0026] In one exemplary embodiment, the decision engine module is further configured to: Confirm that at least three nearby vessels are using AIS communication. After confirming that the message was successfully sent and receiving a reply from the rescue platform, reduce the sending frequency; After confirming that the rescue personnel are gradually approaching, increase the frequency of sending location information.

[0027] In one exemplary embodiment, the decision engine module is further configured to: Once the battery level is confirmed to be ≥80%, the Automatic Identification System (AIS) is activated to transmit at high frequency, and a standard distress message is continuously broadcast. The GPS is activated to continuously track the ship and report its location once at regular intervals. If the battery level is confirmed to be between 80% and 30%, activate the Automatic Identification System (AIS) by broadcasting at a reduced frequency once or by using a carrier listening strategy. This means remaining silent during normal times, but immediately increasing the transmission frequency when an AIS signal is detected nearby. Switch the GPS to periodic inspection and reporting of the location once and disable continuous tracking mode, using single positioning and single transmission instead. Once the battery level is confirmed to be 10% ≤ 30%, the Automatic Identification System (AIS) is turned off, and the Global Positioning System (GPS) is activated using a combination of periodic and trigger modes. Specifically, the frequency is adjusted to wake up and send coordinates every 1-3 hours, and to wake up and send a message immediately when vital signs show extreme abnormalities. Once the battery level is confirmed to be less than 10%, switch the transmission mode to heartbeat mode, which sets the frequency to an extremely low value and transmits once every 8 hours.

[0028] In one exemplary embodiment, the system is further equipped with a BeiDou short message communication module. Upon receiving a response from search and rescue personnel, the BeiDou short message communication module provides a voice prompt, sends location and vital signs information, receives search and rescue information, and obtains rescue feedback. Specifically, in standby mode, it sends a short message containing its own ID and status to the BeiDou satellite every 1-3 hours; upon activation of the personnel-in-water location beacon, it immediately initiates BeiDou high-precision positioning to obtain accurate coordinates better than 10 meters, while simultaneously sending a standard distress message; it continuously sends distress messages every 1-5 minutes, waiting for the rescue center to receive the alarm and then sending a confirmation message to the location beacon via the BeiDou satellite; it sends the real-time location and trajectory of the location beacon to nearby rescue vessels via short messages, and sends more detailed information to the rescue vessels via AIS; it receives commands from approaching rescue personnel to disable the alarm or switch to beacon mode and cease operation.

[0029] This embodiment provides a method for optimizing the transmission mode of a position beacon signal, which utilizes the aforementioned position beacon signal transmission mode optimization system to optimize the transmission mode of the position beacon signal.

[0030] In some embodiments, the above-described position beacon signal transmission mode optimization system can also be implemented in the following ways.

[0031] In this embodiment, the beacon signal transmission mode optimization system includes an intelligent dynamic optimization AI model for the beacon distress signal transmission frequency and communication method: (1) Input: Power index (SOC), coordinate information (longitude, latitude), number and strength of Automatic Identification System (AIS) signal, Beidou module signal strength, vital signs data of people who fell into the water, ocean current (statistical analysis through coordinate and time information), density of surrounding ships, etc. All data are acquired in real time through the integrated module.

[0032] (2) AI model: Establish a dynamic change model of transmission frequency corresponding to the duration of falling into the water, distance from rescuers, and power status of the positioning beacon; establish a signal transmission mode that combines different communication methods according to the location of the person falling into the water and the power status of the positioning beacon; use AI algorithms to intelligently analyze the fused massive data to realize the planning of intelligent communication methods; In one exemplary embodiment, the AI ​​module adopts a lightweight embedded framework (such as TensorFlow Lite, ONNX Runtime PyTorch Mobile, etc.) to build an extremely lightweight machine learning inference framework. Through dynamic sparse training technology, model quantization, knowledge distillation and other methods, the system hardware resource requirements are reduced, and finally, the AI ​​model can be inferred, dynamically optimized and output the selection of corresponding transmission frequency, transmission terminal, transmission content, etc. based on the input data obtained by power 1. (1). The main features of this model include: (1) When a person falls into the water, based on location information, comprehensive knowledge base, etc., intelligent reasoning will send a signal at a high frequency that is safe and reliable, so as to make high-precision drift displacement prediction in the future. (2) After ensuring that the information is successfully transmitted and a reply is received from the rescue platform, reduce the sending frequency appropriately to conserve power and improve battery life; (3) Set the vital signs information of the person who fell into the water as the highest priority. At that time, the device will transmit distress information at all times, regardless of the amount of battery power, until it is exhausted. (4) After receiving information that the rescuers are gradually approaching, the system will intelligently increase the frequency of location information transmission to ensure faster and more accurate location of the person who fell into the water.

[0033] (3) Output: selection of transmission signal source, transmission frequency, transmission information content, etc.

[0034] In one exemplary embodiment, the output data of the AI ​​model mainly includes: the source of the transmitted signal, the selection of the transmission frequency, and the content of the transmitted information; In one exemplary embodiment, the dynamic output parameters of the AI ​​model optimize the selection of the phase transmission channel and transmission frequency: (1) When the SOC is at a high level (typical value such as 100%), AIS transmits at high frequency and continuously broadcasts standard distress message (Mayday) at a fixed frequency (such as 30 seconds); Beidou continuously tracks and reports the location once at regular intervals (RDSS short message). (2) When the SOC is at a medium level (typical value such as 80%), AIS intelligently reduces the frequency (such as every 300 seconds) and broadcasts once or adopts the "carrier listening" strategy, that is, it is silent normally, but when it detects that there is an AIS signal in the vicinity (i.e. there is a ship nearby), it immediately increases the transmission frequency (such as every 60 seconds); Beidou changes to timed inspection (such as every 15-30 minutes) to report the position once and closes the continuous tracking mode, and uses single positioning + single transmission. (3) When the SOC is at a low level (typical value such as 30%), the AIS frequency drops to zero and is completely shut down; Beidou adopts a combination of periodic mode and trigger mode, that is, the frequency is adjusted to wake up and send coordinates once every 1-3 hours and wake up and send a message immediately when the vital signs are extremely abnormal. (4) When the SOC is extremely low, switch to "heartbeat mode" to fix the frequency at an extremely low value (typical value: 1 time / 8 hours).

[0035] In one exemplary embodiment, the selection of the transmitted information content: (1) When using AIS to transmit, the main information transmitted includes location, terminal, drift and velocity direction; (2) When using BeiDou to transmit information, the main information sent includes location, life status of personnel, drift direction and speed; In one exemplary embodiment, the four states of the SOC are characterized as follows: (1) First stage: Utilizing the second-level high real-time and line-of-sight propagation characteristics of AIS (about 5 nautical miles), all nearby ships and shore base stations can immediately see the alarm icon on the electronic nautical chart, thereby achieving second-level detection and avoidance; Beidou can break through the line-of-sight limitation of AIS, report the danger to the professional rescue coordination center hundreds to thousands of kilometers away, activate remote rescue forces, and provide key trajectory prediction basis for subsequent search and rescue; (2) Second stage: The use of AIS is to maintain its presence in the near range and ensure that newly entered ships can find the distressed persons; while the peak power consumption of Beidou short message is high (about 18W) but the duration is extremely short (about 0.3 seconds). By significantly reducing the transmission frequency, the average power consumption can be reduced to an extremely low level, while ensuring that the search and rescue platform can still grasp the approximate location and survival status. (3) The third stage: AIS needs to be continuously transmitted and its basic power consumption (even when not transmitting) and transmission power consumption are much higher than the standby power consumption of Beidou. Therefore, at the last moment, the short-range broadcast value of AIS is far less than the long-range beacon value of Beidou. However, by utilizing the excellent low-power design of Beidou terminals (such as standby power consumption of 0.0005W), the battery life of the device can be extended from a few hours to several days or even dozens of days, which provides the longest possible hope of survival for those adrift at sea.

[0036] In one exemplary embodiment, the BeiDou two-way communication function is integrated into the positioning beacon: (1) Equipped with a Beidou short message communication module; (2) It can provide voice prompts after receiving a reply from the search and rescue personnel; (3) Continuously and efficiently send location and vital signs information, and continuously receive search and rescue information and obtain rescue feedback.

[0037] In one exemplary embodiment, (1) In standby mode, the position marker sends a short message containing its own ID and status to the Beidou satellite at a very low frequency (e.g., every 1-3 hours); (2) Once the personnel fall into the water beacon is activated, Beidou high-precision positioning is immediately initiated to obtain accurate coordinates better than 10 meters, and at the same time, a standard distress message is sent (that is, the sensor data such as the current attitude, speed, and surrounding sea conditions are packaged). (3) The position beacon continuously sends distress messages at a high frequency (e.g., every 1-5 minutes). After receiving the alarm, the rescue center sends a "confirmed receipt" feedback message to the position beacon via the Beidou satellite. (4) At the same time, Beidou will send the real-time position and trajectory of the beacon to nearby rescue vessels via short message. At close range (such as within a few nautical miles), the beacon can send more detailed information to the rescue vessels via AIS. (5) When rescuers approach, they can use a handheld terminal or shipboard equipment to send instructions such as "turn off alarm" or "switch to beacon mode" to the position beacon via Beidou short message, and the position beacon will stop working.

[0038] In one exemplary embodiment, a distress signal transmitting device controllable by the search and rescue platform backend is established: After receiving a distress signal, the search and rescue platform can optimize and adjust the frequency of location and vital signs information provided by the positioning beacon as it continuously narrows the search area.

[0039] In one exemplary embodiment, (1) During the wide-area search period immediately after receiving the alarm information, the platform sends MODE_URGENT (emergency mode), sends the location frequency 1-2 minutes / time, and attaches vital signs with the package; (2) When the rescue ship / aircraft enters within a radius of 5 nautical miles but has not yet visually spotted the person in the water, the rescue platform needs to correct the error of the last few hundred meters in real time and send MODE_TRACKING (tracking mode) at a frequency of 5-10 minutes / time. If the internal algorithm of the position beacon detects that the position change exceeds the threshold (such as 50 meters) or the attitude changes drastically (such as being lifted by waves), it will immediately send the position once. Normally, it will send the position at a low frequency. Vital signs will be queried as needed or triggered by an anomaly. (3) When the rescuers have seen the person in the water or the life raft (within 1 nautical mile), the platform issues MODE_HOMING (return mode) and forces the AIS Class B (10 seconds / time) to be activated so that the rescue ship's radar and ECDIS can directly capture it. The platform also instructs the position beacon to turn on the high-frequency flash or buzzer to facilitate visual positioning and continuous monitoring of vital signs.

[0040] In some embodiments, the above-described position beacon signal transmission mode optimization system can also be implemented in the following ways.

[0041] I. Priority-based decision-making workflow This model's decision-making process employs a composite logical structure of "abnormality-priority interruption + hierarchical condition judgment," ensuring that conventional energy-saving strategies can be bypassed in critical and urgent moments to achieve immediate response to weak vital signs. The entire workflow design balances real-time performance, interpretability, and embedded deployment feasibility, avoiding delays caused by complex inference.

[0042] 1. Core Decision-Making Principles The system operates according to the following three core logical principles: (1) Priority principle for vital signs: Vital signs strength is the highest priority interruption signal. Once it is determined to be "weak", all other judgment nodes will be skipped immediately, and emergency launch mode will be forcibly entered.

[0043] (2) Dynamic trade-off principle under power constraints: Under normal vital signs conditions, the launch strategy needs to take into account the power level and other environmental factors, and make an intelligent balance between extending the standby time and increasing the probability of being detected.

[0044] (3) Environmental perception-driven communication switching principle: By utilizing AIS signal strength and geographic location information, the density of surrounding ship activity can be determined, and the optimal communication channel (near-field broadcast or satellite link) can be dynamically selected to improve information delivery efficiency.

[0045] 2. Decision-making and execution process The model executes judgments layer by layer in the following order, forming a clear control path: start; ↓ Read the intensity of vital signs; ↓Yes; Weak vital signs? ──────→Activate the [Emergency Frequency] (once every 10 seconds) and enable multi-channel synchronous broadcasting; No; Read battery level; ↓ Battery level <20%? ────Yes───→Entering [Low Frequency] (every 5 minutes), unless subsequent conditions force an upgrade; No; Read AIS signal strength and number of ships; ↓ Are there ≥3 ships visible? ───Yes───→Prioritize AIS-MOB (Man Overboard) / VHF Intermediate Frequency Broadcast (once per minute); No; Read the time of falling into the water and the distance to the rescue; ↓ Long distance (>10km) or long time (>6h)? ──Yes──→Switch to satellite channel high-frequency transmission (once every 30 seconds); No; By default, satellite channel intermediate frequency transmission is used (once per minute); This process embodies the design philosophy of "early assertion and fast response," minimizing unnecessary computational overhead and making it suitable for resource-constrained embedded platforms.

[0046] Among them, multiple channels include satellite (BeiDou) and AIS / VHF; 3. Key Decision Rule Matrix To enhance the configurability and maintainability of the system, the main decision paths are summarized into clear conditions-action mapping relationships, which facilitates subsequent parameter tuning and firmware updates, as shown in Table 1. Table 1: Condition-Action Mapping Relationship Table

[0047] The aforementioned set of rules constitutes the core behavioral specifications of the AI ​​model, and has been encoded and verified in the algorithm implementation to ensure logical consistency and execution reliability.

[0048] II. Mathematical Processing Model and Algorithm Implementation The core mathematical processing of this model lies in transforming multidimensional heterogeneous inputs into quantifiable transmit priority scores, and generating the final transmit frequency decision through threshold mapping. This process employs a lightweight linear weighted model to ensure millisecond-level inference response on resource-constrained embedded devices.

[0049] 1. Construction of weighted scoring model The system uses the following weighted linear combination formula to calculate the overall priority score: PriorityScore=w1·(1-L)+w2·(1 B)+w3·T+w4·D w5·E; The variables are defined as follows: L: Normalized value of vital sign intensity (0=weak, 1=strong), inverted to reflect the risk level; B: Normalized energy value (0 = depleted, 1 = fully charged), reflecting the degree of energy constraint; T: Normalized value of time of fall into water (increases with time, with an upper limit of 1), representing the decay of survival probability; D: Distance to rescue normalized value (the greater the distance, the higher the score), indicating the urgency of the location; E: AIS environmental friendliness (points are deducted if there is a ship), reflecting the feasibility of near-field communication; Note: All input variables must be preprocessed to the [0,1] interval to ensure the effectiveness of weight allocation.

[0050] 2. Weighting and Physical Meaning The weighting parameters determine the relative importance of each factor in the decision-making process. Their initial recommended values ​​are set based on the maritime search and rescue priority principle, as shown in Table 2: Table 2: Weighting Allocation Table

[0051] Note: The above weights can be fine-tuned and optimized using real-world scenario data in the future. The current values ​​already meet the basic functional requirements.

[0052] 3. Transmission Frequency Level Mapping Rules Based on the calculated priority scores, the system divides them into four levels, each corresponding to a different transmission frequency strategy: >0.8 → Emergency Frequency: Fires once every 10 seconds, ignoring power consumption; 0.6~0.8 → High frequency: Transmits once every 30 seconds, suitable for high-risk or long-distance scenarios; 0.4~0.6 → Intermediate frequency: Transmits once per minute, standard operating mode; ≤0.4 → Low frequency: Transmits once every 5 minutes for energy-saving standby; Note: This mapping only works if vital signs are normal; if weak vital signs are detected, the scoring will be skipped and the emergency frequency will be entered immediately.

[0053] 4. Algorithm implementation logic and function behavior: The Python function `calculate_transmission_frequency` has been coded and verified, and its implementation logic strictly follows the following priority order: First priority: If the vital signs strength is ≤0.3, then return "emergency"; Second priority: If the battery level is less than 0.2, the default value is "low" unless the submersion time is greater than 12 hours or the distance is greater than 10 kilometers (in which case it will be upgraded to "medium"). Third priority: In all other cases, a weighted scoring model is applied, and frequency levels are determined based on thresholds; This function supports real-time inference, with an average call time of less than 1ms (on Cortex-M4 level MCUs), making it highly practical for engineering applications.

[0054] III. System Deployment Architecture and Operating Environment The deployment architecture of this water-dropping beacon AI model adopts a layered and modular design to ensure that the system achieves intelligent decision-making and real-time response under constraints of low power consumption and high reliability. The overall framework is divided into five logical layers, each with clearly defined responsibilities and interfaces, supporting independent development and testing, and facilitating subsequent maintenance and upgrades.

[0055] 1. Layered System Architecture Design To adapt to embedded edge computing scenarios, the system is functionally decoupled into the following five-layer structure: (1) Data acquisition layer: responsible for acquiring raw data from various sensors and communication modules; (2) Data preprocessing layer: filtering, normalizing and feature synthesis of the original signal; (3) Decision engine layer: Runs AI model to complete launch strategy reasoning; (4) Execution control layer: Schedules the working status of the radio frequency module according to the decision results; (5) Power management layer: Dynamically optimize power consumption and extend the effective working time of the equipment; This architecture supports hardware and software co-optimization, enabling efficient operation under resource-constrained conditions.

[0056] 2. The functions and technical implementations of each level are shown in Table 3; Table 3: Functions and Technical Implementation at Each Level

[0057] IV. Boundary Scenarios and Fault Tolerance Mechanisms To ensure the high reliability and robustness of the AI ​​model for the waterborne beacon in the complex and ever-changing marine environment, the system is designed with a comprehensive boundary scene recognition and fault-tolerant response mechanism. This mechanism does not rely on idealized assumptions but actively defends against real-world risks such as sensor failure, sudden environmental changes, and energy anomalies, ensuring that critical life information can still be effectively transmitted under extreme conditions.

[0058] Table 4 shows typical boundary scenarios and their corresponding engineering-level response strategies; Table 4: Typical Boundary Scenarios and Corresponding Engineering-Level Response Strategies

[0059] The aforementioned mechanism is embedded between the power management layer and the execution control layer, forming a closed-loop protection logic. All strategies have been verified through simulation testing in the prototype system and meet the reliability requirements of the IEC 60945 maritime equipment standard. Through this deep fault-tolerant design, this AI model can not only intelligently schedule resources under normal conditions, but also maintain core functions to the maximum extent in the event of sudden failures, truly achieving the life-saving mission of "not dropping the chain at critical moments".

[0060] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims. All of these forms are within the protection scope of the present invention.

Claims

1. A system for optimizing the transmission mode of a position marker signal, characterized in that, It includes a data acquisition module, a preprocessing module, a decision engine module, an execution control module, and a power management module; The data acquisition module is used to collect data on power index, vital signs of people who have fallen into the water, data from the Automatic Identification System (AIS) and Global Positioning System (GPS). The preprocessing module is used to suppress noise and standardize the collected data, and output a normalized vector. The decision engine module is used to select the communication method, transmission frequency, and transmission information content based on the normalized vector. The execution control module is used for signal scheduling and transmission control; The power management module is used for dynamic power consumption control.

2. The position indicator signal transmission mode optimization system according to claim 1, characterized in that, The preprocessing module is configured to: perform Kalman filtering on the collected data to remove noise; standardize the noise-removed data to the [0,1] interval; estimate the ocean current trend based on coordinates and time; and determine the environmental friendliness based on the Automatic Identification System (AIS) data.

3. The position beacon signal transmission mode optimization system according to claim 1, characterized in that, The normalized vector includes normalized values ​​for vital signs intensity, battery level, time of fall into water, distance from rescue, and AIS environmental friendliness.

4. The position indicator signal transmission mode optimization system according to claim 1, characterized in that, The decision engine module is configured as follows: If the vital signs of the person who fell into the water are confirmed to be weak, give them the highest priority and activate emergency frequency and multi-channel synchronous broadcasting. The vital signs of the person who fell into the water have been confirmed to be normal. Once the normalized power value is confirmed to be less than the preset power threshold, the low-frequency transmission frequency is activated. If the time of falling into the water is confirmed to be greater than the preset time of falling into the water, or the rescue distance is greater than the preset rescue distance, the intermediate frequency transmission frequency will be activated. Calculate the overall priority score based on the normalized vector; Different transmission frequencies are activated based on the comprehensive priority score.

5. The position indicator signal transmission mode optimization system according to claim 4, characterized in that, The formula for calculating the comprehensive priority score is as follows: Priority Score=w1·(1-L)+w2·(1 B)+w3·T+w4·D w5·E, Among them, PriorityScore is the overall priority score; L is the normalized value of vital signs intensity; B is the normalized value of battery power; T is the normalized value of time in the water; D is the normalized value of distance from rescue; E is the AIS environmental friendliness; w1, w2, w3, w4 and w5 are weighting coefficients.

6. The position beacon signal transmission mode optimization system according to claim 4, characterized in that, The method for initiating different transmission frequencies based on the comprehensive priority score is as follows: When the overall priority score is greater than 0.8, the emergency frequency is activated; When the overall priority score is 0.6~0.8, the high-frequency transmission frequency is activated; When the overall priority score is between 0.4 and 0.6, the intermediate frequency transmission frequency is activated; When the overall priority score is less than 0.4, the low-frequency transmission frequency is activated.

7. The position beacon signal transmission mode optimization system according to claim 1, characterized in that, The decision engine module is also configured as follows: Confirm that at least three nearby vessels are using AIS communication. After confirming that the message was successfully sent and receiving a reply from the rescue platform, reduce the sending frequency; After confirming that the rescue personnel are gradually approaching, increase the frequency of sending location information.

8. The position beacon signal transmission mode optimization system according to claim 1, characterized in that, The decision engine module is also configured as follows: Once the battery level is confirmed to be ≥80%, the Automatic Identification System (AIS) is activated to transmit at high frequency, and a standard distress message is continuously broadcast. The GPS is activated to continuously track the ship and report its location once at regular intervals. If the battery level is confirmed to be between 80% and 30%, activate the Automatic Identification System (AIS) by broadcasting at a reduced frequency once or by using a carrier listening strategy. This means remaining silent during normal times, but immediately increasing the transmission frequency when an AIS signal is detected nearby. Switch the GPS to periodic inspection and reporting of the location once and disable continuous tracking mode, using single positioning and single transmission instead. Once the battery level is confirmed to be 10% ≤ 30%, the Automatic Identification System (AIS) is turned off, and the Global Positioning System (GPS) is activated using a combination of periodic and trigger modes. Specifically, the frequency is adjusted to wake up and send coordinates every 1-3 hours, and to wake up and send a message immediately when vital signs show extreme abnormalities. Once the battery level is confirmed to be less than 10%, switch the transmission mode to heartbeat mode, which sets the frequency to an extremely low value and transmits once every 8 hours.

9. The position beacon signal transmission mode optimization system according to claim 1, characterized in that, The system is also equipped with a BeiDou short message communication module. Upon receiving a response from search and rescue personnel, this module provides voice prompts, sends location and vital signs information, receives search and rescue information, and obtains rescue feedback. Specifically, in standby mode, it sends a short message containing its own ID and status to the BeiDou satellite every 1-3 hours; upon activation of the personnel-in-water beacon, it immediately initiates BeiDou high-precision positioning to obtain accurate coordinates better than 10 meters, while simultaneously sending a standard distress message; it continuously sends distress messages every 1-5 minutes, waiting for the rescue center to receive the alarm and then sending a confirmation message to the beacon via BeiDou satellite; it sends the beacon's real-time location and trajectory to nearby rescue vessels via short messages, and sends more detailed information to the rescue vessels via AIS; and it receives commands from approaching rescue personnel to disable the alarm or switch to beacon mode and cease operation.

10. A method for optimizing the transmission mode of a position indicator signal, characterized in that, The position beacon signal transmission mode optimization system as described in any one of claims 1-9 is used to optimize the position beacon signal transmission mode.

Images