Intelligent personal falling-into-water position indicating mark based on multi-mode communication and dynamic cooperation

Abstract

The invention discloses an intelligent personal falling-into-water position indicating mark based on multimode communication and dynamic coordination, which belongs to the field of rescue equipment and comprises a shell, a water-sensitive sensor, an antenna assembly, a battery, a man-machine interaction module and an integrated control circuit board, a master control module, a positioning module, a signal modulation module, a radio frequency emission module and a man-machine interaction module are integrated on the integrated control circuit board. The master control module is further configured to execute a dynamic time division multiplexing and channel state interception protocol, motion-power consumption adaptive control, and positioning data confidence evaluation and fusion. According to the invention, the accessibility of the alarm signal under the congestion channel is obviously improved in the theoretical level; the dynamic optimal balance between the cruising ability and the rescue efficiency is realized; more stable and more credible high-quality position information is provided; the technical span of the personal falling-into-water position indicating mark from a passive beacon to an active intelligent agent is marked.

Description

Technical Field

[0001] This invention relates to the field of water safety rescue equipment technology, specifically to an intelligent personal water-falling location beacon integrating active alarm, precise positioning and multi-mode communication functions and its working method. Background Technology

[0002] Personal position beacons (PBOs) are critical emergency equipment for ensuring the safety of crew members, fishermen, and those engaged in water work and sports. Traditional PBOs (such as PLBs or MOB Beacons) have relatively limited functionality, typically relying on satellite systems (such as the 406MHz EPIRB system) or simple VHF analog signals (such as 121.5MHz). Their alarms have a certain delay, and the information cannot be effectively and directly received and identified by nearby vessels that are most likely to provide rapid rescue.

[0003] With the development of marine electronic technology, Automatic Identification Systems (AIS) and Digital Selective Calling (DSC) have become standard equipment on modern ships, offering advantages such as real-time, short-range, and high-precision communication. However, in practical applications, especially in densely populated waters, existing technologies have revealed the following unresolved technical contradictions: 1. Alarm signal collision and channel efficiency issues: On VHF data channels (such as CH87B / 88B used by AIS), existing position indicators typically employ a fixed-interval blind transmission mechanism similar to "time-slot ALOHA". In densely populated areas, their AISMOB messages randomly compete with a large number of regular AIS messages from ships, resulting in a high probability of collision, easy loss of critical alarm information, and inability to guarantee reliable reception by nearby ships within the optimal rescue window.

[0004] 2. Mismatch between static allocation of system resources and dynamic scenarios: The transmission power, frequency, and mode of existing equipment are mostly fixed settings. This leads to wasted power consumption and unnecessary shortening of standby time on calm waters; while in severe sea conditions (when the person in the water is struggling violently or there are large waves), insufficient signal strength or update rate results in delayed location information and limited signal coverage, failing to provide optimal information support for dynamic rescue.

[0005] 3. The contradiction between a single positioning data source and information reliability: Although some devices adopt dual-mode positioning, their switching logic is mostly a simple "switch to backup if the primary source fails," failing to quantitatively evaluate and intelligently fuse the real-time quality of multi-source positioning data (such as satellite geometric distribution and signal-to-noise ratio). In complex electromagnetic environments or under partial obstruction conditions, there is still a risk of positioning interruption, a sharp drop in accuracy, or the output of unreliable data. Summary of the Invention

[0006] This invention aims to overcome the aforementioned shortcomings and provide an intelligent personal water-falling location beacon and its method based on multi-mode communication and dynamic collaboration. The core concept of this invention lies in constructing an intelligent closed-loop system of "perception-decision-execution-optimization," rather than simply stacking functional modules. This system proactively manages channel access by introducing channel state monitoring and adaptive avoidance mechanisms to resolve signal conflict issues; it intelligently allocates energy by establishing a dynamic mapping model between motion state and power consumption strategies to resolve the contradiction between endurance and timeliness; and it improves the accuracy and robustness of location information by implementing location data confidence assessment and weighted fusion algorithms to address data source vulnerability. These three elements work together to make the device an intelligent terminal capable of adapting to complex and dynamic rescue scenarios.

[0007] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In a first aspect, the present invention provides an intelligent personal water positioning beacon based on multi-mode communication and dynamic collaboration. The beacon includes a housing, a water-sensitive sensor, an antenna assembly, a battery, and an integrated control board. The integrated control board integrates a main control module, a positioning module, a signal modulation module, a radio frequency transmission module, and a human-machine interaction module. The main control module is further configured to execute: Dynamic time-division multiplexing and channel state monitoring protocol: In each cycle of controlling the radio frequency transmission module to sequentially transmit AISMOB message signals, DSC distress alarm signals, and digital voice alarm signals, before transmitting any signal, the target VHF channel is first monitored for energy for a duration of t1; if the monitored channel energy is lower than a preset threshold Eth, the signal is immediately transmitted; if it is higher than or equal to Eth, a random backoff time is waited before re-monitoring until successful transmission; Motion-power adaptive control: Based on the motion data collected in real time by the attitude sensor connected to the main control module, calculate the motion index M, which represents the intensity of the current sea state disturbance; and dynamically adjust the current transmission power P, alarm cycle T, and transmission duration ratio R of AIS, DSC, and voice signals according to the pre-stored lookup table that maps the motion index M to the transmission parameter set {P,T,R}. Positioning data confidence assessment and fusion: Real-time acquisition of positioning data Lb from the BeiDou system, along with its accuracy factor DOPb and satellite count Nb, and positioning data Lg from the GPS system, along with its accuracy factor DOPg and satellite count Ng; when both systems' data are valid, a weighted fusion algorithm is used to calculate the final positioning result L_final = Wb × Lb + Wg × Lg, where the weights Wb and Wg are inversely proportional to DOPb, and Wb + Wg = 1; the final positioning result L_final is used to generate all alarm signals.

[0008] Preferably, in the dynamic time-division multiplexing and channel state monitoring protocol, the preset threshold Eth is adaptively adjusted according to the current transmit power P, and the adjustment relationship is: Eth = K × P + C, where K and C are constants preset according to the environmental noise level.

[0009] Preferably, the motion index M is obtained by calculating the variance or amplitude spectral density of the data output by the attitude sensor within a preset time window; the lookup table contains at least three levels: when M is lower than the first threshold M_low, it corresponds to "calm mode", using the lowest power P1 and the longest period T1; when M is higher than the second threshold M_high, it corresponds to "severe mode", using the highest power P3 and the shortest period T3, and increasing the proportion of voice signal transmission time; when M is between the first and second thresholds, it corresponds to "standard mode", using the middle power P2 and period T2.

[0010] Preferably, in the location data confidence assessment and fusion, the conditions for data validity are defined as follows: the number of satellites N ≥ 4 and the accuracy factor DOP ≤ 5; if only one system data is valid, then the data of that system is directly used as L_final; if both systems are invalid, then the previously valid L_final is used.

[0011] Preferably, the main control module is also configured to execute a battery power adaptive strategy: monitor the remaining battery power Q in real time, and when Q is lower than the warning power Q_alert, automatically enter the energy-saving mode, gradually reduce the transmission power P and extend the cycle period T, while maintaining the highest transmission priority for the DSC distress alarm signal.

[0012] Preferably, the human-computer interaction module includes a flash and a voice unit; the main control module controls the flash to flash in SOS Morse code mode and controls the voice unit to broadcast a distress message containing MMSI code and latitude and longitude in a bilingual loop; after each successful transmission of an AISMOB or DSC signal containing new location information, the flash is controlled to perform visual confirmation by flashing a specific rapid sequence.

[0013] Preferably, the signal modulation module integrates a DSC encoding unit, an AIS message encapsulation unit, and a speech synthesis and playback unit.

[0014] Secondly, the present invention also provides a dynamic collaborative alarm method for the above-mentioned intelligent personal water-falling locator. This includes the following steps: S1. Waterfall Trigger and Environmental Awareness: In response to the water sensor signal, the system is woken up and the positioning module and attitude sensor are activated; S2. Intelligent initialization: Acquire initial positioning data, calculate initial motion index M0, and determine the initial launch parameter set {P0,T0,R0} according to the lookup table; S3. Enter the collaborative alarm loop and execute the following sub-steps until intervention or shutdown: S31. Channel Awareness and Transmission Decision: Based on the current signal type and parameter set to be transmitted in the current cycle, perform energy listening on the target channel for a period of t1 and compare it with the threshold Eth. Based on the comparison result, execute immediate transmission or backoff and retry. S32. Signal generation and transmission: Using the latest fusion positioning result L_final and preset MMSI code, generate and transmit corresponding AISMOB, DSC or digital voice alarm signals; S33. Status Update and Parameter Adjustment: During the loop interval, based on the latest acquired positioning data confidence, channel busy / idle statistics, updated motion index M and battery power Q, the adaptive algorithm is invoked to update the transmission parameter set {P,T,R} for the next loop; The adaptive algorithm is as follows: If the average busy-to-idle ratio of the channel is higher than the threshold Busy_th within N1 consecutive cycles, then the upper limit of the random backoff time is increased. If the rate of change ΔM of the motion index M exceeds the positive threshold, then immediately switch to a higher power level parameter set based on the current M value; If the battery charge Q is lower than Q_alert, the linear decay function is activated, gradually decreasing P and increasing T.

[0015] S34. Visual feedback: After each successful transmission of a critical position update signal, drive the flash to produce a confirmation flash.

[0016] Compared with the prior art, the present invention has the following beneficial effects: 1. Significantly Improved Reachability of Alarm Signals in Congested Channels at the Theoretical Level: This invention innovatively applies the mature Carrier Sense Multiple Access / Collision Avoidance (CSMA / CA) concept from wireless local area networks to maritime VHF data links. Through a "listen-backoff-transmit" protocol, the traditional random transmission mode of position indicators based on "time-slotted ALOHA" is improved to a controlled transmission mode based on channel busy / idle states. According to multiple access communication theory, under the same channel load conditions, the throughput performance of CSMA-type protocols is far superior to that of ALOHA-type protocols. Therefore, this method can fundamentally reduce the probability of alarm messages being lost due to random collisions, theoretically significantly improving the alarm success rate and timeliness in high-density ship areas.

[0017] 2. Achieving a dynamic optimal balance between endurance and rescue effectiveness: This invention establishes a closed-loop feedback control model from "physical motion state" to "communication resource allocation." The intensity of sea state disturbances is calculated in real time using attitude data, and the transmission power, frequency, and signal ratio are dynamically adjusted accordingly. In calm sea conditions, the system automatically enters a low-power state, significantly reducing average power consumption and effectively extending the theoretical standby and alarm duration of the equipment. In severe sea conditions, transmission is automatically enhanced to ensure the strength of critical information. This adaptive strategy resolves the inherent contradiction of "either wasting power or sacrificing performance" under fixed-parameter strategies.

[0018] 3. Providing more stable and reliable high-quality location information: By evaluating the quality indicators (such as accuracy factor and number of satellites) of BeiDou and GPS positioning data in real time and performing weighted fusion, the positioning output of this invention has the following theoretical advantages: First, when the signal quality of a single system deteriorates, its contribution weight can be automatically reduced to avoid low-quality data polluting the output; second, when both systems are available, the expected error of the fusion result is theoretically no greater than that of either single system, and it is statistically more stable. This enhances the continuity, reliability, and accuracy of location information in complex environments, providing a more reliable basis for decision-making in rescue operations.

[0019] 4. This invention marks a technological leap from "passive beacons" to "active intelligent agents" for personal underwater positioning beacons: By deeply integrating environmental perception, multi-source information processing, intelligent decision-making, and reliable execution, this invention forms a complete autonomous and collaborative system. The device can autonomously optimize its behavior strategy based on the external environment (channel, sea state) and internal status (battery power, positioning quality), achieving a leap from simple function execution to the ability to adapt to complex systems. Attached Figure Description

[0020] Figure 1 This is a schematic diagram of the structure of the present invention; Figure 2 This is a schematic diagram of another direction of the present invention; Figure 3 This is an exploded view of the present invention; Figure 4 A schematic diagram showing the connection between the protective cover and the front housing via ropes; Figure 5 This is a logic diagram of the present invention; Figure 6 This is a flowchart illustrating the dynamic collaborative alarm method. Figure 7 A flowchart illustrating the motion-power adaptive control strategy; Figure 8 A flowchart illustrating the process of confidence assessment and fusion of location data.

[0021] In the diagram: 1-Housing, 2-Antenna assembly, 3-Battery, 4-Integrated control board, 5-Front housing, 6-Rear housing, 7-Sealing ring, 8-Switch contact, 9-Antenna shaft, 10-Antenna, 11-Transparent cover, 12-Hook, 13-Protective cover, 14-Rope, 15-Test button. Detailed Implementation

[0022] 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. Example 1

[0023] Please see Figure 1-4 This intelligent personal water-falling locator, based on multi-mode communication and dynamic collaboration, includes a housing 1, a water sensor, an antenna assembly 2, a battery 3, and an integrated control board 4. The housing 1 comprises a front housing 5, a rear housing 6, a hook 12, a transparent cover 11, a test button 15, a rope 14, and a protective cover 13. The front housing 5 and the rear housing 6 are connected by a sealing ring 7, achieving a high level of waterproofing. The water sensor includes a switch contact 8 on the front housing, typically located at the bottom of the device, used to detect water-falling conditions. The integrated control board 4 has one end inside the front housing 5 and the other end inside the rear housing 6. The antenna assembly 2 is connected to the radio frequency transmission module and includes an antenna shaft 9 and an antenna 10, compatible with AIS, DSC, and VHF communication bands. The antenna 10 is fixed to the outer wall of the rear housing 6 with screws. A transparent cover 11 is located on the side of the front housing 5 not covered by the protective cover. A flash lamp, composed of an array of multiple high-brightness LEDs, is located inside the transparent cover 11.

[0024] Battery 3 is housed within housing 1 and mounted on integrated control board 4 to power the device. Preferably, the power supply uses a rechargeable CR123A lithium battery pack, equipped with a corresponding charging management circuit (battery management unit) and a magnetic waterproof charging interface located on the housing. The main control module is also connected to the battery management unit to monitor battery level and provide low-battery voice alerts via an intelligent voice unit.

[0025] The rear housing 6 is also provided with a hook 12 for carrying. A protective cover 13 is snapped onto the periphery of the front housing 5 and is arranged side by side with the transparent cover 11, with the protective cover 13 partially covering the front housing 5. In addition, the protective cover 13 is also connected to the front housing 5 by a rope 14.

[0026] The instructions for knotting and coiling the rope (e.g.) Figure 4 (as shown) (1) The rope is made of polypropylene core rope with a diameter of φ2, orange color and a length of 1.5±0.1m.

[0027] (2) Heat both ends of the rope with a soldering iron to prevent the rope from loosening and to facilitate threading.

[0028] (3) Coil the B end of the rope as shown in the diagram, pass the A end of the rope through the hole in the front shell as shown in the diagram, tie a No. 1 knot, and then pass it through the hole in the front shell.

[0029] (4) Finally, thread the rope A end through the protective cover and tie a No. 2 knot. Lightly heat the No. 2 knot with a soldering iron to prevent the knot from coming loose.

[0030] (5) The rope length between knot 1 and knot 2 is 80-90mm, and the distance between knot 2 and end A is 3-5mm.

[0031] (6) The rope must not be damaged.

[0032] In addition, a test button 15 is provided on the front housing 5, and a through hole is provided on the protective cover 13 to accommodate the test button 15 so that the test button 15 can be pressed from outside the protective cover 13. Example 2

[0033] The integrated control board integrates a main control module (such as an MCU), a positioning module (integrating a Beidou and GPS dual-mode chip), a signal modulation module, a radio frequency transmission module (VHF band), and a human-machine interaction module. The main control module is connected to an attitude sensor (such as a six-axis IMU).

[0034] The main control module is configured to perform three core functions: Dynamic Time-Division Multiplexing and Channel State Monitoring Protocol: The main control module controls the RF transmission module to sequentially transmit three signals—AISMOB messages, DSC distress alarms, and digital voice alarms—within an alarm cycle. Before transmitting any signal, the RF front-end is controlled to perform energy monitoring on the target channel (such as the AIS channel) for a duration of t1 (e.g., 50ms). If the detected energy is lower than a fixed threshold Eth (e.g., -110 dBm), the channel is considered idle, and transmission is initiated immediately; otherwise, a backoff time randomly generated within the interval [0, T_backoff] is waited before re-executing the monitoring until successful transmission. This effectively avoids message collisions with other AIS devices.

[0035] The dynamic time-division multiplexing and channel state monitoring protocol is implemented in software as follows: Before the start of the planned transmission window, the main control module briefly switches the RF front-end to receive mode and performs a Received Signal Strength Indication (RSSI) measurement on the target VHF channel (e.g., CH87B for AISMOB messages) for a duration of T_listen (e.g., 10ms). A preset idle threshold Eth is used, which can be set based on the receiver noise floor and system demodulation threshold, and can be dynamically fine-tuned with the current transmit power P, for example, Eth=f(P, Noise_Floor). If the measured value is lower than Eth, the channel is determined to be idle, and the system immediately switches to transmit mode and sends a signal; otherwise, the channel is determined to be busy, and a backoff algorithm is executed: a random backoff delay within the interval [T_min, T_max] is generated, and the monitoring process is re-executed after the delay. This method essentially adapts the CSMA / CA mechanism used in terrestrial wireless LANs to solve hidden terminals and packet collisions for use in maritime mobile distress alarm scenarios. By introducing the rules of "listen first, speak later" and "random conflict resolution," this protocol can effectively coordinate the contention for access to the shared channel by multiple unknown terminals, thereby improving the overall efficiency and reliability of the entire alarm network at the Media Access Control (MAC) layer.

[0036] Motion-Power Adaptive Control: The implementation steps of the motion-power adaptive control strategy are as follows: First, data is collected at a frequency Fs (e.g., 10Hz) using a built-in six-axis attitude sensor (including a three-axis accelerometer and a three-axis gyroscope). Within a sliding time window of length T_window (e.g., 20 seconds), the composite vector variance of the accelerometer data is calculated as the motion index M. Two thresholds, M_low and M_high, are set (e.g., M_low = 0.05g², M_high = 0.5g²). The system maintains a lookup table containing three sets of predefined parameters: • Calm mode (M < M_low): {P=P_low(eg, 0.5W), T_cycle=T_long(eg, 300s), R_voice=0.2} • Standard mode (M_low≤M≤M_high): {P=P_std(eg,1W), T_cycle= T_std(eg, 120s), R_voice=0.5} • Severe mode (M>M_high): {P=P_high(eg, 2W), T_cycle=T_short(eg, 60s), R_voice=1.0} Here, R_voice represents the percentage of transmission time of the digital voice alarm signal within a single cycle. The main control module calculates M in real time and switches operating modes based on a lookup table. This strategy constructs a negative feedback control system: violent environmental motion (high M) triggers stronger signal transmission (high P, short T_cycle) and richer information broadcasting (high R_voice) to cope with communication challenges under harsh conditions; while calm environments (low M) trigger energy-saving strategies to store precious battery energy. Through this dynamic resource allocation, the system optimizes the total energy budget over time, theoretically maximizing the effective operating time of the equipment without reducing the overall rescue success rate, or providing better alarm performance in extreme sea conditions with a given battery capacity.

[0037] Positioning data confidence assessment and fusion: The main control module reads positioning data, DOP values, and satellite counts from BeiDou and GPS in real time. Valid data conditions are defined as: satellite count ≥ 4 and DOP ≤ 5. If both systems are valid, the weight is calculated as: Wb = (1 / DOPb) / (1 / DOPb + 1 / DOPg), and Wg is calculated similarly. Then, the weighted fused position L_final = Wb × Lb + Wg × Lg is calculated and used for generating all alarm messages. If only BeiDou is valid, then L_final = Lb; if neither is valid, the previous valid position is used.

[0038] The main control module performs the following steps to make a location decision: a) Obtain BeiDou data: Lb, DOPb=3.2, Nb=6; Obtain GPS data: Lg, DOPg=7.5, Ng=5.

[0039] b) Validity assessment: BeiDou data satisfies Nb=6≥4 and DOPb=3.2≤5, so it is valid; GPS data satisfies Ng=5≥4, but DOPg=7.5>5, so it is invalid.

[0040] c) According to the rule (only one system is valid), the valid BeiDou data is directly used as the final positioning result L_final=Lb.

[0041] d) If in the next cycle, the BeiDou data becomes DOPb=8.1, Nb=3 (invalid) due to obstruction, while the GPS data recovers to DOPg=2.1, Ng=8 (valid), then the valid GPS data is used as L_final = Lg.

[0042] e) If both fail due to extreme conditions in the next cycle (e.g., DOP > 10), the system will reuse the valid L_final from the previous cycle (i.e., Lg in step d) and record the location failure flag. Simultaneously, a corresponding status flag will be added to the generated alarm message to inform the receiver that the current location information may be extrapolated or historical data and should be used with caution. This mechanism ensures the continuity of location information output to the greatest extent possible. Example 3

[0043] The human-computer interaction module includes an LED flash and a speech synthesis chip. The main control module controls the flash to flash in an SOS pattern of "three short, three long, three short" and controls the speech unit to repeatedly announce "Mayday, MMSI: XXXXXXXXX, Position:...". After each successful transmission of an AIS or DSC signal with a new position, the flash will flash three times rapidly as confirmation. Example 4

[0044] The main control module in this embodiment also implements a battery power adaptive strategy. When the battery power Q is detected to be lower than the warning power Q_alert (e.g., 20% of the total power), it automatically enters power saving mode. In this mode, the system keeps the transmission parameters of the DSC signal (highest priority) unchanged, but linearly attenuates the transmission power P of AISMOB and voice signals by 5% per cycle, while gradually extending the alarm cycle T by 50% from the current value. In this way, when the power is insufficient, the most critical DSC alarm function is prioritized, and the total alarm duration of the device is extended as much as possible.

[0045] It should be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0046] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A smart personal water-based positioning beacon based on multi-mode communication and dynamic collaboration, comprising a shell, a water-sensitive sensor, an antenna assembly, a battery, and an integrated control board, wherein the integrated control board integrates a main control module, a positioning module, a signal modulation module, a radio frequency transmission module, and a human-machine interaction module, characterized in that, The main control module is also configured to execute: Dynamic time-division multiplexing and channel state monitoring protocol: In each cycle of controlling the radio frequency transmission module to sequentially transmit AISMOB message signals, DSC distress alarm signals, and digital voice alarm signals, before transmitting any signal, the target VHF channel is first monitored for energy for a duration of t1; if the monitored channel energy is lower than a preset threshold Eth, the signal is immediately transmitted; if it is higher than or equal to Eth, a random backoff time is waited before re-monitoring until successful transmission; Motion-power adaptive control: Based on the motion data collected in real time by the attitude sensor connected to the main control module, calculate the motion index M, which represents the intensity of the current sea state disturbance; and dynamically adjust the current transmission power P, alarm cycle T, and transmission duration ratio R of AIS, DSC, and voice signals according to the pre-stored lookup table that maps the motion index M to the transmission parameter set {P,T,R}. Positioning data confidence assessment and fusion: Real-time acquisition of positioning data Lb from the BeiDou system, along with its accuracy factor DOPb and satellite count Nb, and positioning data Lg from the GPS system, along with its accuracy factor DOPg and satellite count Ng; when both systems' data are valid, a weighted fusion algorithm is used to calculate the final positioning result L_final = Wb × Lb + Wg × Lg, where the weights Wb and Wg are inversely proportional to DOPb, and Wb + Wg = 1; the final positioning result L_final is used to generate all alarm signals.

2. The intelligent personal water positioning beacon according to claim 1, characterized in that, In the dynamic time-division multiplexing and channel state monitoring protocol, the preset threshold Eth is adaptively adjusted according to the current transmit power P. The adjustment relationship is: Eth=K×P+C, where K and C are constants preset according to the environmental noise level.

3. The intelligent personal water positioning beacon according to claim 1, characterized in that, The motion index M is obtained by calculating the variance or amplitude spectral density of the data output by the attitude sensor within a preset time window; the lookup table contains at least three levels: when M is below the first threshold M_low, it corresponds to "calm mode", using the lowest power P1 and the longest period T1; when M is above the second threshold M_high, it corresponds to "severe mode", using the highest power P3 and the shortest period T3, and increasing the proportion of voice signal transmission time; when M is between the first and second thresholds, it corresponds to "standard mode", using the middle power P2 and period T2.

4. The intelligent personal water positioning beacon according to claim 1, characterized in that, In the location data confidence assessment and fusion, the conditions for data validity are defined as follows: the number of satellites N≥4 and the accuracy factor DOP≤5; if only one system data is valid, then the data of that system is directly used as L_final; if both systems are invalid, then the previously valid L_final is used.

5. The intelligent personal water positioning beacon according to claim 1, characterized in that, The main control module is also configured to execute a battery power adaptive strategy: monitor the remaining battery power Q in real time, and when Q is lower than the warning power Q_alert, automatically enter the energy-saving mode, gradually reduce the transmission power P and extend the cycle period T, while maintaining the highest transmission priority for the DSC distress alarm signal.

6. The intelligent personal water positioning beacon according to claim 1, characterized in that, The human-computer interaction module includes a flash and a voice unit; the main control module controls the flash to flash in SOS Morse code mode and controls the voice unit to broadcast a distress message containing MMSI code and latitude and longitude in a bilingual loop; after each successful transmission of an AISMOB or DSC signal containing new location information, the flash is controlled to perform visual confirmation by flashing a specific fast sequence.

7. The intelligent personal water positioning beacon according to claim 1, characterized in that, The signal modulation module integrates a DSC encoding unit, an AIS message encapsulation unit, and a speech synthesis and playback unit; the main control module and the positioning module are connected to the signal modulation module.

8. A dynamic collaborative alarm method for an intelligent personal water-falling marker, characterized in that, Includes the following steps: S1. Waterfall Trigger and Environmental Awareness: In response to the water sensor signal, the system is woken up and the positioning module and attitude sensor are activated; S2. Intelligent initialization: Acquire initial positioning data, calculate initial motion index M0, and determine the initial launch parameter set {P0,T0,R0} according to the lookup table; S3. Enter the collaborative alarm loop and execute the following sub-steps until intervention or shutdown: S31. Channel Awareness and Transmission Decision: Based on the current signal type and parameter set to be transmitted in the current cycle, perform energy listening on the target channel for a period of t1 and compare it with the threshold Eth. Based on the comparison result, execute immediate transmission or backoff and retry. S32. Signal generation and transmission: Using the latest fusion positioning result L_final and preset MMSI code, generate and transmit corresponding AISMOB, DSC or digital voice alarm signals; S33. Status Update and Parameter Adjustment: During the loop interval, based on the latest acquired positioning data confidence, channel busy / idle statistics, updated motion index M and battery power Q, the adaptive algorithm is invoked to update the transmission parameter set {P,T,R} for the next loop; S34. Visual feedback: After each successful transmission of a critical position update signal, drive the flash to produce a confirmation flash.

9. The dynamic collaborative alarm method according to claim 8, characterized in that, In step S33, the adaptive algorithm is as follows: If the average busy-to-idle ratio of the channel is higher than the threshold Busy_th within N1 consecutive cycles, then the upper limit of the random backoff time is increased. If the rate of change ΔM of the motion index M exceeds the positive threshold, then immediately switch to a higher power level parameter set based on the current M value; If the battery charge Q is lower than Q_alert, the linear decay function is activated, gradually decreasing P and increasing T.

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