A fishing float system and control method

Abstract

A fishing float system and control method, comprising a float module and a mobile terminal, wherein; the float module comprises a waterproof shell and an electronic cabin, the electronic cabin is arranged inside the waterproof shell, the waterproof shell is used to avoid the electronic cabin from being flooded; the electronic cabin is provided with a main control module, a Bluetooth, a motion sensing module, a visual feedback module and a power module, wherein; the main control module is electrically connected with the Bluetooth; the main control module is electrically connected with the motion sensing module, and the motion sensing module is used to sense the motion state of the float; the main control module is electrically connected with the visual feedback module, and the visual feedback module is used to send light signals according to the fish condition; the power module is used to supply power for the main control module; the mobile terminal is communicatively connected with the mobile terminal through the Bluetooth, and is used to receive fish condition event information.

Description

Technical Field

[0001] This invention relates to the field of float technology, and in particular to a fishing float system and control method. Background Technology

[0002] As a key tool for sensing fish activity during fishing, the fishing float has evolved from traditional visual floats to electronic luminous floats, and now to intelligent floats. Traditional floats rely on the angler's naked eye to observe changes in the water's surface, which has significant limitations: observation becomes significantly more difficult in low-light conditions such as at night, dusk, or rain, or when there is water reflection or wave interference; prolonged staring at the float can cause visual fatigue, leading to distraction and missed opportunities to set the hook; furthermore, traditional floats cannot record objective data on bites, making it difficult for anglers to summarize experience and improve skills.

[0003] To address the aforementioned issues, some electronic fishing floats have emerged on the market, primarily providing audible and visual cues by integrating LEDs or miniature buzzers within the float. However, existing technologies suffer from the following drawbacks: First, integrating buzzers and other sound-generating components significantly increases the float's size and weight, affecting buoyancy balance and sensitivity, thus violating fundamental float design principles. Second, their functionality is limited, typically providing only simple "whether the fish has bitten" indications, failing to differentiate between different levels of fish activity such as slight touches, tentative bites, and forceful pulls, requiring anglers to rely on experience to determine the optimal time to set the hook. Third, the cues cannot be customized, and the buzzer may disturb fish. Fourth, power consumption control is poor, resulting in short battery life, making it difficult to meet the needs of all-day fishing. Fifth, they lack data recording and statistical analysis functions, failing to generate valuable fishing data assets. Summary of the Invention

[0004] The purpose of this invention is to disclose a fishing float system and control method. The technical problems to be solved by this invention include: achieving low power consumption and long-lasting operation of intelligent floats under constraints of extremely small size and weight; accurately identifying fish activity events of different intensities in high-noise water environments and quantifying the bite intensity; realizing the collaborative work of float-based feedback and remote feedback from mobile terminals; and providing users with configurable personalized experiences and visualized fishing data analysis.

[0005] To achieve the above objectives, this invention discloses a fishing float system, including a float module and a mobile terminal, wherein: the float module includes a waterproof outer shell and an electronic compartment, the electronic compartment being disposed inside the waterproof outer shell, the waterproof outer shell being used to prevent water from entering the electronic compartment; the electronic compartment is equipped with a main control module, Bluetooth, a motion sensing module, a visual feedback module, and a power module, wherein: the main control module is electrically connected to the Bluetooth; the main control module is electrically connected to the motion sensing module, the motion sensing module being used to sense the movement state of the float; the main control module is electrically connected to the visual feedback module, the visual feedback module being used to emit light signals according to fish activity; the power module is used to supply power to the main control module; The mobile terminal communicates with the main control module via Bluetooth to receive fish activity event information. The main control module is in deep sleep mode when there are no events. When the motion sensing module detects acceleration that meets preset hardware trigger conditions, it wakes up the main control module. After being woken up, the main control module performs time-domain and frequency-domain analysis on the acceleration data, identifies the type of fish activity event, and calculates the bite intensity index. Based on the identification result, it controls the visual feedback module to emit a corresponding light signal and sends a data packet containing the event type and intensity index to the mobile terminal via Bluetooth. The mobile terminal receives the data packet, plays a corresponding preset prompt sound, and records the event information in a database for statistical analysis and visualization.

[0006] Furthermore, the motion sensing module includes a three-axis accelerometer, which has a built-in programmable interrupt generator. The triggering conditions include a first threshold interrupt and a second threshold interrupt. The first threshold interrupt corresponds to a first acceleration threshold and is used to wake up the system and enter a mild sensing mode. The second threshold interrupt corresponds to a second acceleration threshold and is used to trigger a preliminary determination of a fish activity event. The second acceleration threshold is greater than the first acceleration threshold.

[0007] Furthermore, the main control module performs time-domain and frequency-domain analysis on the acceleration data, specifically including: extracting acceleration time-domain features within a preset time window, the time-domain features including peak value, peak-to-peak value, variance, zero-crossing rate, and waveform factor; performing a fast Fourier transform on the acceleration data to extract frequency-domain energy spectrum features and calculating the ratio of low-frequency energy to high-frequency energy; and identifying fish activity event types based on the time-domain features and frequency-domain energy spectrum features using a weighted decision fusion algorithm.

[0008] Furthermore, the bite strength index is calculated using the following formula:

[0009] Where BHI is the bite strength index, A p_p For peak-to-peak acceleration, A refFor reference peak value; E low For low-frequency energy, E high Z represents the high-frequency energy; Z represents the zero-crossing rate. ref The reference zero-crossing rate is α; α, β, and γ are weighting coefficients that satisfy α+β+γ=1.

[0010] Furthermore, the main control module is also used to perform dynamic threshold adjustment: record the acceleration characteristic values ​​of the past N valid fish activity events, calculate the mean μ and standard deviation σ within the moving average window; and update the hardware trigger threshold of the motion sensing module according to the following formula:

[0011] Among them, T new The threshold value is the hardware trigger threshold, and k is a configurable sensitivity coefficient with a value range of 1.5-3.0.

[0012] Furthermore, the main control module is also used to: increase the Bluetooth transmit power from the first power level to the second power level when the Bluetooth link quality indicator RSSI is lower than the first threshold; and start the data caching mechanism when no acknowledgment frames are received from the mobile terminal for several consecutive times, temporarily store the event data in the internal flash memory, and perform batch retransmission after the link is restored.

[0013] Furthermore, the main control module is also used to: compress the acceleration waveform data in real time when the continuously collected acceleration data meets the preset data compression conditions, and transmit the compressed data to the mobile terminal in segments via Bluetooth; the compression algorithm includes differential coding and Huffman coding.

[0014] A method for controlling a fishing float, applied to a fishing float system as described above, includes the following steps: S1: The mobile terminal is in deep sleep mode, and the motion sensing module monitors acceleration via hardware interrupt. S2: When the acceleration meets the hardware triggering conditions, the motion sensing module wakes up the main control module via an interrupt; S3: The main control module collects acceleration data after wake-up, performs time-domain and frequency-domain analysis, identifies the type of fish activity event, and calculates the bite intensity index; S4: The main control module controls the visual feedback module to emit corresponding light signals based on the recognition results; S5: The main control module sends a data packet containing the event type and intensity index to the mobile terminal via Bluetooth; S6: The mobile terminal receives the data packet, plays the corresponding preset prompt tone, and records the event information to the database; S7: Mobile terminals perform statistical analysis based on historical data and generate visual reports.

[0015] Furthermore, the identification of fish activity event types in step S3 specifically includes: Extract the time-domain features of acceleration and construct a feature vector; The feature vector is input into a pre-trained classification model, which outputs an event type probability distribution; the classification model is a lightweight decision tree model or a support vector machine model.

[0016] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method.

[0017] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. An event wake-up mechanism is implemented using the hardware interrupt function of the motion sensor, enabling the system to enter a deep sleep mode. Combined with a two-level wake-up architecture, it runs at full speed only when a valid fishing event occurs, and quickly returns to sleep after the event is processed. With Bluetooth transmission, it can operate continuously for extended periods, meeting the needs of continuous fishing. 2. Breaking through the limitations of traditional threshold comparison methods, this paper innovatively introduces a multi-dimensional feature extraction and fusion decision-making mechanism. Through comprehensive analysis of time-domain feature peak value, zero-crossing rate, waveform factor, frequency-domain feature energy ratio, and spectral centroid, combined with a lightweight classification model, the recognition accuracy is significantly improved. The introduction of the bite intensity index (BHI) provides anglers with a quantitative reference, helping them to accurately grasp the timing of setting the hook. 3. The dynamic threshold adjustment mechanism enables the system to automatically adapt to background noise changes under different water conditions and weather conditions. Whether it is a still pond or a flowing river, whether it is windless weather or level 3 wind and waves, the system can maintain stable recognition performance through adaptive algorithms without the need for users to manually adjust parameters frequently. 4. By combining the visual feedback module with mobile terminals, it can adapt to different fishing scenarios. When fishing at night, you can pay attention to the float light and avoid startling the fish by turning on your phone screen. When fishing during the day or watching multiple fishing rods at the same time, you can rely on the phone's sound reminder. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a cross-sectional structural diagram of an embodiment of the present invention; Figure 2 This is a structural block diagram of an embodiment of the present invention; Figure 3 This is a flowchart of an embodiment of the present invention; Explanation of key figure labels: 1. Visual feedback module; 2. Motion sensing module; 3. Main control module; 4. Power module; 5. Bluetooth; 6. Mobile terminal; 7. Drift tail; 8. Waterproof shell; 9. Electronic compartment; 91. Electronic compartment top cover; 92. Electronic compartment bottom cover; 10. Visual feedback module. Detailed Implementation

[0020] 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.

[0021] In this invention, the terms "upper," "lower," "left," "right," "front," "rear," "top," "bottom," "inner," "outer," "middle," "vertical," "horizontal," "lateral," and "longitudinal" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. These terms are primarily for the purpose of better describing the invention and its embodiments, and are not intended to limit the indicated devices, elements, or components to having a specific orientation, or to be constructed and operated in a specific orientation.

[0022] Furthermore, in addition to indicating direction or positional relationship, some of the aforementioned terms may also have other meanings. For example, the term "above" may also be used in certain situations to indicate a dependency or connection. Those skilled in the art can understand the specific meaning of these terms in this invention based on the specific circumstances.

[0023] Furthermore, the terms "installation," "setup," "equipped with," "connection," and "linked" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral structure; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium, or an internal connection between two devices, components, or parts. Those skilled in the art can understand the specific meaning of these terms in this invention based on the specific circumstances.

[0024] Furthermore, the terms "first," "second," etc., are primarily used to distinguish different devices, components, or parts (which may be the same or different in specific type and construction), and are not intended to indicate or imply the relative importance or quantity of the indicated devices, components, or parts. Unless otherwise stated, "a plurality of" means two or more.

[0025] The technical solution of the present invention will be further described below with reference to the embodiments and accompanying drawings.

[0026] Please see Figures 1 to 2 The embodiments of this application provide a fishing float system, including a float module and a terminal module.

[0027] Specifically, the float module includes a waterproof outer shell 8 and an electronic compartment 9. The electronic compartment 9 is located inside the waterproof outer shell 8, which seals the electronic compartment 9 to prevent water from entering. One end of the waterproof outer shell 8 is provided with a float tail 7. The waterproof outer shell 8 is made of a high-transmittance, low-density composite material, specifically HDPE polymer waterproof membrane. Moreover, the waterproof outer shell 8 has a streamlined design to suit water conditions. The electronic compartment 9 has a cylindrical structure with a diameter of no more than 8mm and a length of no more than 25mm, and is completely waterproof through a precision potting process.

[0028] The electronic cabin 9 is equipped with a main control module 3, Bluetooth 5, motion sensing module 2, visual feedback module 10 and power module 4. The electronic cabin 9 includes an upper cover 91 and a lower cover 92, which are connected in a closed manner. The upper cover 91 is used to house the main control module 3, Bluetooth 5, motion sensing module 2 and visual feedback module 10, and the lower cover 92 is used to house the power module 4 to ensure its centralization.

[0029] The main control module 3 is electrically connected to the Bluetooth 5; the main control module 3 is electrically connected to the motion sensing module 2, which is used to sense the movement state of the float; the main control module 3 is electrically connected to the visual feedback module 10, which is used to emit light signals according to the fish situation; the power module 4 is used to supply power to the main control module 3, the Bluetooth 5, the motion sensing module 2 and the visual feedback module 10; the mobile terminal 6 is communicatively connected to the Bluetooth 5 and is used to receive fish situation event information.

[0030] The main control module 3 is used to enter a deep sleep mode when there are no events. When the motion sensing module 2 detects that the acceleration meets the preset hardware trigger conditions, it wakes up the main control module 3. After being woken up, the main control module 3 performs time-domain and frequency-domain analysis on the acceleration data, identifies the type of fish activity event, and calculates the bite intensity index. Based on the identification result, it controls the visual feedback module 10 to emit the corresponding light signal and sends the data packet containing the event type and intensity index to the mobile terminal 6 via Bluetooth 5. The mobile terminal 6 is used to receive the data packet, play the corresponding preset prompt sound, and record the event information in the database for statistical analysis and visualization.

[0031] More specifically, Bluetooth 5 uses a SoC chip integrating the Bluetooth 55.0 protocol. The size of Bluetooth 5 is no larger than 2.5mm × 2.5mm, and it supports multiple low-power modes. In deep sleep mode, the current can be as low as 0.6μA, and the wake-up time is as short as a few microseconds. The motion sensing module 2 uses a three-axis accelerometer with a package size no larger than 2mm × 2mm. It has a built-in programmable interrupt generator and supports multiple trigger condition configurations. It has a FIFO buffer to temporarily store data to reduce the wake-up frequency of the main controller. It supports multiple built-in functions such as free fall, motion detection, and stillness detection. This invention makes special use of its multi-level interrupt function to lay the foundation for the subsequent low-power multi-level wake-up architecture. The visual feedback module 10 uses LEDs, which are small in size, low in power consumption, and high in brightness. It should also be noted that, in order to further improve the visual effect, a light guide structure can be set at the tail of the float 7 to evenly transmit light to the visible part. The power module 4 uses a button battery, which is connected to the PCB through a flexible metal contact for easy replacement. In order to further reduce the size, a rechargeable soft-pack lithium battery can also be used, which can be used with a wireless charging coil to achieve contactless charging.

[0032] It should also be noted that the mobile terminal 6 is a smartphone, tablet, or watch with a dedicated application installed. It connects to the float module via Bluetooth 5 to enable two-way data transmission and function configuration.

[0033] The motion sensing module 2 includes a three-axis accelerometer, which has a built-in programmable interrupt generator. The triggering conditions include a first threshold interrupt and a second threshold interrupt. The first threshold interrupt corresponds to a first acceleration threshold and is used to wake up the system and enter a mild sensing mode. The second threshold interrupt corresponds to a second acceleration threshold and is used to trigger a preliminary determination of fish activity. The second acceleration threshold is greater than the first acceleration threshold.

[0034] Specifically, in deep sleep mode, only the triaxial accelerometer is active, and its built-in interrupt generator continuously monitors the acceleration value. When the acceleration exceeds a preset first threshold T1, which typically corresponds to a weak disturbance, such as a small fish touching the surface or a wave impact, the sensor wakes up the main control module 3, putting it into a light sensing mode. In this mode, the main control module 3 reads sensor data at a lower frequency to assess background noise, but does not trigger a complete event processing flow. When the acceleration exceeds a second threshold T2, which typically corresponds to a valid fish activity signal, the sensor triggers a complete event processing flow. After being woken up, the main control module 3 collects acceleration data at a higher frequency, such as 100Hz, for a fixed time window, such as 2 seconds, in preparation for in-depth analysis. The main control module 3 preprocesses the collected acceleration data, including DC removal, filtering, time-domain feature extraction, and frequency-domain feature extraction, and uses a fusion algorithm to determine the event type and intensity.

[0035] The acquired triaxial acceleration signal ax (t), a y (t) and a z (t), first calculate the magnitude of the combined acceleration:

[0036] The synthesized acceleration is preprocessed, including removing the DC component and bandpass filtering, typically retaining the 0.5-20Hz frequency band to filter out high-frequency noise and extremely low-frequency drift.

[0037] Specifically, the main control module 3 performs time-domain and frequency-domain analysis on the acceleration data, including: extracting acceleration time-domain features within a preset time window, the time-domain features including peak value, peak-to-peak value, variance, zero-crossing rate, and waveform factor; performing a fast Fourier transform on the acceleration data to extract frequency-domain energy spectrum features and calculating the ratio of low-frequency energy to high-frequency energy; and identifying fish activity event types based on the time-domain features and frequency-domain energy spectrum features using a weighted decision fusion algorithm.

[0038] Specifically, the temporal feature extraction extracts the following features within the time window [t0, t0+W], where t0 is the start time of feature extraction, t0+W is the end time of feature extraction, and the interval length is W seconds.

[0039] Time-domain characteristics include: peak value

[0040] Peak-to-peak value

[0041] variance

[0042] Zero crossing rate

[0043] Waveform factor

[0044] Among them, A peak Let A be the peak acceleration, a(t) be the acceleration function, and max() be the maximum value function; p-p σ is the peak-to-peak acceleration, min() is the minimum function; 2 Let N be the variance, N be the total number of sampling points, and a be the variance. i Let i be the acceleration value at the i-th sampling point. The variance represents the mean. A large variance indicates drastic signal fluctuations, corresponding to behaviors such as fish struggling and trembling. A small variance indicates a stable signal, corresponding to the float remaining still or moving at a constant speed. Variance is sensitive to outliers and can effectively capture sudden fish activity. Z represents the zero-crossing rate, and a... i+1 This represents the acceleration value at the (i+1)th sampling point. For indicator functions, Zero-crossing conditions; a high zero-crossing rate indicates frequent signal oscillations, corresponding to rapid shaking and struggling of the fish, while a low zero-crossing rate indicates monotonous signal changes or slow fluctuations, corresponding to steady pulling of the fish; for example, the zero-crossing rate of crucian carp taking a light bite is about 5-15 times / second, the zero-crossing rate of carp taking a strong bite is about 15-30 times / second, and the zero-crossing rate of small fish disturbing the bait with high-frequency shaking can reach 30-50 times / second; SF is the waveform factor, A RMS Let |a| be the root mean square value. i | indicates absolute value.

[0045] Wherein, root mean square A RMS The calculation formula is:

[0046] Among them, A RMS The root mean square value, It is the square of the acceleration value at the i-th sampling point.

[0047] Frequency domain feature extraction involves performing a Fast Fourier Transform (FFT) on the acceleration sequence within the time window to obtain the power spectral density P(f), and then calculating the following frequency domain features: Low-frequency energy Typically, a frequency of 0.5-3Hz is used, corresponding to the fish swimming slowly or tentatively touching the surface. Mid-frequency energy Typically, 3-8Hz is selected, corresponding to normal biting and pulling. High-frequency energy Typically, a frequency of 8-20Hz is used, corresponding to violent struggling or disengagement. Energy ratio characteristics Used to distinguish between light and strong bites Spectral centroid

[0048] Among them, E low For low-frequency energy, P(f) is the power spectral density, and f is the low-frequency energy. low1 As the lower limit of low frequency, f low2 For low-frequency upper limit, E mid For mid-frequency energy, f mid1 f is the lower limit of the intermediate frequency. mid2 For the upper limit of the intermediate frequency, E high For high-frequency energy, f high1 As the lower limit for high frequency, f high2 R is the upper limit for high frequency. low / high SC represents the energy ratio of low frequency to high frequency; SC is the centroid of the spectrum, f is the frequency, and f·P(f) is the weighted frequency. SC < 5 Hz indicates a light bite, tentative movement, and slow pulling; 5-8 Hz indicates a standard crucian carp bite; 8-12 Hz indicates a standard carp bite; 12-15 Hz indicates a violent struggle and a large fish exerting force; and SC > 15 Hz indicates a bouncing off the hook and high-frequency shaking caused by small fish disturbing the bait.

[0049] Based on the above characteristics, this invention uses a lightweight classification model for fish behavior event identification. Considering the limited computing resources of the MCU at the float end, a decision tree model or a support vector machine model is preferred.

[0050] Constructing feature vectors The feature vectors are input into a pre-trained classification model, which outputs a probability distribution of event types. This invention classifies fishery events into six types: Type 0: No event (background noise); Type 1: Slight touch (small fish pecking, water flow); Type 2: Tentative bite (light bite); Type 3: Standard bite (normal feeding); Type 4: Violent pull (sharp bite, float disappears); Type 5: Fish gets off the hook or escapes (special event).

[0051] The training data for the classification model was collected through actual fishing and generated through laboratory simulations, and labeled by domain experts. To adapt to the differences in different waters, the classification model supports incremental learning and updates on mobile devices.

[0052] To provide anglers with a more intuitive quantitative reference, this invention defines the Bite Intensity Index (BHI), with a value range of 0-100. The Bite Intensity Index is calculated using the following formula:

[0053] Where BHI is the bite strength index, A p_p For peak-to-peak acceleration, A ref For reference peak value; E low For low-frequency energy, E high Z represents the high-frequency energy; Z represents the zero-crossing rate. ref The reference zero-crossing rate; α, β, and γ are weighting coefficients that satisfy α + β + γ = 1; and A ref Z ref As a normalized reference value, it can be dynamically adjusted based on the statistical values ​​of users' historical data. Preferably, when focusing on the bite force, α is increased; when focusing on the bite frequency, γ is increased; and when distinguishing fish size or activity, β is adjusted.

[0054] In some embodiments, the bite strength index is calculated using the following formula:

[0055] Where BHI is the bite strength index, A p_p For peak-to-peak acceleration, A ref For reference peak value; E low For low-frequency energy, E high Z represents the high-frequency energy; Z represents the zero-crossing rate.ref For reference zero-crossing rate, SC ref The reference spectral centroid is α; α, β, and γ are weighting coefficients that satisfy α + β + γ + δ =1; and A ref Z ref and SC ref As a normalized reference value, it can be dynamically adjusted based on statistical values ​​from historical user data. Preferably, when focusing on the bite force, α is increased; when focusing on the bite frequency, γ is increased; and when differentiating fish size or activity, β and γ are adjusted. δ .

[0056] The main control module 3 is also used to perform dynamic threshold adjustment: record the acceleration characteristic values ​​of the past N valid fish activity events, calculate the mean μ and standard deviation σ within the moving average window; and update the hardware trigger threshold of the motion sensing module according to the following formula:

[0057] The statistical characteristics of background noise are relatively stable over a longer time scale, while fish activity signals exhibit short-term abrupt changes. Among these, T... new The threshold value is defined as the hardware trigger threshold, and k is a configurable sensitivity coefficient ranging from 1.5 to 3.0. A smaller k value results in a more sensitive system, but may increase the false alarm rate; a larger k value makes the system more robust, but may miss minor fish activity. Users can adjust the k value in real time via a mobile app to adapt to current water and weather conditions. To further improve adaptability, this invention also supports time-based adaptation: automatically lowering the threshold to increase sensitivity during periods of high fish activity, such as early morning and dusk; and automatically raising the threshold to reduce power consumption and false alarms during periods of low fish activity, such as midday and late night.

[0058] In this embodiment, since Bluetooth Low Energy has a limited transmission rate and frequent transmission of large amounts of data would significantly increase power consumption, this invention designs a real-time data compression algorithm for transmitting acceleration waveform data. The difference between adjacent sampling points is typically small, and differential coding can significantly reduce the amount of data. Let the original sequence be x0, x1, x2, ..., and the encoded sequence be d0 = x0, di = x... i -x i-1 (i≥1) For stationary signals, the difference values ​​are concentrated around 0, and can be represented with fewer bits. Statistical analysis of the difference sequence generates a Huffman tree, assigning short codewords to high-probability difference values ​​and long codewords to low-probability ones, achieving lossless compression. For the acceleration waveform of a fishing float, the compression ratio can reach 3:1 to 5:1. The compressed data is fragmented and packaged, with each packet containing 18 bytes of data and a 2-byte sequence number. The receiving end reassembles the data based on the sequence number, achieving reliable transmission.

[0059] The main control module is also used to: increase the Bluetooth transmit power from the first power level to the second power level when the Bluetooth link quality indicator RSSI is lower than the first threshold; and start the data caching mechanism when no acknowledgment frames are received from the mobile terminal for several consecutive times, temporarily store the event data in the internal flash memory, and perform batch retransmission after the link is restored.

[0060] Specifically, to further optimize power consumption, the main control module monitors the Bluetooth link quality indicator RSSI (Received Signal Strength Indicator) and packet error rate PER. When RSSI is higher than the threshold and PER is lower, the first power level (e.g., 0dBm) is used; when RSSI is lower than the threshold or PER is higher, the power level is gradually increased to the second power level (e.g., +4dBm) or even the third power level (e.g., +8dBm).

[0061] Furthermore, if no acknowledgment frame is received from the mobile terminal after sending data packets multiple times, it is determined that the link is interrupted (e.g., the mobile phone leaves the Bluetooth coverage area). At this time, the main control module activates the data caching mechanism, temporarily storing the event data in the internal flash memory (capable of storing thousands of events). After the link is restored, the historical data is retransmitted in batches to ensure that no data is lost.

[0062] See Figure 3 As shown, the present invention also discloses a fishing float control method, applied to the above-mentioned fishing float system, characterized by comprising the following steps: S1: The smart float terminal is in deep sleep mode, and the motion sensing module monitors acceleration via hardware interrupt. After system power-on initialization, the main control module configures the interrupt parameters of the motion sensing module (including the first threshold T1, the second threshold T2, and the interrupt duration). Subsequently, the main control module itself enters a deep sleep mode (current < 2μA). The motion sensing module remains operational, continuously monitoring acceleration using its built-in hardware interrupt function. S2: When the acceleration meets the hardware triggering conditions, the motion sensing module wakes up the main control module via an interrupt; Specifically, when the float's movement reaches the first threshold T1, the motion sensing module wakes up the main control module via interrupt 1. The main control module enters a light sensing mode, reading sensor data at a low sampling rate (e.g., 10Hz) and continuously assessing the background noise level. If the second threshold T2 is not reached within a preset time, the main control module re-enters deep sleep. If the second threshold T2 is reached, the complete event processing flow is triggered. S3: The main control module collects acceleration data after wake-up, performs time-domain and frequency-domain analysis, identifies the type of fish activity event, and calculates the bite intensity index; The specific steps in step S3 for identifying fish activity event types include: Extract the time-domain features of acceleration and construct the feature vector F=[A peakA p-p , σ 2 Z, SF, A RMS ] T ; Among them, A peak For the peak value, A p-p For peak-to-peak value, σ 2 Let Z be the variance, Z be the zero-crossing rate, SF be the waveform factor, and A be the zero-crossing rate. RMS It is the root mean square value; The feature vector is input into a pre-trained classification model, which outputs an event type probability distribution; the classification model is a lightweight decision tree model or a support vector machine model. The main control module collects acceleration data at a high sampling rate (e.g., 100Hz) within a preset time window (e.g., 1 second before and after, for a total of 2 seconds). The collected data is preprocessed (DC removal and filtering), and then time-domain and frequency-domain features are extracted to construct feature vectors. These feature vectors are then input into a pre-trained classification model to identify event types and calculate the bite strength index (BHI). S4: The main control module controls the visual feedback module to emit corresponding light signals based on the recognition results; The main control module queries a preset light mapping table based on the event type and BHI to determine the color and flashing mode of the RGB LEDs. Specifically, Type 1 (slight touch): blue breathing light; Type 2 (tentative bite): cyan flashing 3 times; Type 3 (standard bite): green constant light for 5 seconds; Type 4 (violent pull): red strobe; Type 5 (escape): purple gradient. The main control module outputs the corresponding waveform via PWM to drive the LEDs to emit light, achieving the first level of on-site feedback.

[0063] S5: The main control module sends a data packet containing the event type and intensity index to the mobile terminal via Bluetooth; The main control module encapsulates data packets containing the following fields: Device ID (2 bytes), Timestamp (4 bytes), Event Type (1 byte), BHI (1 byte), RSSI (1 byte), and Battery Level (1 byte). The data packets are sent to the mobile terminal via Bluetooth broadcast or connected mode. After transmission, the main control module decides, based on its configuration, whether to immediately return to deep sleep or continue in a light awareness mode awaiting user interaction.

[0064] S6: The mobile terminal receives the data packet, plays the corresponding preset prompt tone, and records the event information to the database; The mobile app receives the data packet and parses each field. Based on the event type and BHI, it queries the user-preset sound mapping table and plays the corresponding prompt sound. The prompt sounds can be customized by the user, allowing them to record personalized voice messages (such as "Gentle touch, be careful!" or "Strong touch, lift the rod quickly!") or select different music clips. The app also stores the event information in a local SQLite database, recording fields including time, type, BHI, RSSI, and battery level.

[0065] S7: Mobile terminals perform statistical analysis based on historical data and generate visual reports; The app calculates and updates statistical information in real time based on historical data. This includes: cumulative bite count (today, this week, this month); bite frequency curve (bites per hour or half hour); intensity distribution histogram (the percentage of events in different BHI intervals); active period analysis (the time of day with the most concentrated biting); and weather forecast and fishing condition correlation analysis (the impact of temperature, air pressure, and wind direction on bite frequency). Users can view these statistical charts through the app to gain a deeper understanding of fishing patterns and optimize their fishing strategies. The app also supports data export and cloud backup to create a personal fishing condition database.

[0066] It's also worth noting that the mobile app offers a wealth of personalized configuration features. Users can customize system behavior according to preferences and scenario needs, including sensitivity settings, lighting settings, sound settings, data statistics, and firmware upgrades. Sensitivity settings allow users to adjust the sensitivity coefficient 'k' in the dynamic threshold using a slider; the left side of the slider represents "sensitive," and the right side represents "robust." Lighting settings allow users to select RGB colors and flashing modes for six event types, with preview functionality supported. Sound settings allow users to select a notification sound for each event type, supporting selection from system ringtones or importing custom audio from files. A "quiet period" can be set, disabling sound alerts and only keeping the lights on during this time. Data statistics allow users to view historical data charts and filter by date, fish species (manual labeling required), and fishing spot. Firmware upgrades support OTA updates via Bluetooth, updating the float terminal's main control firmware, including optimizing classification model parameters and adding new features.

[0067] This embodiment achieves the core functions of a smart float while maintaining a low cost, and can meet the needs of most recreational fishing scenarios.

[0068] This application also discloses a computer-readable storage medium having a computer program stored thereon, characterized in that the computer program, when executed by a processor, implements the steps of the method described above.

[0069] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0070] In the above embodiments, the descriptions of each embodiment have different focuses, and some embodiments are not described in detail. For details regarding the above, please refer to the relevant descriptions in other embodiments.

[0071] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the shown or discussed mutual couplings or direct couplings or communication connections may be through some service interfaces; indirect couplings or communication connections between apparatuses or units may be electrical or other forms.

[0072] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0073] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0074] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0075] The above are merely exemplary embodiments of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Those skilled in the art will readily conceive of other embodiments of this disclosure upon considering the specification and the disclosure of practical truths. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described in this disclosure.

[0076] The technical means disclosed in this invention are not limited to those disclosed in the above embodiments, but also include technical solutions composed of any combination of the above technical features. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of this invention, and these improvements and modifications are also considered within the scope of protection of this invention.

Claims

1. A fishing float system, characterized in that, Includes a float module and a mobile terminal (6), wherein; The float module includes a waterproof shell (8) and an electronic compartment (9). The electronic compartment (9) is located inside the waterproof shell (8). The waterproof shell (8) is used to prevent water from entering the electronic compartment (9). The electronic compartment (9) is equipped with a main control module (3), Bluetooth (5), a motion sensing module (2), a visual feedback module (10), and a power module (4). The main control module (3) is electrically connected to the Bluetooth (5); The main control module (3) is electrically connected to the motion sensing module (2), and the motion sensing module (2) is used to sense the motion state of the float; The main control module (3) is electrically connected to the visual feedback module (10), and the visual feedback module (10) is used to emit light signals according to the fish situation; The power module (4) is used to supply power to the main control module (3); The mobile terminal (6) is connected to the mobile terminal (6) via Bluetooth (5) to receive fish activity information; The main control module (3) is used to be in deep sleep mode when there is no event; when the motion sensing module (2) detects that the acceleration meets the preset hardware triggering conditions, the main control module (3) is woken up; after being woken up, the main control module (3) performs time domain and frequency domain analysis on the acceleration data, identifies the type of fish event and calculates the bite intensity index; according to the identification result, the visual feedback module (10) is controlled to emit the corresponding light signal, and the data packet containing the event type and intensity index is sent to the mobile terminal (6) via Bluetooth (5); The mobile terminal (6) is used to receive the data packet, play the corresponding preset prompt sound, and record the event information to the database for statistical analysis and visualization.

2. The fishing float system according to claim 1, characterized in that, The motion sensing module (2) includes a three-axis accelerometer, which has a built-in programmable interrupt generator. Its triggering conditions include a first threshold interrupt and a second threshold interrupt. The first threshold interrupt corresponds to a first acceleration threshold and is used to wake up the system and enter a mild sensing mode. The second threshold interrupt corresponds to a second acceleration threshold and is used to trigger a preliminary determination of fish activity. The second acceleration threshold is greater than the first acceleration threshold.

3. A fishing float system according to claim 1, characterized in that, The main control module (3) performs time-domain and frequency-domain analysis on the acceleration data, specifically including: extracting the acceleration time-domain features within a preset time window, the time-domain features including peak value, peak-to-peak value, variance, zero-crossing rate, and waveform factor; performing a fast Fourier transform on the acceleration data, extracting the frequency-domain energy spectrum features, and calculating the ratio of low-frequency energy to high-frequency energy; and identifying the fish activity event type based on the time-domain features and frequency-domain energy spectrum features using a weighted decision fusion algorithm.

4. A fishing float system according to claim 1, characterized in that, The bite strength index is calculated using the following formula: ； Where BHI is the bite strength index, A p_p For peak-to-peak acceleration, A ref For reference peak value; E low For low-frequency energy, E high Z represents the high-frequency energy; Z represents the zero-crossing rate. ref The reference zero-crossing rate is α; α, β, and γ are weighting coefficients that satisfy α+β+γ=1.

5. A fishing float system according to claim 1, characterized in that, The main control module (3) is also used to perform dynamic threshold adjustment: record the acceleration characteristic values ​​of the past N effective fish events, and calculate the mean μ and standard deviation σ within the moving average window; The hardware trigger threshold of the motion sensing module is updated according to the following formula: ； Among them, T new The threshold value is the hardware trigger threshold, and k is a configurable sensitivity coefficient with a value range of 1.5-3.

0.

6. A fishing float system according to claim 2, characterized in that, The main control module (3) is also used to: when the Bluetooth (5) link quality indicator RSSI is lower than the first threshold, increase the Bluetooth (5) transmission power from the first power level to the second power level; when no acknowledgment frames are received from the mobile terminal (6) for several consecutive times, start the data caching mechanism, temporarily store the event data in the internal flash memory, and perform batch retransmission after the link is restored.

7. A fishing float system according to claim 2, characterized in that, The main control module (3) is also used to: compress the acceleration waveform data in real time when the continuously collected acceleration data meets the preset data compression conditions, and transmit the compressed data to the mobile terminal (6) in segments via Bluetooth (5); the compression algorithm includes differential coding and Huffman coding.

8. A method for controlling a fishing float, applied to the fishing float system as described in any one of claims 1-7, characterized in that, Includes the following steps: S1: The mobile terminal (6) is in deep sleep mode, and the motion sensing module (2) monitors acceleration by hardware interrupt. S2: When the acceleration meets the hardware triggering conditions, the motion sensing module (2) wakes up the main control module (3) through an interrupt; S3: The main control module (3) collects acceleration data after wake-up, performs time-domain and frequency-domain analysis, identifies fish event types and calculates the bite intensity index; S4: The main control module (3) controls the visual feedback module (10) to emit corresponding light signals according to the recognition results; S5: The main control module (3) sends a data packet containing the event type and intensity index to the mobile terminal (6) via Bluetooth (5); S6: The mobile terminal (6) receives the data packet, plays the corresponding preset prompt tone, and records the event information to the database; S7: The mobile terminal (6) performs statistical analysis based on historical data and generates a visual report.

9. A method for controlling a fishing float according to claim 8, characterized in that, The specific steps in step S3 for identifying fish activity event types include: Extract the time-domain features of acceleration and construct a feature vector; The feature vector is input into a pre-trained classification model, which outputs an event type probability distribution; the classification model is a lightweight decision tree model or a support vector machine model.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 8-9.

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