Anti-drowning intelligent swimming cap and system thereof

Abstract

The invention belongs to the technical field of swimming tools, and particularly relates to an anti-drowning intelligent swimming cap and a system thereof, and the anti-drowning intelligent swimming cap comprises a cap body, and a detection module, a processing module, a communication module, a power supply module and a waterproof packaging structure which are integrated in the cap body. The sensors are integrated with the swimming cap, resistance brought by additional equipment is reduced, the high-elasticity fabric is attached to the head, falling caused by water flow impact is avoided, the swimming comfort degree is improved, meanwhile, the drowning state is judged by comprehensively monitoring heart rate, blood oxygen, posture and water depth data and combining a preset algorithm, the judgment accuracy is greatly improved, and the drowning prevention effect is achieved. And the NB-IoT remote communication module is adopted, relay does not need to be depended on short-distance equipment, alarm information can be directly sent to a monitoring platform, the timeliness of transmission of the alarm information is ensured, and time is won for rescue.

Description

Technical Field

[0001] This invention belongs to the field of swimming equipment technology, specifically relating to a smart swimming cap and system for preventing drowning. Background Technology

[0002] Swimming is a healthy sport, and a swimming cap is an essential piece of equipment for swimming. It can prevent ear congestion and protect the head, while effectively reducing the damage to hair caused by chlorinated pool water, as well as reducing drag and increasing swimming speed. In existing technologies, ordinary swimming caps only have basic functions such as hair protection and drag reduction, without any detection or alarm functions. Although some smart wearable devices, such as fitness trackers and watches, can detect heart rate and blood oxygen, their detection accuracy is low in swimming scenarios because the wearing position (wrist) is easily affected by water flow. Moreover, most of them are not waterproof enough to meet the needs of prolonged underwater use. Dedicated anti-drowning devices mostly use single posture detection or water depth detection. If they only determine whether the user has been stationary underwater for a long time to trigger an alarm, they lack monitoring of the human body's physiological state (heart rate, blood oxygen), which can easily lead to false alarms or missed alarms. At the same time, the communication between existing devices and platforms mostly relies on Bluetooth short-range connection with mobile phones. If the user is far away from the mobile phone, the alarm information cannot be transmitted in time. In view of this, a smart anti-drowning swimming cap is proposed. Summary of the Invention

[0003] The purpose of this invention is to provide a smart swimming cap and system for preventing drowning. It can judge the drowning state by comprehensively monitoring heart rate, blood oxygen, posture and water depth data, combined with a preset algorithm, which greatly improves the accuracy of judgment and reduces the occurrence of false alarms and missed alarms. Furthermore, it adopts an NB-IoT long-distance communication module, which does not rely on short-range devices for relay, and can directly send alarm information to the monitoring platform, ensuring the timeliness of alarm information transmission and buying time for rescue.

[0004] The specific technical solution adopted by this invention is as follows:

[0005] A smart swimming cap and system for preventing drowning, comprising a cap body, and a detection module, a processing module, a communication module, a power module and a waterproof encapsulation structure integrated inside the cap body;

[0006] The detection module includes a heart rate sensor, a blood oxygen sensor, a six-axis attitude sensor (accelerometer + gyroscope), and a pressure sensor;

[0007] The processing module uses an MCU, which is connected to the detection module, communication module, and power module respectively. It is used to receive heart rate, blood oxygen, posture, and water depth data transmitted by the detection module, and to determine whether the user is drowning by using a preset algorithm (such as when the heart rate exceeds the normal range, the blood oxygen saturation is below the threshold, the posture is abnormal, and the water depth exceeds the safe value for a certain period of time).

[0008] The communication module uses a waterproof NB-IoT module, which is connected to the processing module. When the processing module determines that the user is drowning, it sends alarm information, including the user's identity information, real-time location, heart rate, blood oxygen, water depth and attitude, to the preset monitoring platform.

[0009] The power module uses a small rechargeable lithium battery to power each module.

[0010] Furthermore, the heart rate sensor and blood oxygen sensor are used to collect the user's heart rate and blood oxygen saturation data in real time, the six-axis attitude sensor is used to detect the user's swimming posture (such as whether there is abnormal tilting or stillness), and the pressure sensor is used to detect the current water depth data.

[0011] Furthermore, the rear of the cap has an embedded magnetic charging interface (including a waterproof magnetic core and contacts) that is electrically connected to the power module, and a waterproof cover is provided at the port of the magnetic charging interface.

[0012] Furthermore, the waterproof encapsulation structure provides an overall seal for the detection module, processing module, communication module, and power module, employing waterproof adhesive potting and sealing ring design, with heat-melt sealing treatment applied to the seams of the cap body.

[0013] A drowning prevention system includes a monitoring platform, which is used to receive alarm information sent by a communication module and display the alarm information.

[0014] A drowning prevention system includes the following steps:

[0015] S1. When in use, the user wears the smart swimming cap. The power module supplies power to each module. The heart rate sensor, blood oxygen sensor, six-axis attitude sensor and pressure sensor in the detection module collect relevant data in real time and transmit the data to the processing module.

[0016] S2. The processing module analyzes and processes the received data and determines whether the user is drowning based on a preset algorithm.

[0017] S3. If drowning is determined, the processing module controls the communication module to immediately send an alarm message to the monitoring platform. After receiving the alarm message, the monitoring platform can take timely rescue measures.

[0018] The technical effects achieved by this invention are as follows:

[0019] In this invention, the sensors are integrated with the swimming cap, reducing the resistance caused by additional equipment. The highly elastic fabric fits the head snugly, preventing it from slipping off due to water flow and improving swimming comfort. Simultaneously, by comprehensively monitoring heart rate, blood oxygen, posture, and water depth data, and combining this with a preset algorithm through data fusion, the drowning status is determined, significantly improving the accuracy of the assessment and reducing false alarms and missed alarms. Furthermore, the use of an NB-IoT long-range communication module eliminates the need for short-range relay devices, allowing alarm information to be directly sent to the monitoring platform, ensuring timely alarm transmission and buying time for rescue. The purpose of data fusion is to collaboratively process information from different sensors, different times, and different dimensions, combining it to produce more accurate, complete, and reliable information than any single sensor. This solution adopts a hierarchical, hybrid fusion architecture, divided into three levels from low to high: data-level fusion, feature-level fusion, and decision-level fusion.

[0020] This invention uses magnetic charging, eliminating the need for plugging and unplugging. Combined with a fully waterproof enclosure, the waterproof lifespan is extended to more than 3 years (the average lifespan of existing pluggable interfaces is 1 year). Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the circuit structure of the present invention;

[0022] Figure 2 This is a flowchart of the operation of the multi-sensor fusion drowning prevention system of the present invention;

[0023] Figure 3 This is a schematic diagram of the swimming cap in this invention.

[0024] The attached diagram lists the components represented by each number as follows:

[0025] 101. Cap body; 102. Blood oxygen sensor; 103. Heart rate sensor; 104. Pressure sensor; 105. Six-axis attitude sensor. Detailed Implementation

[0026] To make the objectives and advantages of this invention clearer, the invention will be specifically described below with reference to embodiments. It should be understood that the following text is merely used to describe one or more specific embodiments of the invention and does not strictly limit the scope of protection specifically claimed by the invention.

[0027] like Figure 1-3 As shown, a smart swimming cap and system for preventing drowning includes a cap body 101, and a detection module, a processing module, a communication module, a power module and a waterproof encapsulation structure integrated inside the cap body 101.

[0028] The detection module includes a heart rate sensor 103, a blood oxygen sensor 102, a six-axis attitude sensor 105 (accelerometer + gyroscope) and a pressure sensor 104;

[0029] The processing module uses an MCU, which is connected to the detection module, communication module, and power module respectively. It is used to receive heart rate, blood oxygen, posture, and water depth data transmitted by the detection module and determine whether the user is drowning by using a preset algorithm (such as when the heart rate exceeds the normal range, the blood oxygen saturation is below the threshold, the posture is abnormal, and the water depth exceeds the safe value for a certain period of time).

[0030] The communication module uses a waterproof NB-IoT module, which is connected to the processing module. When the processing module determines that the user is drowning, it sends alarm information, including the user's identity information, real-time location, heart rate, blood oxygen, water depth and attitude, to the preset monitoring platform.

[0031] The power module uses a small rechargeable lithium battery to power each module.

[0032] Heart rate sensor 103 and blood oxygen sensor 102 are used to collect the user's heart rate and blood oxygen saturation data in real time. Six-axis attitude sensor 105 is used to detect the user's swimming posture (such as whether there is abnormal tilting or stillness). Pressure sensor 104 is used to detect the current water depth data.

[0033] The rear of the cap 101 has an embedded magnetic charging interface (including a waterproof magnetic core and contacts) that is electrically connected to the power module. The magnetic charging interface port is equipped with a waterproof cover. When used with a dedicated magnetic charger, the circuit connection is achieved through magnetic attraction during charging. When not charging, the interface is sealed by the waterproof cover.

[0034] The waterproof encapsulation structure provides a complete seal for the detection module, processing module, communication module, and power module. It employs waterproof adhesive potting and sealing ring design, and the 101 seam of the cap body is heat-fused to ensure that the equipment can operate normally underwater.

[0035] A drowning prevention system includes a monitoring platform, which is used to receive alarm information sent by a communication module and display the alarm information.

[0036] A drowning prevention system, characterized by comprising the following steps:

[0037] S1. When in use, the user wears the smart swimming cap. The power module supplies power to each module. The heart rate sensor 103, blood oxygen sensor 102, six-axis attitude sensor 105 and pressure sensor 104 in the detection module collect relevant data in real time and transmit the data to the processing module.

[0038] S2. The processing module analyzes and processes the received data and determines whether the user is drowning based on a preset algorithm.

[0039] S3. If drowning is determined, the processing module controls the communication module to immediately send an alarm message to the monitoring platform. After receiving the alarm message, the monitoring platform can take timely rescue measures.

[0040] The working principle of this invention is as follows: When in use, the user wears the smart swimming cap, the power module supplies power to each module, and the heart rate sensor 103, blood oxygen sensor 102, six-axis attitude sensor 105 and pressure sensor 104 in the detection module collect the wearer's heart rate, blood oxygen, attitude and water depth data in real time, and transmit the data to the processing module. The processing module analyzes and processes the received data, and determines whether the user is drowning by performing data fusion according to a preset algorithm. If drowning is determined, the processing module controls the communication module to immediately send an alarm message to the monitoring platform. After receiving the alarm message, the monitoring platform can take timely rescue measures.

[0041] Meanwhile, the processing module can monitor the power module's battery level in real time. When the battery level is lower than the set value, it controls the communication module to send a low battery reminder to the platform so that the user can charge in time. When charging, simply remove the waterproof cover and attach the magnetic charger to the interface to complete the charging process. After charging is complete, replace the waterproof cover to maintain the waterproof performance.

[0042] The multi-sensor data fusion method is as follows:

[0043] The purpose of data fusion is to collaboratively process information from different sensors, different times, and different dimensions to create information that is more accurate, complete, and reliable than any single sensor. This solution adopts a hierarchical and hybrid fusion architecture, which is divided into three levels from low to high: data-level fusion, feature-level fusion, and decision-level fusion.

[0044] The first level is data-level fusion, which mainly operates at the signal level. It processes raw data, overcomes inherent sensor limitations, and lays the foundation for subsequent analysis. Specifically, addressing the issue of motion interference affecting the heart rate sensor 103 and blood oxygen sensor 102 (PPG) underwater, the data from the three-axis accelerometer and gyroscope of the six-axis attitude sensor 105 are used as reference noise sources and input into a Normalized Least Mean Square (NLMS) adaptive filter. This filter dynamically adjusts its coefficients to generate an estimate that highly approximates the motion noise waveform in the PPG signal. The value is subtracted from the original PPG signal in real time to output a purified signal that can be used to accurately calculate heart rate (HR) and blood oxygen saturation (SpO2). At the same time, the attitude sensor data itself is processed by a Kalman filter algorithm to fuse the gravitational field direction measured by the accelerometer and the angular velocity measured by the gyroscope to compensate for gyroscope drift and accurately calculate the real-time attitude angle of the swimming cap (i.e., the head) in three-dimensional space. The data streams of all sensors are synchronized and aligned through hardware timestamps and software interpolation algorithms to ensure that all data points are on a unified time reference.

[0045] The second level is feature-level fusion, which aims to extract physically meaningful feature indicators from the preprocessed synchronous data stream and identify complex events through correlation analysis. This level first extracts features in parallel from the data of various sensors: heart rate variability (HRV) and blood oxygenation trend are extracted from the purified PPG signal; peak detection, frequency domain transformation, and machine learning classifiers are used from the calculated attitude angles and raw data from the six-axis attitude sensor 105 to identify swimming stroke types, calculate stroke frequency, body roll angle, and instantaneous impact features of turns and starts; and real-time water depth and single immersion duration are calculated from the pressure sensor 104 data. Subsequently, a rule-based state machine model is used to logically correlate the above cross-domain features to define complex swimming events. This multi-feature fusion event recognition method greatly improves the accuracy of state judgment.

[0046] The third level is the decision-making level fusion, which is the highest level of the entire system. It is responsible for integrating all feature and event information to conduct global analysis and decision-making. This level adopts multi-threshold weighted decision-making, expert systems, and machine learning regression models. It has formulated graded early warning rules: when only one of the three features (physiological, movement, and environmental) is abnormal, a local slight alert is triggered; when any two are abnormal at the same time, the risk level is determined to be increased, and a local strong alarm is triggered; when all three are abnormal, it is determined to be extremely high risk, and the alarm information is immediately uploaded to the cloud. The cloud platform can perform secondary fusion verification, such as combining data or video streams from other equipment in the pool, and finally push accurate alarm information to the lifeguard terminal.

[0047] This progressive, coarse-to-refined data fusion strategy effectively solves the core technical challenges of high data noise, complex features, and high false alarm rates in underwater motion monitoring. It realizes the transformation from low-level raw data to high-level semantic information and intelligent decision-making, significantly improving the reliability, practicality, and value of smart swimming cap products.

[0048] The above description is merely a preferred embodiment of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention. Structures, devices, and operating methods not specifically described or explained in this invention are implemented according to conventional methods in the art unless otherwise specified or limited.

Claims

1. A smart swimming cap for preventing drowning, characterized in that: It includes a cap body (101), and a detection module, processing module, communication module, power module and waterproof encapsulation structure integrated inside the cap body (101); The detection module includes a heart rate sensor (103), a blood oxygen sensor (102), a six-axis attitude sensor (105) (accelerometer + gyroscope) and a pressure sensor (104). The processing module uses an MCU, which is connected to the detection module, communication module, and power module respectively. It is used to receive heart rate, blood oxygen, posture, and water depth data transmitted by the detection module, and to determine whether the user is drowning by using a preset algorithm (such as when the heart rate exceeds the normal range, the blood oxygen saturation is below the threshold, the posture is abnormal, and the water depth exceeds the safe value for a certain period of time). The communication module uses a waterproof NB-IoT module, which is connected to the processing module. When the processing module determines that the user is drowning, it sends alarm information, including the user's identity information, real-time location, heart rate, blood oxygen, water depth and attitude, to the preset monitoring platform. The power module uses a small rechargeable lithium battery to power each module.

2. The smart swimming cap for preventing drowning according to claim 1, characterized in that: The heart rate sensor (103) and blood oxygen sensor (102) are used to collect the user's heart rate and blood oxygen saturation data in real time. The six-axis attitude sensor (105) is used to detect the user's swimming posture (such as whether there is abnormal tilting or stillness). The pressure sensor (104) is used to detect the current water depth data.

3. The smart swimming cap for preventing drowning according to claim 1, characterized in that: The rear of the cap (101) has an embedded magnetic charging interface (including a waterproof magnetic core and contacts) that is electrically connected to the power module, and a waterproof cover is provided at the port of the magnetic charging interface.

4. The smart swimming cap for preventing drowning according to claim 1, characterized in that: The waterproof encapsulation structure provides an overall seal for the detection module, processing module, communication module, and power module. It employs waterproof glue potting and sealing ring design, and the seam of the cap (101) is heat-sealed.

5. A drowning prevention system, characterized in that: The system includes a monitoring platform and the anti-drowning smart swimming cap as described in any one of claims 1-4. The monitoring platform is used to receive alarm information sent by the communication module and display the alarm information.

6. The anti-drowning system according to claim 5, characterized in that: Includes the following steps: S1. When in use, the user wears the smart swimming cap, the power module supplies power to each module, and the heart rate sensor (103), blood oxygen sensor (102), six-axis attitude sensor (105) and pressure sensor (104) in the detection module collect relevant data in real time and transmit the data to the processing module. S2. The processing module analyzes and processes the received data and determines whether the user is drowning based on a preset algorithm. S3. If drowning is determined, the processing module controls the communication module to immediately send an alarm message to the monitoring platform. After receiving the alarm message, the monitoring platform can take timely rescue measures.

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