Multi-mode human body existence radar monitoring system

Abstract

The utility model relates to a multi-mode human body existence radar monitoring system. The system is composed of a radar sensor, an infrared sensor, a visual sensor, a sound sensor and a pressure sensor, data acquisition and processing technologies of various sensors are combined, high-precision monitoring of existence and activity of a human body can be achieved, and automatic control of equipment is achieved through an intelligent control feedback mechanism. The system has the advantages that high integration level and multi-sensor complementation are achieved, higher monitoring accuracy and reliability can be provided in different environments, real-time human body dynamic monitoring can be provided by integrating a multi-modal data source and a radar system, and important information such as the motion trail, the position change and the respiratory rate of a human body can be accurately captured. Therefore, richer and more accurate sensing capability is provided for applications such as smart home, intelligent security and protection, health monitoring and the like.

Description

TECHNICAL FIELD

[0001] The utility model relates to radar monitoring system technical field, concretely is a multimodal human existence radar monitoring system. BACKGROUND

[0002] Radar monitoring systems usually rely on millimeter wave radars, especially FMCW (Frequency Modulated Continuous Wave) radars. Millimeter wave radars can detect the reflection signals of human bodies by sending and receiving high-frequency electromagnetic waves. The electromagnetic waves emitted by the radar are reflected back after encountering human bodies, and the radar receiver calculates the distance, speed and other motion parameters of the object according to the time delay and frequency shift of the signal; the radar is not affected by environmental conditions such as light and weather, and can penetrate certain walls or obstacles, so it is suitable for 24-hour all-weather monitoring.

[0003] Although radars can detect human motion, their ability to recognize and analyze complex human movements is still weak.

[0004] At the same time, the existing radar systems usually face the problem of insufficient spatial resolution, which means that they may have difficulty in accurately distinguishing different targets in complex environments, especially in the presence of multiple targets or obstructions, with low recognition accuracy. SUMMARY

[0005] The utility model aims to provide a multimodal human existence radar monitoring system to solve the above-mentioned problems.

[0006] To achieve the above-mentioned purpose, the utility model provides the following technical scheme:

[0007] A multimodal human existence radar monitoring system, comprising: a radar sensor for data acquisition and transmission;

[0008] an infrared sensor for infrared data acquisition and transmission;

[0009] a visual sensor for infrared data acquisition and transmission;

[0010] a sound sensor for infrared data acquisition and transmission;

[0011] a pressure sensor for infrared data acquisition and transmission;

[0012] a receiving end for data reception after transmission, extraction of predetermined features according to application requirements, storage of data after transmission in a storage module, and feedback of real-time monitoring data to a display module;

[0013] digital signal conversion after data reception by the receiving end, feedback to a coordinated control module for intelligent device control after processing by an integrated module.

[0014] The data collection and processing technology combined with multiple sensors can achieve high-precision monitoring of human presence and activity, and realize automatic control of the device through intelligent control feedback mechanism. The advantage of the system lies in high integration and multi-sensor complementation, which can provide higher monitoring accuracy and reliability in different environments.

[0015] According to an aspect of the present application, the infrared sensor collects data by detecting infrared radiation. It converts the sensed infrared signal into an electrical signal, which is then processed and transmitted;

[0016] The visual sensor is used to collect image or video data, capture infrared spectrum, and send data out through predetermined processing and transmission methods;

[0017] The sound sensor collects sound signals, which need to be converted into digital signals through audio processing

[0018] The pressure sensor converts the detected pressure value into a digital or analog signal;

[0019] The receiving end system analyzes the data, including the correlation between pressure changes and infrared signals, performs fault diagnosis, temperature compensation, or is used for environmental monitoring.

[0020] The system provides rich environmental information to the receiving end through the combination of multiple sensors. The signals of these sensors can be processed and analyzed to realize functions such as fault diagnosis, temperature compensation, and environmental monitoring. In modern automation, intelligent devices, industrial control, environmental monitoring, and other fields, the application of sensors is becoming more and more widespread, and their collaborative work can provide comprehensive and real-time data support for the system, ensuring efficient and safe operation of the system.

[0021] According to an aspect of the present application, the infrared data is transmitted to the integrated unit through wired or wireless communication protocol; the transmitted infrared data is temperature and heat distribution information, which is transmitted to the receiving end through the transmission system.

[0022] According to an aspect of the present application, image data is transmitted through image transmission protocol.

[0023] According to an aspect of the present application, the receiving end first needs to decode the received data, and for image or video data, decoding operation is performed;

[0024] First, data filtering and denoising are performed: noise interference may occur during transmission, and the receiving end uses a filter to perform denoising processing on the data to ensure data quality;

[0025] According to application requirements, specific features are extracted and further analyzed. Signal processing algorithms, pattern recognition, and data fusion are used;

[0026] Data storage: the processed data is stored in the database, recording historical data.

[0027] The receiving end from receiving raw data to carry out denoising, feature extraction, analysis and processing to the final storage of the entire workflow. This process has a wide range of applications in image, video analysis, signal processing and other application scenarios.

[0028] Compared with the prior art, the utility model has the advantages that:

[0029] The multi-modal human existence radar system combines various sensing technologies such as millimeter wave radar, infrared sensor, visual sensor and pressure sensor, and effectively overcomes the defects of single sensor through data fusion method. The radar wave is not affected by environmental temperature, humidity, illumination and other conditions, and can realize all-weather and omnidirectional monitoring. BRIEF DESCRIPTION OF DRAWINGS

[0030] Figure 1 It is a principle schematic view of the multi-modal human existence radar monitoring system. DETAILED DESCRIPTION

[0031] In the following description, a large number of specific details are given in order to provide a more thorough understanding of the present application. However, it is obvious to those skilled in the art that the present application can be implemented without one or more of these details. In other examples, some technical features known in the art are not described in order not to obscure the present application.

[0032] Applicant believes that the traditional monitoring system mostly relies on single sensing technology, such as infrared sensor, ultrasonic sensor, etc. These technologies are easily disturbed in some environments. For example, the infrared sensor is greatly affected by environmental temperature changes, the ultrasonic sensor is strongly affected by sound reflection, and the radar can detect the movement of the human body, but its recognition and analysis ability for complex human body actions is still weak. At the same time, the existing radar system usually faces the problem of insufficient spatial resolution, which means that they may have difficulty in accurately distinguishing different targets in complex environments, especially in the case of multiple targets or obstructions, the recognition accuracy is low.

[0033] To this end, the applicant designs a multi-modal human presence radar monitoring system composed of radar sensors, infrared sensors, visual sensors, sound sensors and pressure sensors, which combines data acquisition and processing technologies of multiple sensors, can realize high-precision monitoring of human presence and activity, and realizes automatic control of equipment through intelligent control feedback mechanism. The advantage of the system is high integration and multi-sensor complementation, which can provide higher monitoring accuracy and reliability in different environments, and through the integration of multi-modal data sources, the radar system can provide real-time human dynamic monitoring, accurately capture important information such as human motion trajectory, position change and breathing frequency. This provides more rich and accurate sensing capabilities for smart home, intelligent security, health monitoring and other applications.

[0034] The multi-modal human presence radar monitoring system disclosed by the utility model relates to a kind of multi-modal human presence radar monitoring system, in practical application, as shown in Figure 1 As shown, it comprises radar sensor, infrared sensor, visual sensor, sound sensor and pressure sensor;Radar uses millimeter wave radar, infrared sensor uses thermal imaging to detect human heat, to further improve the accuracy of human detection, especially in the weak radar signal scene. Visual sensor (camera): through computer vision analysis of human contour or behavior in image, to identify and track the dynamic of human. Sound sensor: using sound wave analysis, detecting human voice or breathing and other physiological activities. Pressure sensor: detect the pressure change of human in mattress, floor and other places, to confirm whether there is human presence or not in sleep state.

[0035] The system monitors whether there is human presence in target area in real time. For example, in smart home, the radar system can detect whether there is personnel in the room, and automatically adjust the light or air conditioner. The system can calculate the accurate position of human through radar signal reflection, and can be dynamically tracked, suitable for personnel monitoring in security monitoring or industrial environment. Combined with the data of multi-modal sensors, the specific actions of human (such as standing, sitting, walking, etc.) can be analyzed, and abnormal behaviors (such as falling, sudden stagnation, etc.) can be identified, for health care of the elderly or intelligent medical treatment. The system can also monitor the vital signs of human, such as breathing rate, heart rate, etc., commonly used in medical monitoring, remote health management and other fields.

[0036] Optimize computing performance and efficiency by combining different types of processors such as CPU, GPU, TPU (Tensor Processing Unit). Combine hardware specifically designed for specific tasks (such as artificial intelligence or image processing) with general-purpose computing units to improve the overall performance and energy efficiency of the system. Such as Google's TPU, NVIDIA's A100, Apple's M series chip

[0037] In actual use process: infrared sensor transmits after infrared data acquisition;

[0038] Infrared sensors collect data by detecting infrared radiation, such as heat or changes in temperature of objects. They convert the sensed infrared signals into electrical signals, which are then processed and transmitted. After the sensor detects infrared radiation, it converts these signals into digital or analog signals that can be processed. The infrared data is transmitted to a data processing system through wired or wireless communication protocols (such as I2C, SPI, Bluetooth, Wi-Fi, etc.). The transmitted infrared data is information such as temperature, heat distribution, etc. The data is transmitted through the transmission system to the receiving end (microcontroller, computer, or embedded system) for analysis, filtering, denoising, and analysis. After the visual sensor collects infrared data, it is transmitted

[0039] Visual sensors (such as infrared cameras or infrared scanners) are usually used to collect image or video data, capture infrared spectra (such as thermal imaging), and transmit data through certain processing and transmission methods. Visual sensors generate images or videos by capturing information in the infrared band. These infrared imaging data reflect the temperature distribution and thermal characteristics of objects. Image data is transmitted through image transmission protocols (such as MJPEG, H.264 compression format, or through network protocols such as HTTP, RTSP). The received data is processed through decoding, denoising, color adjustment, etc. In some applications, machine learning algorithms are also used for target detection, temperature anomaly detection, etc.

[0040] Sound sensors collect infrared data after transmission;

[0041] Sound sensors (such as microphones or ultrasonic sensors) collect sound signals, not direct infrared data. Sound sensors usually do not directly collect infrared data. However, ultrasonic sensors can measure temperature, distance, or other types of data by emitting ultrasonic waves and receiving echoes. Sound sensors collect sound signals, which usually need to be converted into digital signals through audio processing. Data transmission: sound signals are transmitted through transmission protocols (such as PCM, I2S, Wi-Fi, etc.). Data processing: audio data is processed through signal processing algorithms (such as filtering, noise suppression, echo cancellation, etc.) for analysis or triggering other applications.

[0042] Pressure sensors collect infrared data after transmission;

[0043] Pressure sensors are mainly used to sense pressure changes, but in some applications, they can also be combined with infrared technology (such as monitoring the temperature of gases or liquids through pressure sensors). In these scenarios, the sensor combines infrared data collection for sensing.

[0044] The pressure sensor converts the detected pressure value (represented by voltage changes) into a digital or analog signal, combined with infrared data (e.g., temperature changes). The collected pressure and infrared data are transmitted to the data processing center through wired or wireless transmission protocols (such as CAN, I2C, LoRa, etc.).

[0045] The receiving end system analyzes the data, including the correlation between pressure changes and infrared signals, for fault diagnosis, temperature compensation, or environmental monitoring applications.

[0046] After data transmission, the receiving end system needs to further process these data. The processing flow includes the following steps:

[0047] Data reception and decoding: The receiving end first needs to decode the received data (for example, analog signals obtained from sensors need to be converted into digital signals through ADC (analog-to-digital converter)). For image or video data, decoding operations are usually required.

[0048] Data filtering and denoising: During transmission, there may be noise interference, and the receiving end often uses filters (such as low-pass filters) to denoise the data to ensure data quality.

[0049] Feature extraction and analysis: According to application requirements, specific features (such as temperature hotspots in images, frequency spectrum analysis of sound signals, etc.) may need to be extracted and further analyzed. Signal processing algorithms, pattern recognition, data fusion, etc. can be used.

[0050] Data storage: The processed data may be stored in a database for subsequent query, analysis, or historical data recording.

[0051] Decision and control: Based on the analysis results, the system may make decisions or trigger specific actions. For example, if the temperature detected by the infrared sensor is too high, the system will trigger an alarm or shut down the device.

[0052] Feedback and display: For real-time monitoring systems, data processing will be displayed through the user interface or fed back to other control systems for further response (such as in smart homes, the combination of visual and infrared sensor data will automatically adjust indoor temperature and humidity).

[0053] It is apparent for a person skilled in the art that the present application is not restricted to the details of the above exemplary embodiments, but that it can be implemented in other concrete forms without departing from the spirit or the essential characteristics of the present application. Therefore, the embodiments should be considered as exemplary only, and not limiting, the scope of the present application being defined by the appended claims rather than the above description, and all changes coming within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims should not be construed as limiting the claims concerned.

Claims

1. A multi-modal human presence radar monitoring system, characterized by, Comprise: Radar sensor data collection and transmission; Infrared sensor for infrared data collection and transmission; Visual sensor for infrared data collection and transmission; Sound sensor for infrared data collection and transmission; Pressure sensor for infrared data collection and transmission; The receiving end of the data transmission, according to the application requirements of the predetermined characteristics, the data transmission in the storage module for storage, according to the real-time monitoring data feedback to the display module; The receiving end of the data reception after digital signal conversion, after conversion through the integrated module processing feedback to the control module for intelligent equipment control.

2. A multi-modal human presence radar monitoring system according to claim 1, characterized in that: Infrared sensor through the detection of infrared radiation to collect data, it will be converted into an electrical signal, and then processed and transmitted; Visual sensor for collecting image or video data, capture infrared spectrum, through the predetermined processing and transmission method to send data out; Sound sensor to collect sound signals, signals need to be converted to digital signals through audio processing, Pressure sensor converts the detected pressure value into digital or analog signal; The receiving end of the system for data analysis, including pressure changes and infrared signal correlation, fault diagnosis, temperature compensation or for environmental monitoring.

3. The multi-modal human presence radar monitoring system of claim 1, wherein: Infrared data through wired or wireless communication protocol transmission to the integrated unit; transmission of infrared data is temperature, heat distribution information, data will be transmitted to the receiving end through the transmission system.

4. The multi-modal human presence radar monitoring system of claim 1, wherein: Image data will be transmitted through the image transmission protocol.

5. The multi-modal human presence radar monitoring system of claim 1, wherein: Sound signals will be transmitted through the transmission protocol, pressure and infrared data collected by the pressure sensor will be sent to the data processing center through wired or wireless transmission protocol.

6. The multi-modal human presence radar monitoring system of claim 1, wherein: The receiving end first needs to decode the received data, for image or video data, decoding operation; First, data filtering and denoising: there will be noise interference in the transmission process, the receiving end uses filter to denoise the data, to ensure data quality; According to the application requirements, extract specific features and further analysis, using signal processing algorithm, pattern recognition, data fusion; Data storage: the processed data is stored in the database, records historical data.

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