Monitoring system platform based on brain-computer intelligent safety helmet

Abstract

The invention relates to the technical field of safety monitoring and brain-computer interfaces, and discloses a monitoring system platform based on a brain-computer intelligent safety helmet, and the platform comprises a brain-computer intelligent safety helmet module which is used for collecting the electroencephalogram signal, heart rate, blood oxygen and head posture information of an operator in real time; the wireless communication base station module is responsible for providing a wireless communication channel in a complex working environment and transmitting data collected by the brain-computer intelligent safety helmet to a monitoring system platform; the monitoring system platform module is used for receiving data from the brain-computer intelligent safety helmet in real time and displaying vital signs, brain waves and position information of an operator through a visual interface; and a data processing and analyzing module. By means of the brain-computer intelligent safety helmet module, electroencephalogram signals of an operator can be collected in real time, the attention state, the fatigue state and the consciousness state of the operator can be monitored, the physiological and psychological conditions of the operator are comprehensively evaluated in combination with vital sign data such as heart rate and blood oxygen, and the recognition capacity for potential risks is remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of safety monitoring and brain-computer interface, and specifically to a monitoring system platform based on a brain-computer intelligent safety helmet. Background Art

[0002] As the requirements for safe production in industrial and engineering projects continue to increase, especially in tunnel construction, mine operations, chemical plants and other high-risk environments, the life safety protection of operators has become particularly important. Most of the existing operator safety monitoring systems rely on video monitoring, manual sign-in and simple vital sign monitoring methods, and fail to achieve comprehensive real-time monitoring of the operator's status.

[0003] Traditional safety monitoring systems mostly rely on video monitoring and manual management, which cannot collect the physiological and psychological status of workers in real time and make it difficult to predict potential risks. Especially in complex working environments such as tunnels and mines, video monitoring often has blind spots and cannot fully cover all working areas. Summary of the invention

[0004] In view of the shortcomings of the existing technology, the present invention provides a monitoring system platform based on a brain-computer intelligent safety helmet, which solves the problem that most traditional safety monitoring systems rely on video monitoring and manual management, cannot collect the physiological and psychological states of workers in real time, and are difficult to predict potential risks.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: a monitoring system platform based on brain-computer intelligent helmet, comprising: Brain-computer intelligent helmet module: It integrates multiple sensors including brain wave monitoring, vital sign monitoring and posture sensing, and is used to collect the operator's brain wave signals, heart rate, blood oxygen and head posture information in real time, and transmit the data to the monitoring system platform through a wireless communication base station. This module is the front-end data collector of the system and directly obtains the real-time status of the personnel; Wireless communication base station module: This module is responsible for providing wireless communication channels in complex working environments, transmitting data collected by the brain-computer intelligent helmet to the monitoring system platform. It also has a positioning function to track the location of the operator in real time; Monitoring system platform module: Receives data from the brain-computer intelligent helmet in real time, and displays the vital signs, brain waves and location information of the operator through a visual interface. It has functions including early warning, alarm, data storage and analysis, and forms linkage with other modules. When an abnormal situation is detected, the platform can issue an alarm and provide support for subsequent decision-making through data analysis; Data processing and analysis module: This module cleans, processes and analyzes the raw data transmitted from the brain-computer intelligent helmet to the monitoring platform, generates health status reports, risk assessments and work performance analysis, and helps predict potential safety hazards through the fusion and trend analysis of multiple data, providing data support for the monitoring system platform.

[0006] Preferably, the brain-computer intelligent helmet module includes: The brain wave monitoring unit is used to collect the brain wave signals of the operators and monitor their attention, fatigue, emotional and consciousness status in real time; A vital signs monitoring unit, comprising a heart rate sensor and a blood oxygen sensor, for monitoring the heart rate, blood oxygen saturation, respiratory rate and blood pressure of the operator; A posture sensing unit, which includes an accelerometer and a gyroscope, and is used to detect the head posture and head movement state of the operator, and determine whether the operator is wearing a safety helmet; The SOS alarm system unit triggers an alarm signal when abnormal EEG signals or vital signs of the operator are detected. The alarm signal can be transmitted to the monitoring system platform via a wireless network; Built-in battery unit, supports long-term operation, has low power consumption design, and the battery unit can be charged via USB port or wireless charging; A communication unit, wherein the communication unit can realize wireless data transmission between the smart helmet and the wireless communication base station.

[0007] Preferably, the brain-computer intelligent safety helmet module further includes an environmental monitoring unit, which includes a temperature sensor, a humidity sensor, a gas sensor and a dust sensor, and is used to monitor the temperature, humidity, toxic gas concentration and dust concentration of the working environment.

[0008] Preferably, the wireless communication base station module includes: A communication unit, which supports 4G, 5G, Wi-Fi, LoRa or other wireless communication protocols and can transmit data of the smart helmet to the monitoring system platform; A positioning unit, which includes a GPS unit, a Beidou unit and a UWB unit, and can accurately locate the real-time position of the operator; A signal enhancement unit, which is used to improve the signal transmission quality in complex environments and ensure the stability of data transmission in long-distance, deep tunnel or mine environments; A multi-node base station network unit, the base station can arrange multiple base station nodes in a grid manner according to the complexity of the operating environment to achieve full coverage signal transmission in the operating area.

[0009] Preferably, the monitoring system platform module includes: Real-time data monitoring unit, used to display the operator's EEG signals, vital signs, head posture and environmental monitoring data in real time; Early warning and alarm unit, which can trigger early warning based on preset thresholds. When the EEG signal, heart rate and blood oxygen data exceed the preset thresholds, an alarm is issued and a notification is pushed to the management personnel. The notification can be sent via SMS, voice, flashing lights or mobile phone applications; A data storage unit, which is used to store real-time collected operation data and manage historical data; Historical data analysis unit, used to analyze the long-term health data and work performance of operators, and generate health reports, work performance reports and risk assessment reports; Remote access unit supports remote access and management via PC, mobile phone and tablet terminal devices.

[0010] Preferably, the monitoring system platform module further includes a task management unit, which is capable of associating work tasks with the status of workers and dynamically adjusting tasks based on factors including health status and work performance.

[0011] Preferably, the monitoring system platform module also includes an audio and video communication unit, which can realize audio and video monitoring and intercom functions of the work site, allowing remote voice or video communication between managers and operators.

[0012] Preferably, the data processing and analysis module includes: A data cleaning unit, which is used to filter and clean noise and abnormal data in the collected signals to ensure the accuracy of EEG signals and vital signs data; A data fusion unit capable of comprehensively analyzing EEG signals, vital signs, and environmental monitoring data to generate a safety status assessment of the operator; A health status prediction unit, which performs trend analysis based on the operator's historical health data and can predict the operator's health risks, including fatigue, hypoxia and abnormal heart rate; A report generation unit, which can automatically generate health reports, fatigue status assessment reports and work performance reports for reference by managers.

[0013] Preferably, the SOS alarm system unit of the smart helmet module has a manual triggering function, and the operator can manually send out a distress signal through a physical button or voice command in an emergency.

[0014] Preferably, the wireless communication base station module supports a seamless roaming function based on the collaborative work of multiple base stations, ensuring that data transmission is not interrupted when operators move in a wide or multi-layer area.

[0015] The present invention provides a monitoring system platform based on brain-computer intelligent helmets. It has the following beneficial effects: 1. The system of the present invention can collect the EEG signals of the workers in real time through the brain-computer intelligent helmet module, monitor their attention state, fatigue state and consciousness state, and combine the vital signs data such as heart rate and blood oxygen to comprehensively evaluate the physiological and psychological conditions of the workers, significantly improving the ability to identify potential dangers.

[0016] 2. The system of the present invention uses multi-sensor fusion technology to monitor not only vital signs, but also environmental data such as temperature, humidity, and toxic gas concentration in the working environment, and combines it with the psychological state of the operators and analyzes it through intelligent algorithms. When it is found that the personnel are in a dangerous state or the environment is deteriorating, the system can issue an early warning to help managers take timely measures to reduce accidents.

[0017] 3. The system of the present invention ensures the stability of data transmission in complex environments through the deployment of base stations of multiple communication protocols (such as 4G, 5G, LoRa, etc.). The multi-base station collaboration and signal enhancement mechanism enable the system to achieve seamless roaming in deep tunnels or mines, ensuring that the status data of the operators can be transmitted to the monitoring center in real time, no matter how complex the environment is, ensuring the timeliness of information transmission.

[0018] 4. The system of the present invention has an intelligent early warning and alarm mechanism based on multidimensional data. It can not only trigger the alarm based on a single vital sign, but also combine EEG signals and environmental data, and adopt a multivariate analysis model to reduce the false alarm rate. At the same time, the alarm mechanism supports automatic and manual triggering to ensure that the management personnel are notified in time in an emergency and provide effective emergency support.

[0019] 5. The system of the present invention has powerful data processing and analysis functions, and can perform trend analysis on the long-term data of operators, and generate health reports and work performance reports through historical data. Through long-term monitoring and evaluation of the status of operators, the system can help managers predict potential risks in advance, and provide data support to optimize job scheduling and personnel dispatch, and improve overall work efficiency and safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 This is a platform architecture diagram of a monitoring system based on a brain-computer intelligent helmet of the present invention; Figure 2 This is the architecture diagram of the brain-computer intelligent helmet module of the present invention; Figure 3 This is a module architecture diagram of a wireless communication base station of the present invention; Figure 4 This is a module architecture diagram of the monitoring system platform of the present invention; Figure 5 This is a diagram of the data processing and analysis module architecture of the present invention. DETAILED DESCRIPTION

[0021] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] Please see attached Figure 1 - Attachment Figure 5 , an embodiment of the present invention provides a monitoring system platform based on a brain-computer intelligent helmet, comprising: 1. Brain-computer intelligent helmet module It integrates multiple sensors including brain wave monitoring, vital sign monitoring and posture sensing, which are used to collect the workers' brain wave signals, heart rate, blood oxygen and head posture information in real time, and transmit the data to the monitoring system platform through the wireless communication base station. This module is the front-end data collector of the system, which directly obtains the real-time status of the personnel. The brain-computer intelligent helmet module also includes the following units: Brainwave monitoring unit: This unit uses high-precision brainwave sensors to accurately collect brainwave signals from operators in a noisy environment. The signal is processed by a dedicated brainwave processing algorithm to analyze the state of attention, fatigue, emotion, and consciousness in real time, and the influence of external noise is eliminated through a filtering mechanism to ensure data stability. The underlying logic compares it with the preset brainwave reference map to promptly determine whether the operator's mental state is abnormal.

[0023] Vital Signs Monitoring Unit: The unit includes a heart rate sensor and a blood oxygen sensor, which can monitor the heart rate, blood oxygen saturation, respiratory rate and blood pressure of the operator based on photoplethysmography (PPG) and infrared sensor technology. The data is transmitted to the monitoring platform through a wireless communication base station for real-time display. The underlying logic of vital signs data collection includes a multivariate data fusion algorithm to reduce data deviations caused by environmental interference and ensure real-time and accuracy.

[0024] Posture sensing unit: This unit uses an accelerometer and a gyroscope to detect the operator's head posture and head movement status, and uses a built-in posture recognition algorithm to determine whether the operator is wearing a helmet correctly. The underlying logic is based on a multi-axis posture detection algorithm, which determines whether a fall or violent exercise has occurred by calculating the posture change rate, and performs a comprehensive analysis in combination with the work environment data.

[0025] SOS alarm system unit: This unit is responsible for immediately triggering an alarm signal when abnormal EEG signals or vital signs of operators are detected. The alarm signal is automatically transmitted to the monitoring system platform through the communication unit, and the system also supports presetting emergency contacts. The alarm system adopts a combination of automatic triggering and manual triggering. The underlying logic implements a multiple confirmation mechanism based on multi-dimensional parameters to avoid false alarms.

[0026] Built-in battery unit: This unit is designed for low power consumption, supports long working hours, adopts intelligent power management algorithm, and is charged through USB port or wireless charging. The battery module integrates charging status monitor and battery power prediction algorithm to ensure that the battery can maintain stable power supply under any working conditions.

[0027] Communication unit: This unit supports multiple wireless communication protocols and can realize two-way data transmission between the smart helmet and the wireless communication base station. The underlying logic ensures real-time data transmission and security through efficient data compression and encryption algorithms, and has the function of automatically switching signal channels to adapt to different working environments.

[0028] Environmental monitoring unit: This unit integrates temperature sensors, humidity sensors, gas sensors and dust sensors, and can monitor the temperature, humidity, toxic gas concentration and dust concentration of the working environment in real time. The underlying logic can identify abnormal environmental conditions and issue early warning signals in a timely manner through multi-sensor data fusion algorithms.

[0029] 2. Wireless communication base station module This module is responsible for providing wireless communication channels in complex working environments, transmitting data collected by the brain-computer intelligent helmet to the monitoring system platform, and also has positioning functions to track the location of workers in real time. The wireless communication base station module includes the following units: Communication unit: The communication unit supports a variety of wireless communication protocols, including 4G, 5G, Wi-Fi, LoRa, etc., and is used to transmit the data of the smart helmet to the monitoring system platform. The underlying logic of the communication unit includes an algorithm that automatically selects the optimal communication path to ensure efficient and stable data transmission in complex or remote environments.

[0030] Positioning unit: The positioning unit integrates GPS, Beidou and UWB positioning technologies to provide high-precision real-time positioning of operators. The underlying logic uses a multi-source positioning data fusion algorithm combined with the signal strength information of wireless communication base stations to provide sub-meter-level precise positioning.

[0031] Signal enhancement unit: This unit is responsible for enhancing the quality of wireless signal transmission in complex environments. The signal enhancement unit has a built-in adaptive signal amplification algorithm that dynamically adjusts the signal frequency and transmission power to ensure stable data transmission in complex environments such as deep tunnels and mines.

[0032] Multi-node base station network unit: This unit can arrange multiple base station nodes in a grid manner according to the complexity of the operating environment to achieve full coverage of signal transmission in the operating area. The underlying logic includes a grid-based adaptive network protocol that can automatically coordinate data routing between nodes to ensure that there are no signal dead spots in a large operating area.

[0033] 3. Monitoring system platform module The monitoring system platform module is used to receive data from the brain-computer intelligent helmet and the wireless communication base station, and to display the vital signs, brain waves, location information and environmental monitoring data of the operator in real time through a visual interface. The module has data storage, analysis, early warning and alarm functions. The monitoring system platform module includes the following units: Real-time data monitoring unit: This unit can display the real-time status data of operators through a visual interface. The underlying logic uses a data stream processing engine to ensure that the delay of data display is at the millisecond level and supports multi-user and cross-platform access.

[0034] Early warning and alarm unit: The early warning and alarm unit automatically triggers an alarm based on the set threshold. When the EEG signal, heart rate and blood oxygen data exceed the preset threshold, the system will immediately issue an early warning notification. The unit adopts a multi-level alarm mechanism and combines the operating environment to make intelligent alarm judgments to reduce the false alarm rate.

[0035] Data storage unit: This unit is used to store all data of operators in real time. The data storage uses an efficient distributed storage system, which can support long-term storage and backup management of massive data and ensure data integrity and security.

[0036] Historical data analysis unit: This unit uses a big data analysis engine to perform trend analysis on the long-term health data of operators and generate health reports, work performance reports, and risk assessment reports. The underlying logic is combined with a machine learning model to identify potential safety hazards for operators.

[0037] Remote access unit: This unit supports managers to conduct remote real-time monitoring and management through PCs, mobile phones and tablet terminals. The underlying logic uses a secure encryption protocol to ensure the security of remote access.

[0038] Task management unit: The task management unit can associate the work tasks with the status of the workers, and optimize the scheduling of workers by dynamically adjusting the task allocation. The underlying logic ensures the highest matching degree between the work tasks and the status of the workers through the task allocation optimization algorithm.

[0039] Audio and video communication unit: This unit can provide audio and video monitoring and real-time intercom functions at the work site, and realize remote voice or video communication. Audio and video transmission uses low-latency encoding technology to ensure the smoothness of real-time communication.

[0040] 4. Data processing and analysis module The data processing and analysis module cleans, processes and analyzes all collected raw data and generates relevant reports. This module includes the following units: Data cleaning unit: This unit is responsible for removing noise and outliers from the data. The underlying logic uses advanced filters and anomaly detection algorithms to ensure data accuracy.

[0041] Data fusion unit: This unit conducts comprehensive analysis of EEG signals, vital signs and environmental monitoring data to generate a safety status assessment of the operator. Data fusion is based on a multi-level data fusion algorithm and can provide a global view of safety assessment.

[0042] Health status prediction unit: This unit uses trend analysis and prediction models based on the historical data of operators to identify potential health risks of operators. The underlying logic uses a prediction model based on deep learning and has high-precision health risk prediction capabilities.

[0043] Report generation unit: This unit automatically generates health reports, fatigue status assessment reports, and work performance reports for managers to refer to. The report generation logic supports customization and can generate reports of different types and formats according to user needs.

[0044] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A monitoring system platform based on brain-computer intelligent helmet, characterized in that: include: Brain-computer intelligent helmet module: It integrates multiple sensors including brain wave monitoring, vital sign monitoring and posture sensing, and is used to collect the operator's brain wave signals, heart rate, blood oxygen and head posture information in real time, and transmit the data to the monitoring system platform through a wireless communication base station. This module is the front-end data collector of the system and directly obtains the real-time status of the personnel; Wireless communication base station module: This module is responsible for providing wireless communication channels in complex working environments, transmitting data collected by the brain-computer intelligent helmet to the monitoring system platform. It also has a positioning function to track the location of the operator in real time; Monitoring system platform module: Receives data from the brain-computer intelligent helmet in real time, and displays the vital signs, brain waves and location information of the operator through a visual interface. It has functions including early warning, alarm, data storage and analysis, and forms linkage with other modules. When an abnormal situation is detected, the platform can issue an alarm and provide support for subsequent decision-making through data analysis; Data processing and analysis module: This module cleans, processes and analyzes the raw data transmitted from the brain-computer intelligent helmet to the monitoring platform, generates health status reports, risk assessments and work performance analysis, and helps predict potential safety hazards through the fusion and trend analysis of multiple data, providing data support for the monitoring system platform.

2. A monitoring system platform based on brain-computer intelligent helmet according to claim 1, characterized in that: The brain-computer intelligent helmet module includes: The brain wave monitoring unit is used to collect the brain wave signals of the operators and monitor their attention, fatigue, emotional and consciousness status in real time; A vital signs monitoring unit, comprising a heart rate sensor and a blood oxygen sensor, for monitoring the heart rate, blood oxygen saturation, respiratory rate and blood pressure of the operator; A posture sensing unit, which includes an accelerometer and a gyroscope, and is used to detect the head posture and head movement state of the operator, and determine whether the operator is wearing a safety helmet; The SOS alarm system unit triggers an alarm signal when abnormal EEG signals or vital signs of the operator are detected. The alarm signal can be transmitted to the monitoring system platform via a wireless network; Built-in battery unit, supports long-term operation, has low power consumption design, and the battery unit can be charged via USB port or wireless charging; A communication unit, wherein the communication unit can realize wireless data transmission between the smart helmet and the wireless communication base station.

3. A monitoring system platform based on brain-computer intelligent helmet according to claim 2, characterized in that: The brain-computer intelligent safety helmet module further includes an environmental monitoring unit, which includes a temperature sensor, a humidity sensor, a gas sensor and a dust sensor, and is used to monitor the temperature, humidity, toxic gas concentration and dust concentration of the working environment.

4. The monitoring system platform based on brain-computer intelligent helmet according to claim 1 is characterized in that: The wireless communication base station module comprises: A communication unit, which supports 4G, 5G, Wi-Fi, LoRa or other wireless communication protocols and can transmit data of the smart helmet to the monitoring system platform; A positioning unit, which includes a GPS unit, a Beidou unit and a UWB unit, and can accurately locate the real-time position of the operator; A signal enhancement unit, which is used to improve the signal transmission quality in complex environments and ensure the stability of data transmission in long-distance, deep tunnel or mine environments; A multi-node base station network unit, the base station can arrange multiple base station nodes in a grid manner according to the complexity of the operating environment to achieve full coverage signal transmission in the operating area.

5. The monitoring system platform based on brain-computer intelligent helmet according to claim 1 is characterized in that: The monitoring system platform module includes: Real-time data monitoring unit, used to display the operator's EEG signals, vital signs, head posture and environmental monitoring data in real time; Early warning and alarm unit, which can trigger early warning based on preset thresholds. When the EEG signal, heart rate and blood oxygen data exceed the preset thresholds, an alarm is issued and a notification is pushed to the management personnel. The notification can be sent via SMS, voice, flashing lights or mobile phone applications; A data storage unit, which is used to store real-time collected operation data and manage historical data; Historical data analysis unit, used to analyze the long-term health data and work performance of operators, and generate health reports, work performance reports and risk assessment reports; Remote access unit supports remote access and management via PC, mobile phone and tablet terminal devices.

6. A monitoring system platform based on brain-computer intelligent helmet according to claim 5, characterized in that: The monitoring system platform module further includes a task management unit, which can associate the work task with the status of the operator and dynamically adjust the task based on factors including health status and work performance.

7. The monitoring system platform based on brain-computer intelligent helmet according to claim 5 is characterized in that: The monitoring system platform module also includes an audio and video communication unit, which can realize audio and video monitoring and intercom functions of the work site, allowing remote voice or video communication between managers and operators.

8. The monitoring system platform based on brain-computer intelligent helmet according to claim 1 is characterized in that: The data processing and analysis module includes: A data cleaning unit, which is used to filter and clean noise and abnormal data in the collected signals to ensure the accuracy of EEG signals and vital signs data; A data fusion unit capable of comprehensively analyzing EEG signals, vital signs, and environmental monitoring data to generate a safety status assessment of the operator; A health status prediction unit, which performs trend analysis based on the operator's historical health data and can predict the operator's health risks, including fatigue, hypoxia and abnormal heart rate; A report generation unit, which can automatically generate health reports, fatigue status assessment reports and work performance reports for reference by managers.

9. The monitoring system platform based on brain-computer intelligent helmet according to claim 2 is characterized in that: The SOS alarm system unit of the smart helmet module has a manual triggering function, and the operator can manually send out a distress signal through a physical button or voice command in an emergency.

10. The monitoring system platform based on brain-computer intelligent helmet according to claim 1 is characterized in that: The wireless communication base station module supports a seamless roaming function based on the collaborative work of multiple base stations, ensuring that data transmission is not interrupted when operators move in a wide or multi-layer area.

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