Supervision place information interaction system

Abstract

The invention relates to the technical field of intelligent management, in particular to a supervision place information interaction system. The system generates a personalized daily task plan for a supervised object through the central management unit and preloads the task plan to the wearable device. The wearable device continuously collects vital sign data streams through a biological information collection module of the wearable device, can start a non-inductive identity verification process when being triggered, and generates an alarm when an abnormality is found. The system can dynamically calculate the task execution sequence according to the context information uploaded in real time, and dynamically adjust the task flow when the task is abnormal or the physiological state of a person is abnormal. And when the wearable device enters the target area and successfully authenticates with the area interaction terminal, the task information can be decrypted and displayed, and the next task is prepared after the completion confirmation is obtained. Besides, the system can also quantitatively calculate the comprehensive pressure level of the personnel based on physiological and task data collected for a long time, evaluate the activity curative effect through correlation analysis, and generate personalized suggestions for optimizing subsequent plans, such as increasing beneficial activities or adjusting activity types, so that intelligent and precise supervision and correction are realized.

Description

Technical Field

[0001] This application relates to the field of intelligent management technology, specifically to an information interaction system for regulatory sites. Background Technology

[0002] Supervision facilities such as prisons and drug rehabilitation centers bear the dual responsibility of enforcing regulations and providing education and correction. Currently, information exchange and management in these facilities rely heavily on fixed broadcasts, bulletin boards, and basic electronic access control systems, which are significantly inadequate.

[0003] First, the information transmission method is crude, making it impossible to accurately assign tasks and guide individuals based on their personalized correction plans, resulting in low management efficiency and difficulty in guaranteeing correctional effectiveness. Second, existing technologies have weak ability to perceive the state of individuals, and are usually unable to verify the identity of individuals and the binding status of devices in real time and seamlessly, posing certain security risks. Third, managers have difficulty obtaining timely feedback on the physiological and psychological state of those being monitored, and cannot correlate objective data such as heart rate and stress levels with daily task performance, making adjustments to correctional plans lack data support and scientific rigor.

[0004] Application content

[0005] The purpose of this application is to provide an information exchange system for regulatory facilities to improve the safety and corrective effectiveness of regulatory facilities.

[0006] This application provides an information exchange system for regulatory sites, including:

[0007] The central management unit is used to generate and assign personalized daily task plans to those being monitored.

[0008] Wearable devices, worn on designated parts of the monitored object's body, include a data storage module, a communication module, a display module, and a biometric information collection module. They are communicatively connected to the central management unit and are used to receive and encrypt the daily task plan, and decrypt and display the task information after authorization.

[0009] Multiple regional interactive terminals are deployed in various functional areas within the regulatory site and are communicatively connected to the central management unit and the wearable devices. They are used to authenticate and interact with the wearable devices that enter their communication range. The central management unit preloads an encrypted daily task plan sequence into the wearable devices. The wearable devices only decrypt the sequence and display the task information of the current step after moving to the target functional area and successfully authenticating with the corresponding regional interactive terminal.

[0010] In some embodiments, the wearable device is configured to perform device status and wearer identity activity monitoring, specifically including the following steps:

[0011] S110, continuously collect the wearer's vital signs data stream through the bio-information acquisition module;

[0012] S120 initiates a contactless authentication process based on a preset strategy or event trigger to confirm the identity of the current wearer;

[0013] S130, if the vital signs data stream is interrupted for more than a first preset time, or the contactless identity verification process fails continuously, it is determined to be an abnormal state.

[0014] S140, generate alarm information of the corresponding level, and upload the alarm information to the central management unit through the regional interactive terminal and / or wearable device.

[0015] In some embodiments, the bio-information acquisition module includes at least an optical sensing unit and an electrophysiological sensing unit. Step S110, which involves continuously acquiring the wearer's vital signs data stream through the bio-information acquisition module, further includes:

[0016] S111 monitors cardiovascular-related physiological parameters through an optical sensing unit and monitors skin electrical activity through an electrophysiological sensing unit.

[0017] S112, establish a personalized vital sign baseline based on historical data of the monitored object when it is in a stable state;

[0018] S113, continuously compare the real-time collected vital sign data with the personalized vital sign baseline, and generate a physiological state warning when a continuous deviation is detected.

[0019] In some embodiments, the step of initiating the contactless authentication process in step S120 further includes:

[0020] S121, the wearer's biometric information is acquired through the biometric information acquisition module;

[0021] S122, compare the acquired biometric information with the pre-stored biometric template;

[0022] S123, if the comparison is successful, the identity verification is confirmed; if the comparison fails, the retry mechanism is initiated and an alarm is triggered after consecutive failures.

[0023] In some embodiments, the system is further configured to perform dynamic task planning and guidance, specifically including the following steps:

[0024] S210, dynamically calculate the task execution sequence based on the daily task plan and the context information uploaded in real time from the wearable device;

[0025] S220, based on the task completion status, control the regional interactive terminal to interact with the wearable device to guide the next task.

[0026] In some embodiments, the step of dynamically calculating the task execution sequence in step S210 further includes:

[0027] S211, acquire and update context information from the wearable device in real time, including at least: real-time location, current task status and vital signs data;

[0028] S212, If the current task is not completed within the planned time, the timing of subsequent affected tasks will be automatically recalculated;

[0029] S213, if the vital signs data indicate that the wearer is in a preset abnormal physiological state, the task flow is dynamically adjusted to replace the original task with a predefined alternative task.

[0030] In some embodiments, step S220, which involves controlling the regional interaction terminal to interact with the wearable device to guide the next task, further includes:

[0031] S221, When the wearable device enters the area of ​​the regional interactive terminal in the target area, two-way authentication is completed;

[0032] S222, After successful authentication, the wearable device decrypts and displays detailed task information for the current step;

[0033] S223, wait for and receive a task completion confirmation signal from authorized operators and / or environmental devices, and after verifying the task completion confirmation signal, update the task status and prepare for the next task.

[0034] In some embodiments, the system is further configured to perform personalized plan optimization based on data feedback, specifically including the following steps:

[0035] S310, collect and correlate analysis of long-term physiological data, task execution data and evaluation data of the monitored subjects;

[0036] S320, based on the results of correlation analysis, evaluates the effectiveness of different activities on the status of the regulated object; and generates personalized adjustment suggestions for optimizing subsequent daily task plans.

[0037] In some embodiments, step S310, which involves collecting and correlating long-term physiological data, task execution data, and evaluation data, further includes:

[0038] S311, based on heart rate variability and skin conductance data, quantifies the overall stress level of the monitored subject throughout the day;

[0039] S312, perform a correlation analysis between the overall stress level and the type and quality of tasks performed on the day, and identify specific tasks or events that cause significant changes in the overall stress level.

[0040] In some embodiments, step S320, which generates personalized adjustment suggestions for optimizing subsequent daily task plans, further includes:

[0041] S321, If ​​data analysis shows that a certain type of activity can significantly improve the physiological indicators of the regulated subjects and reduce their stress levels, then a recommendation to increase the frequency of such activities is generated.

[0042] S322 If data analysis indicates that the stress level of the regulated entity is consistently higher than the threshold, then a scheduling recommendation to reduce highly stimulating activities and increase relaxing activities is generated.

[0043] The present invention provides an information interaction system for regulatory sites, which achieves the following significant technical effects through the collaborative work of wearable devices and regional interaction terminals:

[0044] 1. Improved safety management level: By continuously monitoring vital signs and non-contact identity verification, it can determine abnormal states such as equipment detachment or identity fraud in real time and issue alarms immediately, achieving the effect of proactive early warning and effectively improving the safety of the supervised site.

[0045] 2. It achieves precise and personalized management. The system can dynamically calculate and adjust the task sequence based on the real-time location, task progress, and even physiological state of the personnel, enabling differentiated guidance for different supervisors to make the correction process more accurate and efficient.

[0046] 3. A data-driven management closed loop has been formed. By collecting and analyzing physiological data, task data and evaluation data over a long period of time, the system can quantitatively evaluate the corrective effects of different activities and automatically generate personalized adjustment suggestions. This provides managers with more accurate data support for optimizing corrective plans and significantly improves the scientific nature and effectiveness of supervision. Attached Figure Description

[0047] Figure 1 This is a block diagram of the information interaction system in this application;

[0048] Figure 2 This is a flowchart illustrating the device status and wearer identity activity monitoring process in this application;

[0049] Figure 3 This is a flowchart of the vital signs data stream used in this application;

[0050] Figure 4This is a flowchart of the contactless authentication process in this application;

[0051] Figure 5 This is a flowchart of the dynamic task planning and guidance process in this application;

[0052] Figure 6 This is a flowchart of the computation task execution sequence in this application;

[0053] Figure 7 This is a flowchart guiding the user to the next task in this application;

[0054] Figure 8 A flowchart for optimizing the personalized plan in this application;

[0055] Figure 9 A flowchart for the data collected and associated in this application. Detailed Implementation

[0056] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0057] Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0058] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can also be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0059] In addition, the functional modules in the various embodiments of this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0060] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium 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 described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0061] Supervision facilities such as prisons and drug rehabilitation centers bear the dual responsibility of enforcing regulations and providing education and correction. Currently, information exchange and management in these facilities rely heavily on fixed broadcasts, bulletin boards, and basic electronic access control systems, which are significantly inadequate.

[0062] First, the information transmission method is crude, making it impossible to accurately assign tasks and guide individuals based on their personalized correction plans, resulting in low management efficiency and difficulty in guaranteeing correctional effectiveness. Second, existing technologies have weak ability to perceive the state of individuals, and are usually unable to verify the identity of individuals and the binding status of devices in real time and seamlessly, posing certain security risks. Third, managers have difficulty obtaining timely feedback on the physiological and psychological state of those being monitored, and cannot correlate objective data such as heart rate and stress levels with daily task performance, making adjustments to correctional plans lack data support and scientific rigor.

[0063] Example 1

[0064] In view of this, this application provides an information exchange system for regulatory sites, referring to... Figure 1 It includes a central management unit, wearable devices, and multiple regional interactive terminals.

[0065] The central management unit is used to generate and assign personalized daily task plans to the supervised entities.

[0066] The central management unit can be physically represented as a server cluster deployed in the data center of the supervised facility. This server cluster runs task scheduling software, data storage services, and core communication services. Generating personalized daily task plans is a process of multi-source data fusion and decision-making. The central management unit accesses the supervised individual's file information, historical behavioral data, psychological assessment reports, and long-term rehabilitation goals set by medical or correctional personnel. Based on these inputs, the central management unit's built-in rule engine and possible optimization algorithms (such as constraint programming or heuristic algorithms) generate a structured, time-dependent task sequence for each supervised individual. This sequence is precise down to the target area of ​​each task, its estimated duration, and the dependencies between preceding and subsequent tasks. The task plan covers multiple dimensions, including education and learning, labor reform, psychological counseling, physical exercise, and daily life management.

[0067] Wearable devices are worn on designated parts of the monitored person's body and include a data storage module, a communication module, a display module, and a biometric information collection module. They are connected to a central management unit to receive and encrypt daily task plans and decrypt and display task information after authorization.

[0068] Wearable devices are physically designed for use in supervised environments and are tamper-proof or vandal-proof wrist or ankle-worn devices. Their data storage modules typically use embedded flash memory with encryption capabilities, their communication modules integrate near-field communication units such as Bluetooth Low Energy, Zigbee, or LoRa, and Wi-Fi or 4G / 5G cellular network modules for periodic data synchronization with the central management unit, their display modules are typically low-power e-ink screens or segment LCD screens, and their bio-information acquisition modules include at least optical sensors and electrophysiological sensors.

[0069] Multiple regional interactive terminals are deployed in various functional areas within the regulatory site, communicating with the central management unit and wearable devices to authenticate and exchange data with wearable devices that enter their communication range.

[0070] Regional interactive terminals are hardware devices that are fixedly deployed at the entrances or inside key physical spaces such as prison cells, workshops, classrooms, activity areas, and medical rooms. They can be base stations with UWB precise positioning capabilities, low-power Bluetooth beacons that support active scanning and response capabilities, or RFID readers.

[0071] The central management unit preloads encrypted daily task schedule sequences into wearable devices. The wearable devices only decrypt the sequence and display the task information for the current step after successfully authenticating with the corresponding regional interaction terminal upon moving to the target functional area. The central management unit maintains a connection with all regional interaction terminals via wired or wireless networks, forming a comprehensive IoT sensing network. When issuing tasks to wearable devices, the central management unit encrypts the entire task schedule sequence using a pre-set encryption key (such as AES-256 symmetric encryption). This encrypted data packet is transmitted and stored in the wearable device's data storage module. The wearable device itself does not have the ability to independently decrypt and display all tasks; its decryption behavior is strictly limited to a specific spatiotemporal context. Only when the monitored object wearing the wearable device moves to the target functional area specified by its current task, and the wearable device establishes a communication connection with the regional interaction terminal deployed there, and successfully completes a two-way authentication based on cryptographic principles (e.g., using a challenge-response protocol or asymmetric encryption-based authentication), will the regional interaction terminal send a temporary session key or decryption command to the wearable device. Wearable devices can use this temporary key to decrypt the specific task information corresponding to the current step from the encrypted task sequence and render it on the display module, thereby achieving precise guidance for the monitored object, ensuring the high context relevance and security of task information, and avoiding premature leakage or misuse of information.

[0072] Example 2

[0073] Reference Figure 2 In some embodiments, the wearable device is configured to perform device status and wearer identity activity monitoring, specifically including the following steps:

[0074] S110 continuously collects the wearer's vital signs data stream through the bio-information acquisition module. This continuous collection of vital signs data stream through the bio-information acquisition module is a continuous physiological signal sensing process.

[0075] In some specific embodiments, the bioinformation acquisition module includes at least an optical sensing unit and an electrophysiological sensing unit. The optical sensing unit can be a photoplethysmography sensor, which continuously monitors cardiovascular-related physiological parameters, including but not limited to heart rate, heart rate variability, and blood oxygen saturation, by emitting a specific wavelength of light signal (typically green light, sensitive to changes in blood flow) into the skin and receiving the reflected light. The electrophysiological sensing unit can be a skin conductance sensor, which continuously monitors skin electrical activity by measuring changes in conductivity between two electrodes on the skin surface; this signal is an indirect indicator of the excitability of the sympathetic nervous system. These raw physiological signals undergo preliminary signal conditioning (such as filtering and amplification) and feature extraction within the wearable device's microcontroller, forming a temporally continuous vital sign data stream. This data stream is recorded and cached locally at a specific sampling frequency (e.g., 1Hz for heart rate, 4Hz for blood pressure and blood flow rate).

[0076] Specifically, refer to Figure 3 The steps for continuously collecting the wearer's vital signs data stream through the biometrics acquisition module include:

[0077] The S111 monitors cardiovascular-related physiological parameters via an optical sensing unit and skin electrical activity via an electrophysiological sensing unit. The microprocessor within the wearable device runs specific digital signal processing algorithms to calculate the instantaneous heart rate and further derives heart rate variability indices, such as RMSSD or SDNN, by calculating the differences between consecutive heartbeat intervals. Blood oxygen saturation calculation relies on the analysis of differences in the absorption rates of different wavelengths of light (typically red and infrared) by the PPG sensor. The electrophysiological sensing unit monitors skin electrical activity and outputs skin conductance level signals and skin conductance response signals.

[0078] S112 establishes personalized vital sign baselines based on historical data of the monitored subjects when they are in a stable state. The central management unit collects historical vital sign data for each monitored subject over several days during nighttime sleep or designated rest periods. After cleaning and aggregating this data, statistical methods (such as calculating confidence intervals) or clustering algorithms are used to establish unique resting heart rate ranges, heart rate variability baselines, baseline blood oxygen saturation values, and skin conductance level baselines for each individual. The baseline model can be dynamically updated periodically based on new stable-state data to adapt to long-term changes in the physiological state of the monitored subjects.

[0079] S113 continuously compares real-time collected vital sign data with a personalized vital sign baseline and generates a physiological state warning when a persistent deviation is detected. The wearable device or central management unit continuously calculates the Z-score of the real-time data relative to the baseline or uses threshold-based judgment logic. For example, if the real-time heart rate continuously exceeds the individual's resting heart rate limit for a second preset duration (e.g., for 5 minutes), accompanied by a significant increase in skin conductance, the system determines it as a "physiological irritation state." This persistent deviation refers not only to an abnormality in a single indicator but also emphasizes the fusion analysis and pattern recognition of multimodal physiological signals. Once such a persistent deviation is detected, the system generates a low-level physiological state warning to alert medical personnel to potential physical and mental health problems in the monitored individual.

[0080] S120 initiates a contactless authentication process based on a preset strategy or event trigger to confirm the identity of the current wearer;

[0081] Specifically, refer to Figure 4 The steps to initiate a seamless authentication process include:

[0082] S121, the wearer's biometric information is acquired through the biometric acquisition module; one or more difficult-to-forge physiological features are collected using specific sensors integrated into the contact surface of the wearable device. Given the morphological factors of the wrist device, one of the preferred biometric features is the wrist vein pattern, which can be achieved by setting up a miniature near-infrared camera and a matching infrared light source. When the verification process is initiated, the infrared light source illuminates the subcutaneous blood vessels in the wrist, and the near-infrared camera captures the shadow pattern of the blood vessels, forming a vein image. In some other embodiments, the heartbeat characteristics contained in continuously acquired PPG signals can also be used as auxiliary biometric features.

[0083] S122, the acquired biometric information is compared with a pre-stored biometric template. For vein image verification, the dedicated image processing chip integrated within the wearable device preprocesses the captured vein image, including grayscale conversion, contrast enhancement, and thinning, and then extracts the feature point set of the veins. Subsequently, using feature matching algorithms, such as minutiae matching or deep learning-based feature vector comparison, the real-time extracted feature set is compared with the registration template pre-stored in the device's secure storage area to calculate similarity. The pre-stored biometric template is a reference model generated through multiple acquisitions and fusions during device initialization and binding.

[0084] S123, if the comparison is successful, the identity verification is confirmed; if the comparison fails, a retry mechanism is initiated and an alarm is triggered after consecutive failures. The system sets a similarity threshold. If the similarity score between the real-time feature set and the template is higher than the threshold, the comparison is considered successful, the identity verification is passed, and this verification event is recorded. If the score is lower than the threshold, the comparison is considered failed. At this time, the system initiates a retry mechanism. In this embodiment, it can be adopted that up to two re-collection and comparisons are automatically performed within the next 10 seconds. If the number of consecutive failures reaches the preset limit, for example, a total of three failures, it means that the wearer's identity cannot be confirmed. At this time, a high-level identity verification failure alarm will be triggered. This alarm will immediately execute step S140, upload the alarm information to the central management unit, and may be accompanied by local audio and visual alarms from the wearable device to alert nearby management personnel.

[0085] S130, if the vital signs data stream is interrupted for more than a first preset duration, or the contactless authentication process fails continuously, it is determined to be in an abnormal state; the determination logic is executed by the decision logic unit built into the wearable device. An interruption of the vital signs data stream means that the optical sensing unit and the electrophysiological sensing unit fail to detect valid physiological signals within more than the first preset duration, strongly suggesting that the device may have been removed or severely obstructed. In this embodiment, the first preset duration can be set to 60 consecutive seconds. Continuous failure of the contactless authentication process means that three consecutive authentication attempts fail within a short period. If either condition is met, the decision logic unit will determine that the system has entered an abnormal state.

[0086] S140: Generate alarm information of the corresponding level and upload it to the central management unit via the regional interactive terminal and / or wearable device. The alarm level can be categorized according to the anomaly type, such as "device detachment warning" or "authentication failure warning." After generating the alarm information, the wearable device will prioritize uploading it to the central management unit via the currently connected regional interactive terminal, utilizing its existing network connection. If no regional interactive terminal is available, the wearable device can upload it directly via its own cellular network module. The alarm information packet typically includes the wearable device ID, timestamp, anomaly type code, and possibly a snapshot of environmental data.

[0087] Example 3

[0088] Reference Figure 5 In some embodiments, the system is also used to perform dynamic task planning and guidance, specifically including the following steps:

[0089] In step S210, the task execution sequence is dynamically calculated based on the daily task plan and context information uploaded in real time from wearable devices. The core scheduling engine of the central management unit continuously monitors data streams from all wearable devices. The context information includes the precise real-time location of the monitored object calculated via UWB or Bluetooth positioning technology, the current task status obtained in step S223 (such as "pending execution," "in execution," "completed," or "timed out"), and vital sign data acquired and uploaded from the biometrics acquisition module. The engine first maintains a global task plan graph, where nodes represent tasks and edges represent temporal and spatial constraints between tasks. Simultaneously, the engine periodically or during critical events reassesses the executability of the entire plan graph.

[0090] Specifically, refer to Figure 6 The steps of dynamically calculating the task execution sequence include:

[0091] S211, acquire and update context information from wearable devices in real time. This information includes at least: real-time location, current task status, and vital sign data. The central management unit acquires and updates context information from all wearable devices in real time through an IoT message middleware (such as the MQTT protocol). Real-time location information is provided by a network of positioning base stations deployed in the environment, calculated using triangulation or fingerprint positioning algorithms; the current task status is an enumeration value managed by the system state machine; vital sign data are feature values ​​that have been preliminarily processed by the wearable devices, such as average heart rate, heart rate variability index, and skin conductance level. All context information is integrated into a real-time updated in-memory database within the central management unit for global access.

[0092] S212, if the current task does not complete within the planned time, the timing of subsequent affected tasks is automatically recalculated. The scheduling engine has an embedded time inference module, which assigns a planned time window to each task. If the system detects that the duration of a task's "in progress" state exceeds its planned window, or if the task fails to transition to the "completed" state on time, the time inference module will determine that the task has timed out. Subsequently, the scheduling engine will initiate a rescheduling algorithm, which considers the time dependencies of all unstarted tasks with the original plan, resource conflicts, and minimum interval requirements between tasks, recalculates the new task start and end time sequences, and updates the global plan.

[0093] S213, if vital sign data indicates that the wearer is in a preset abnormal physiological state, the task flow is dynamically adjusted, replacing the original task with a predefined alternative task. The system presets multiple abnormal physiological state patterns, such as "acute anxiety state" or "fatigue state." When vital sign data uploaded from the wearable device is identified by a lightweight classifier as matching a preset abnormal pattern, the scheduling engine's dynamic task flow adjustment module is triggered. This module accesses a predefined alternative task library, which stores alternative activities suitable for different abnormal states, such as replacing "high-intensity labor" with "seated rest," or "group discussion" with "individual reading." The adjustment module selects the most suitable alternative task from the library based on the identified abnormal state type and immediately replaces the currently executing or about-to-be-executed original task, while simultaneously notifying relevant management personnel.

[0094] S220 controls the interaction between the regional interactive terminal and the wearable device based on the task completion status to guide the next task. It transforms the scheduling decisions of the central management unit into specific instruction displays and regional access control on the wearable device, forming an execution closed loop from the cloud to the edge.

[0095] Specifically, refer to Figure 7 The steps for controlling the interaction between the interactive terminal and the wearable device to guide the next task include:

[0096] S221, when the wearable device enters the area of ​​the regional interactive terminal in the target area, two-way authentication is completed; when the monitored object wearing the wearable device moves according to the system guidance or plan, causing the wearable device to enter the wireless signal coverage area of ​​the target area interactive terminal, the communication initialization process begins.

[0097] Two-way authentication typically employs a challenge-response protocol based on public key infrastructure. The regional terminal sends a random number challenge to the wearable device. The wearable device digitally signs the challenge using its private key and sends it back. The regional terminal then verifies the signature using the pre-stored public key of the wearable device. The same procedure is repeated for the other terminal. This ensures the legitimacy of both parties' identities and prevents malicious devices from accessing or impersonating the device.

[0098] S222, upon successful authentication, the wearable device decrypts and displays detailed task information for the current step. The regional interaction terminal sends an authorization command to the wearable device, which may contain a key for decrypting a specific task data block. This key may be pre-distributed by the central management unit and transmitted to the regional interaction terminal via a secure channel. The wearable device's microprocessor uses this key, through its built-in encryption / decryption coprocessor, to decrypt the corresponding encrypted task data stored in the data storage module. The decrypted task information includes a task title, detailed step instructions, precautions, and possibly a target image or QR code. This information is displayed on the wearable device's display module, providing clear action guidelines for the monitored entity.

[0099] S223, wait for and receive a task completion confirmation signal from authorized operators and / or environmental equipment. After verifying the task completion confirmation signal, update the task status and prepare for the next task. For tasks that require professional skill judgment or involve material handover, the confirmation signal must come from authorized operators. For example, after completing a physical examination, medical personnel can scan the QR code of a wearable device or enter the task completion code through their dedicated PDA or touch screen terminal installed at their workstation.

[0100] For procedural and standardized tasks, confirmation signals can come from environmental devices. For example, a smart medicine cabinet sends a confirmation signal to the central management unit via an IoT protocol after detecting that a medicine has been taken; or a smart fitness device automatically reports after detecting that a preset amount of exercise has been reached. Upon receiving these external confirmation signals, the central management unit matches and verifies them against the currently executing task. If verification is successful, the central management unit's task state machine marks the task as "completed" and triggers the dynamic calculation in step S210 to prepare the next task instruction to be decrypted and executed for the wearable device, thus initiating a new boot loop.

[0101] Example 4

[0102] Reference Figure 8 In some embodiments, the system is also used to perform personalized plan optimization based on data feedback, specifically including the following steps:

[0103] S310 collects and correlates the long-term physiological data, task execution data, and assessment data of the supervised individuals. The central management unit's data lake architecture continuously collects and stores multi-dimensional data. Long-term physiological data comes from continuous monitoring by wearable devices, including time-series data on heart rate, heart rate variability, blood oxygen, and skin conductance. Task execution data includes the start time, actual completion time, duration, whether timeout occurred, completion quality score, and movement trajectory during task execution for each task. Assessment data includes periodic standardized psychological scale results, subjective evaluation records from supervisors, and possible medical diagnoses. All data is correlated and aligned using the supervised individual's unique ID and timestamp to form a comprehensive personal digital profile.

[0104] In some embodiments, refer to Figure 9 Step S310, which involves collecting and correlating long-term physiological data, task execution data, and evaluation data, further includes:

[0105] S311, based on heart rate variability and skin conductance data, quantifies the overall stress level of monitored subjects throughout the day. Heart rate variability data, particularly the ratio of low-frequency power to high-frequency power in its frequency domain, is widely considered an indicator of the balance between sympathetic and vagal nerve tension; an elevated LF / HF ratio typically reflects increased stress. The frequency and amplitude of skin conductance responses in skin conductance are also a direct manifestation of sympathetic nerve excitation.

[0106] The analysis module employs data fusion algorithms, such as weighted summation of the standardized LF / HF ratio and skin conductance response frequency, or principal component analysis to extract their common variance, thereby calculating a comprehensive stress level score between 0 and 100. This score is granular in minutes or hours, forming a stress curve for the entire day.

[0107] S312, perform a correlation analysis between the overall stress level and the type and quality of tasks performed on the day to identify specific tasks or events that cause significant changes in the overall stress level; the correlation analysis can use a time series segment alignment method, first dividing the day into different time periods according to task performance, then calculating the average overall stress level within each task time period and comparing it with the baseline stress level before that task time period.

[0108] Furthermore, event sequence analysis or cross-lag correlation analysis can be used to explore whether the occurrence of a specific task type systematically leads to a significant increase or decrease in overall stress levels over subsequent time periods. Through the accumulation and statistical analysis of large amounts of data, the system can identify which tasks are "high-stress tasks" and which are "relaxing tasks" for a specific individual.

[0109] Furthermore, the analysis considers the quality of task completion, exploring the immediate impact of frustration during task completion on stress. Ultimately, the system can generate an analysis report that clearly identifies which specific tasks or events over a past period were the key triggers that caused statistically significant changes in the monitored individual's stress levels.

[0110] S320, based on the results of association analysis, evaluates the efficacy of different activities on the status of the supervised individuals; generates personalized adjustment suggestions for optimizing subsequent daily task plans; the analysis module of the central management unit will use statistical analysis methods, such as repeated measures ANOVA or mixed effects models, to examine whether there is a statistically significant improvement in the physiological indicators or psychological assessment scores of the supervised individuals before and after participating in specific types of activities.

[0111] For example, the analysis module might calculate the increase in mean heart rate variability of monitored subjects within 24 hours after participating in "horticultural therapy" activities compared to the baseline period, and compare this to the effect of participating in "academic learning." Through this quantitative analysis, the system can objectively assess which activities are most effective in improving anxiety, enhancing concentration, or stabilizing physiological states in specific monitored subjects. Based on this efficacy assessment, the system can generate highly targeted, personalized adjustment suggestions. These suggestions are no longer based on general rules, but rather on the induction and learning from individual historical response data.

[0112] In some embodiments, step S320, which generates personalized adjustment suggestions for optimizing subsequent daily task plans, further includes:

[0113] S321, if data analysis shows that a certain type of activity can significantly improve the physiological indicators and reduce stress levels of the supervised individual, a recommendation to increase the frequency of that type of activity is generated. When the correlation analysis in step S312 and the efficacy assessment in step S320 consistently show that a certain type of activity can significantly reduce the overall stress level score for a supervised individual after participation, and this improvement effect is statistically significant (p-value less than 0.05) and clinically significant, then the system's planning optimization engine will generate a specific recommendation. This recommendation will specify the type of activity and the specific frequency to be increased. For example, if "meditation training" significantly reduces the overall stress level score, then it can be "recommended to increase 'meditation training' from twice a week to four times a week," along with a summary of data evidence supporting the recommendation, such as "Data shows that after participating in this activity, the average stress index decreased by about 30%, and the effect lasted for more than 3 hours." The recommendation will be presented to the supervisor or mental health counselor for their reference when revising the plan for the following week or month.

[0114] S322, if data analysis indicates that the stress level of the monitored individual consistently exceeds a threshold, a scheduling suggestion to reduce high-stimulation activities and increase relaxation activities is generated. The system sets a warning threshold for the overall stress level, which can be based on a group norm or a percentage increase from the individual's baseline. If the system detects that a monitored individual's average daily overall stress level or the percentage of time spent in a high-pressure state consistently exceeds this threshold for several consecutive days, the planning optimization engine will determine that their current task load or content is incompatible. At this time, the engine will activate a protective logic to generate scheduling adjustment suggestions. The core of these suggestions is "reducing the burden" and "easing the burden," specifically: First, identify "high-stimulation activities" in their schedule. These activities can be identified in step S312 or predefined by the system, such as competitive sports, high-intensity assessments, etc., and suggest temporarily reducing or canceling such activities; Second, suggest systematically increasing "relaxation activities" that have been proven effective for the individual in the schedule, such as the activities identified in step S321, or general rest, walking, etc. These recommendations collectively constitute a data-driven, personalized risk avoidance and health promotion program, which aims to help those under supervision recover to a more stable physiological and psychological state by adjusting external stimuli.

[0115] The information exchange system for regulatory facilities provided in this application is centered on a central management unit. By pre-loading encrypted task sequences into wearable devices and relying on regional interaction terminals deployed in various functional areas for near-field authentication and decryption, it achieves precise release and guidance of task information under specific spatiotemporal conditions, ensuring the mandatory and secure execution of processes. The multimodal biometric information acquisition module integrated into the wearable devices enables continuous acquisition of vital sign data streams and contactless identity verification, providing the system with real-time device status and wearer activity monitoring capabilities, and generating physiological state warnings based on personalized baselines. Furthermore, the central management unit can dynamically calculate and adjust the task execution sequence based on real-time uploaded context information, automatically performing time-series replanning and adaptive task flow replacement when tasks time out or abnormal physiological states are detected. Ultimately, by analyzing physiological data, task execution data, and evaluation data over a long period, the system quantifies the effectiveness of different activities, identifies stressors and relief factors, and generates personalized plan optimization suggestions to increase beneficial activities and avoid high-pressure tasks. This forms a continuous improvement closed loop from precise execution to data feedback and then to plan optimization, significantly improving the safety, targeted treatment, and scientific management level of the supervision work.

[0116] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0117] It will be apparent to those skilled in the art that this application is not limited to the details of the exemplary embodiments described above, and that this application can be implemented in other specific forms without departing from the spirit or essential characteristics of this application. Therefore, the embodiments should be considered illustrative and non-limiting in all respects, and the scope of this application is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within this application. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. An information exchange system for regulatory sites, characterized in that, include: The central management unit is used to generate and assign personalized daily task plans to those being monitored. Wearable devices, worn on designated parts of the monitored object's body, include a data storage module, a communication module, a display module, and a biometric information collection module. They are communicatively connected to the central management unit and are used to receive and encrypt the daily task plan, and decrypt and display the task information after authorization. Multiple regional interactive terminals are deployed in various functional areas within the regulatory site and are communicatively connected to the central management unit and the wearable devices. They are used to authenticate and interact with the wearable devices that enter their communication range. The central management unit preloads an encrypted daily task plan sequence into the wearable devices. The wearable devices only decrypt the sequence and display the task information of the current step after moving to the target functional area and successfully authenticating with the corresponding regional interactive terminal.

2. The system according to claim 1, characterized in that, The wearable device is configured to perform device status and wearer identity activity monitoring, specifically including the following steps: S110, continuously collect the wearer's vital signs data stream through the bio-information acquisition module; S120 initiates a contactless authentication process based on a preset strategy or event trigger to confirm the identity of the current wearer; S130, if the vital signs data stream is interrupted for more than a first preset time, or the contactless identity verification process fails continuously, it is determined to be an abnormal state. S140, generate alarm information of the corresponding level, and upload the alarm information to the central management unit through the regional interactive terminal and / or the wearable device.

3. The system according to claim 2, characterized in that, The bio-information acquisition module includes at least an optical sensing unit and an electrophysiological sensing unit. Step S110, which involves continuously acquiring the wearer's vital signs data stream through the bio-information acquisition module, further includes: S111 monitors cardiovascular-related physiological parameters through an optical sensing unit and monitors skin electrical activity through an electrophysiological sensing unit. S112, establish a personalized vital sign baseline based on historical data of the monitored object when it is in a stable state; S113, continuously compare the real-time collected vital sign data with the personalized vital sign baseline, and generate a physiological state warning when a continuous deviation is detected.

4. The system according to claim 2, characterized in that, The step of initiating the contactless authentication process in step S120 further includes: S121, the wearer's biometric information is acquired through the biometric information acquisition module; S122, compare the acquired biometric information with the pre-stored biometric template; S123, if the comparison is successful, the identity verification is confirmed; if the comparison fails, the retry mechanism is initiated and an alarm is triggered after consecutive failures.

5. The system according to claim 1, characterized in that, The system is also used to perform dynamic task planning and guidance, specifically including the following steps: S210, dynamically calculate the task execution sequence based on the daily task plan and the context information uploaded in real time from the wearable device; S220, based on the task completion status, control the regional interactive terminal to interact with the wearable device to guide the next task.

6. The system according to claim 5, characterized in that, The step of dynamically calculating the task execution sequence in step S210 further includes: S211, acquire and update context information from the wearable device in real time, including at least: real-time location, current task status and vital signs data; S212, If the current task is not completed within the planned time, the timing of subsequent affected tasks will be automatically recalculated; S213, if the vital signs data indicate that the wearer is in a preset abnormal physiological state, the task flow is dynamically adjusted to replace the original task with a predefined alternative task.

7. The system according to claim 5, characterized in that, Step S220, which involves controlling the regional interaction terminal to interact with the wearable device to guide the next task, further includes: S221, When the wearable device enters the area of ​​the regional interactive terminal in the target area, two-way authentication is completed; S222, After successful authentication, the wearable device decrypts and displays detailed task information for the current step; S223, wait for and receive a task completion confirmation signal from authorized operators and / or environmental devices. After verifying the task completion confirmation signal, update the task status and prepare for the next task.

8. The system according to claim 1, characterized in that, The system is also used to perform personalized plan optimization based on data feedback, specifically including the following steps: S310, collect and correlate analysis of long-term physiological data, task execution data and evaluation data of the monitored subjects; S320, based on the results of correlation analysis, evaluates the effectiveness of different activities on the status of the regulated object and generates personalized adjustment suggestions for optimizing subsequent daily task plans.

9. The system according to claim 8, characterized in that, Step S310, which involves collecting and correlating long-term physiological data, task execution data, and evaluation data, further includes: S311, based on heart rate variability and skin conductance data, quantifies the overall stress level of the monitored subject throughout the day; S312, perform a correlation analysis between the overall stress level and the type and quality of tasks performed on the day, and identify specific tasks or events that cause significant changes in the overall stress level.

10. The system according to claim 8 or 9, characterized in that, Step S320, which generates personalized adjustment suggestions for optimizing subsequent daily task plans, further includes: S321, If ​​data analysis shows that a certain type of activity can significantly improve the physiological indicators of the regulated subjects and reduce their stress levels, then a recommendation to increase the frequency of such activities is generated. S322 If data analysis indicates that the stress level of the regulated entity is consistently higher than the threshold, then a scheduling recommendation to reduce highly stimulating activities and increase relaxing activities is generated.

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