Unregistered check-in condition monitoring method and system

Abstract

The invention discloses an unregistered check-in condition monitoring method and system. The monitoring method comprises the following steps: acquiring trampling data by at least adopting an array type pressure-sensitive capacitance sensor arranged in a ground mat at a room doorway, and extracting behavior characteristics; and when the newly added behavior features exceeding the registered feature range are identified, determining that the non-registered check-in condition exists. A regionalized monitoring mode is adopted, only treading data of a local area needs to be monitored, comprehensive laying is not needed, basic behavior characteristics of registered personnel are mainly recorded, unregistered personnel are screened out, abnormal conditions are recognized, data processing is simplified, dependence on a network is reduced, and system stability is improved; meanwhile, the problem of privacy leakage caused by comprehensive monitoring of behavior characteristics is also avoided; besides, the regional distributed pressure-sensitive capacitor is adopted to monitor biological information, obtained data is high in reliability and anti-interference, real situations can be accurately fed back, precision and resolution are high, and accuracy and stability of system operation are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of personnel activity monitoring, and in particular to a method and system for monitoring unregistered check-in conditions. Background Art

[0002] In recent years, the global tourism and hotel industries have developed rapidly, bringing more complex room management needs, especially real-time monitoring of room occupancy. With the surge in the number of tourists, the phenomenon of unregistered check-ins has become more frequent, which not only causes trouble for hotel management, but also poses a potential threat to the personal safety of users. In order to effectively solve this problem, the hotel industry currently relies mainly on two methods: manual room inspections and camera monitoring. Although manual room inspections can effectively grasp the occupancy situation, this method is time-consuming and labor-intensive, wastes a lot of human resources, and may disturb users and affect their stay experience. Camera monitoring can provide a certain degree of security, but in the process of implementation, it often causes users to worry about their privacy rights. Therefore, how to find a balance between ensuring security and protecting privacy has become a challenge that needs to be solved in hotel management.

[0003] Not only hotels, but other places such as inpatient wards also have the risk of unregistered persons breaking in, and unregistered entry also needs to be monitored.

[0004] Pressure sensors, with their high sensitivity and accuracy, can respond quickly and accurately detect tiny pressure changes, which makes them widely used in many fields. Due to their small size, light weight and simple preparation process, pressure sensors are widely used in industrial automation, automobile manufacturing, medical equipment and other fields. Especially in the fields of construction and security, pressure sensors are often used for ground pressure monitoring. Through sensors placed on floors, door mats or stairs, they can sense the entry and exit and activities of people in real time.

[0005] This application is particularly suitable for places such as hotels and hospitals that need to monitor the dynamics of people in guest rooms or wards. Through the signal changes detected by the pressure sensor, the occupancy status of the room, the number of people entering and leaving, and even different individuals can be identified by analyzing the pressure pattern. Compared with traditional camera monitoring, this monitoring method is more privacy-friendly and does not rely on video acquisition, but provides security management data through mechanical information.

[0006] However, there are still many problems to be solved in the current application of pressure sensors in personnel activity monitoring. For example, some pressure sensing solutions require complete laying, which is costly; some pressure sensing solutions are prone to interference and unreliable data; and some pressure sensing solutions excessively obtain detailed motion information, which may cause privacy leaks. Summary of the invention

[0007] In view of the deficiencies in the prior art, an object of the present invention is to provide a method and system for monitoring unregistered check-in.

[0008] In order to achieve the above-mentioned invention object, the technical solution adopted by the present invention includes:

[0009] In a first aspect, the present invention provides a method for monitoring a non-registered check-in situation, comprising:

[0010] At least one array of pressure-sensitive capacitance sensors arranged in a floor mat at the door of the room is used to obtain stepping data, and a behavior feature is extracted based on the stepping data;

[0011] Taking the behavior feature corresponding to the room currently recorded as the registered feature, when the array pressure-sensitive capacitive sensor identifies a new behavior feature that exceeds the range of the registered feature, it is determined that the room is unregistered;

[0012] The behavioral characteristics include the weight, stride length, and step frequency of the person stepping on the mat.

[0013] In a second aspect, the present invention further provides a non-registered check-in monitoring system, comprising:

[0014] A feature monitoring module, for obtaining stepping data by at least using an array pressure-sensitive capacitance sensor arranged in a floor mat at the door of a room, and extracting behavior features based on the stepping data;

[0015] The feature comparison module is used to use the currently recorded behavior features corresponding to the room as registered features. When the array pressure-sensitive capacitive sensor identifies a new behavior feature that exceeds the range of the registered features, it is determined that the room is unregistered.

[0016] Based on the above technical solution, compared with the prior art, the beneficial effects of the present invention at least include:

[0017] The unregistered check-in monitoring method and system provided by the present invention adopt a regionalized monitoring method, which only needs to monitor the trampling data of the local area without the need for comprehensive deployment. It mainly records the basic behavioral characteristics of registered personnel to screen out unregistered personnel and thus identify abnormal situations. Without disturbing the user, it accurately captures the behavioral characteristics of the people entering and leaving, and can not only record the number of times people enter and exit, but also determine whether there are unregistered people entering the room, effectively reducing the need for manual room rounds, simplifying data processing, reducing dependence on the network, and improving system stability. At the same time, it also avoids the problem of privacy leakage caused by traditional camera monitoring or comprehensive monitoring of behavioral characteristics using pressure sensors; in addition, regional distributed piezoceramic capacitors are used to monitor biometric information, and the obtained data has strong reliability and anti-interference, can accurately feedback the real situation, and has high accuracy and resolution, ensuring the accuracy and stability of system operation.

[0018] Moreover, the sensing method through floor mats is highly flexible, easy to install and maintain, and low-cost, making it suitable for a wide range of applications. The real-time transmission of data can timely grasp the dynamics of room occupants, improve management efficiency, and enhance the user's stay experience.

[0019] The above description is only an overview of the technical solution of the present invention. In order to enable those skilled in the art to more clearly understand the technical means of the present application and implement them according to the contents of the specification, the following is a description of the preferred embodiments of the present invention in conjunction with detailed drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a schematic diagram of the structure of a non-registered check-in monitoring system provided by a typical implementation case of the present invention;

[0021] Figure 2 It is a schematic diagram of the structure of a floor mat provided by a typical implementation case of the present invention;

[0022] Figure 3 It is a communication architecture diagram of a non-registered check-in monitoring system provided by a typical implementation case of the present invention. DETAILED DESCRIPTION

[0023] There is no technical solution in the prior art that uses pressure sensor devices to monitor rooms without check-in. Some related technical solutions have different application scenarios. These technical solutions can also be applied to hotel room monitoring, but they all have some thorny problems, such as:

[0024] (1) Chinese invention patent publication number CN202111544787.4: “A management system for elderly people living alone based on the Internet of Things”.

[0025] The invention proposes a management system for elderly people living alone based on the Internet of Things, aiming to improve the safety monitoring of elderly people living alone. The system includes a control center, a monitoring unit, a body data detection module, an environmental detection module, a housing management module and an intelligent floor. Among them, the monitoring unit, the body data detection module, the environmental detection module and the housing management module all communicate with the control center, and the intelligent floor is connected to the monitoring unit. The control center is equipped with a database for storing and recording data, and is connected to the rescue alarm module to send out a distress signal.

[0026] When an elderly person living alone falls, the impact on the smart floor produces pressure changes, triggering the pressure sensor and activating the monitoring unit. The system then monitors the indoor situation, locates the elderly person, and determines whether a fall has occurred. Through the control center, the system can quickly identify the situation and activate the rescue alarm module to ensure that the elderly person can get help in time. This system effectively combines the Internet of Things technology to enhance the real-time monitoring and emergency response capabilities for elderly people living alone.

[0027] (2) Chinese invention patent publication number CN107223038A “Monitoring system with pressure sensor in floor covering”.

[0028] The invention discloses a monitoring system, which is mainly composed of a floor covering with a sheet pressure sensor and a sensor control unit. The sensor control unit includes several key components: first, an analog-to-digital converter (ADC) for providing a raw digital signal, and second, a microcontroller, which is designed to process the raw digital signal to generate a processed digital signal with a smaller bandwidth to achieve efficient data extraction. Finally, a communication module is connected to or integrated into the microcontroller, responsible for receiving the processed digital signal and establishing data communication with one or more database servers, and then transmitting the extracted data to these database servers.

[0029] The monitoring system can monitor the pressure changes on the floor in real time through the integrated chip pressure sensor, and ensure the rapid transmission and storage of monitoring data through efficient data processing and communication functions. This system is suitable for a variety of application scenarios, such as security monitoring, smart home, and elderly care, and helps to achieve real-time monitoring and management of crowd flow and abnormal situations.

[0030] (3) Chinese invention patent publication number CN107631686A, “A deformation-sensitive floor”.

[0031] The patent proposes a deformation-sensitive floor, which includes a monitoring module and an intelligent terminal. When used for the first time, the floor collects and stores the personal information of resident family members through a data acquisition unit. During use, when someone enters the detection area, the data acquisition unit sends the floor deformation signal and time information to the data processing unit, which analyzes this data to determine the cadence, pressure, and standing time, thereby identifying whether it is a family member or an intruder, and transmits the results to the intelligent terminal. This technical solution effectively improves family security.

[0032] (4) Chinese invention patent with publication number CN117758961A, “A smart floor and smart floor assembly”.

[0033] The patent proposes a smart floor and its components, including a floor body and multiple pressure sensors laid on the surface. These sensors can detect pressure information when stepped on, and each is provided with different identification information. The sampler is fixed on the floor body and electrically connected to multiple pressure sensors to obtain the pressure information detected by the sensor and its identification information. By analyzing these pressure data, the system can identify the user's weight, force and other movement states, and determine the user's coordinate position on the smart floor, thereby improving the level of intelligence.

[0034] Most of the existing monitoring systems based on pressure signals mentioned above use piezoelectric and piezoresistive sensors, which are sensitive to ambient temperature and humidity. Therefore, their signal responses may vary in different seasons and are affected by whether the air conditioner is turned on indoors. In addition, the complexity of the system and its high dependence on the network may affect its stability, especially when the network is poor or fails, it may not be able to issue an alarm or provide the required monitoring services in time. The complexity of the system means that regular maintenance and technical support are required to ensure the normal operation of each component, which increases operating costs. Smart floors are customized due to different house specifications and lack portability. In addition, smart floors also need to cover the entire house to achieve blind spot monitoring, so the manufacturing cost is relatively high. In addition, smart floors can monitor and analyze people's behavioral characteristics in real time. If these data are unfortunately leaked and obtained by behavioral experts, they can be analyzed, thereby infringing personal privacy rights, which poses certain risks.

[0035] In view of the deficiencies in the prior art, the inventor of this case has proposed the technical solution of the present invention after long-term research and extensive practice. The technical solution, its implementation process and principle will be further explained as follows.

[0036] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0037] Moreover, relational terms such as “first” and “second” are merely used to distinguish one component or method step from another with the same name, but do not necessarily require or imply any such actual relationship or order between these components or method steps.

[0038] The embodiment of the present invention provides a method for monitoring a non-registered check-in situation, which comprises the following steps:

[0039] At least one array of pressure-sensitive capacitance sensors arranged in a floor mat at the door of the room is used to obtain stepping data, and a behavior feature is extracted based on the stepping data;

[0040] Taking the behavior feature corresponding to the room currently recorded as the registered feature, when the array pressure-sensitive capacitive sensor identifies a new behavior feature that exceeds the range of the registered feature, it is determined that the room is unregistered;

[0041] The behavioral characteristics include the weight, stride length, and step frequency of the person stepping on the mat.

[0042] The application field of the above technical solution is the monitoring of unregistered check-ins in places that need to be controlled, such as hotel rooms or hospital wards, in order to improve the safety management and customer experience of the place. Using array capacitive pressure sensor technology, embedded in the floor mat at the door of the guest room, it automatically collects and analyzes various data related to check-in by real-time monitoring of the pressure changes of people entering and leaving. Through real-time analysis of data, managers can obtain more comprehensive customer flow information, optimize room management and service processes, and improve overall operational efficiency. In addition, the system provides users with an intelligent and convenient check-in experience, ensuring that they feel a safe environment while enjoying high-quality services, while avoiding privacy leaks caused by excessive monitoring of behavioral characteristics.

[0043] The key points of the above scheme are: 1. Array sensor design: The capacitive array sensor made of pressure-sensitive material is unique in circuit design and can eliminate temperature and humidity interference; 2. Easy installation and maintenance: The design takes into account the simplicity of hardware configuration, making system installation and maintenance simpler, thereby reducing operating costs and improving overall stability 3. Unique application scenarios: There is currently no non-invasive way to effectively identify the unregistered check-in of hotel staff. This system not only protects user privacy, but also ensures the personal safety of users, achieving a balance between privacy and security.

[0044] Taking the hotel check-in scenario as an example, after the user checks in and enters the room, the floor mat collects behavioral characteristics such as weight, cadence, and stride length. The cloud server records the collected signals. During the stay, the floor mat can detect the user's entry and exit multiple times. The system continuously learns, corrects the user's behavioral characteristics and strengthens memory. After the user checks out, the system will clear this data to avoid privacy leaks.

[0045] The above technical solution uses floor mats arranged only in the room to collect data. This method is relatively simple, but it is sufficient to achieve basic monitoring of occupancy conditions, and the recognition efficiency and accuracy can meet application requirements. In order to further improve the recognition accuracy and meet the needs of refined management, the embodiment of the present invention also provides a more preferred method, which uses floor mats at the door and the registration desk to achieve collaborative monitoring.

[0046] That is, in some embodiments, the method for monitoring non-registration status specifically includes the following steps:

[0047] A first detector is used to obtain first stepping data at the front desk registration desk, wherein the first detector includes a plurality of first pressure-sensitive capacitors and is arranged in an array in a first floor mat at the front desk registration desk;

[0048] A second detector is used to obtain second stepping data at the door of the room, wherein the second detector includes a plurality of second pressure-sensitive capacitors and is arranged in an array on a second floor mat at the door of the room;

[0049] Extracting a first behavior feature group from the first stepping data, and extracting a second behavior feature group from the second stepping information;

[0050] taking the intersection of the first behavior feature group and the second behavior feature group as the registered feature;

[0051] When a behavior feature not included in the first behavior feature group is added to the second behavior feature group, it is determined that there is an unregistered occupant in the corresponding room.

[0052] In order to further improve privacy and avoid data accumulation, in some embodiments, the method for monitoring non-registration may further include the following steps:

[0053] When the room corresponding to any of the behavioral features is checked out, the record of the corresponding behavioral feature is deleted.

[0054] In practical applications, in order to achieve the above purpose, a necessary procedure is to identify which room corresponds to which or which behavior characteristics. Therefore, based on the above solution, the present invention proposes that in some implementation schemes, the process of identifying the room corresponding to any of the behavior characteristics specifically includes the following sub-steps:

[0055] When the room is checked in, the behavior features to be selected in the first behavior feature group within a set time before and after the check-in time are obtained; for example, when checking in, the behavior features to be selected in the first behavior feature group within 1 minute or 5 minutes before and after the check-in time are extracted, and the specific time can be adjusted appropriately.

[0056] When the first stepping on the second floor mat by a person corresponding to any one of the to-be-selected behavior characteristics is received, it is identified that the behavior characteristic corresponds to the room.

[0057] The idea behind the above implementation is that the intersection screening method of the two floor mats at the registration desk and the door can more accurately identify the corresponding person. Some scenarios, for example, when checking in, there are often other people present at the same time, such as people who are consulting or waiting in line. At this time, if all the people sensed by the first floor mat are regarded as the corresponding people of the registered room, it will cause recognition anomalies, and other people will be deleted at check-out, causing errors (for example, people in other rooms in the queue may be close to the people in this room during registration and recognized by the first floor mat, deleted when checking out of this room, and subsequently regarded as unregistered guests); and when registering, it is also possible that the cleaning staff has not left the room. If only relying on the information sensed by the second floor mat to identify the person, the cleaning staff may be mistakenly identified as the person in the room, resulting in data redundancy and anomalies. Therefore, the optimization method of the present invention adopts the form of collaborative identification of two floor mats to avoid interference from other people.

[0058] The above content introduces how to monitor personnel, and regarding the data processing and analysis of the monitored behavioral characteristic data, in some embodiments, the method for monitoring non-registered check-in conditions may also include the following steps:

[0059] A machine learning algorithm is used to classify the behavior characteristics into behavior patterns, wherein the classification categories include normal entry and exit, long-term stay, and abnormal activities, wherein the abnormal activities include entry and exit frequency exceeding a preset value, falling, and jumping;

[0060] When the behavior pattern corresponding to any of the behavior characteristics is identified as an abnormal entry and exit pattern, it is determined that the behavior of the corresponding person is abnormal.

[0061] In some implementation schemes, a clustering algorithm may be used to perform cluster analysis on a plurality of the behavioral features in any of the behavioral patterns to form a plurality of subclasses and mark them.

[0062] Corresponding to the above-mentioned non-registered check-in monitoring method, an embodiment of the present invention further provides a non-registered check-in monitoring system, which includes:

[0063] A feature monitoring module, for obtaining stepping data by at least using an array pressure-sensitive capacitance sensor arranged in a floor mat at the door of a room, and extracting behavior features based on the stepping data;

[0064] The feature comparison module is used to use the currently recorded behavior features corresponding to the room as registered features. When the array pressure-sensitive capacitive sensor identifies a new behavior feature that exceeds the range of the registered features, it is determined that the room is unregistered.

[0065] Corresponding to the preferred solution of using two floor mats for collaborative monitoring in the present invention, the system may further specifically include:

[0066] A first monitoring module, used for acquiring first stepping data at the front desk registration desk by using a first detector, wherein the first detector includes a plurality of first piezoceramic capacitors and is arranged in an array in a first floor mat at the front desk registration desk;

[0067] A second detection module, used for acquiring second stepping data at the door of the room by using a second detector, wherein the second detector includes a plurality of second piezoceramic capacitors and is arranged in an array on a second floor mat at the door of the room;

[0068] The feature comparison module is specifically used to extract a first behavior feature group from the first stepping data, and to extract a second behavior feature group from the second stepping information. When a behavior feature not included in the first behavior feature group is added to the second behavior feature group, it is determined that there is an unregistered check-in situation in the monitored place.

[0069] In some embodiments, the system also includes a CDC chip and a communication module, wherein the CDC chip is electrically connected to the varistor capacitor and is used to convert the analog signal fed back by the varistor capacitor into a digital signal; the communication module is communicatively connected to the CDC chip and is used to transmit the digital signal to a data processing device.

[0070] In some embodiments, each independent ground mat or detector of the system further includes a first power supply and a second power supply, wherein the first power supply supplies power to the varistor and the CDC chip, and the second power supply supplies power to the communication module. Since the present invention preferably adopts wireless communication, the power of the communication module is slightly higher and there is obvious power fluctuation. Therefore, the preferred method of the present invention adopts a dual power supply method to avoid the interference of the power fluctuation of the communication module to the capacitance detection. This interference is not significant in the monitoring of traditional varistor, so the public power supply method is often adopted in the traditional resistive sensing scheme.

[0071] In some embodiments, the data processing device includes a cloud server, and the communication module is a wireless data module that wirelessly communicates with the cloud server; the monitoring system also includes a data terminal that is communicatively connected to the cloud server.

[0072] In some embodiments, the number of arrangement of the pressure-sensitive capacitor arrays in the first ground pad and the second ground pad is not less than 6×4.

[0073] Based on the above technical solution, the present invention integrates an array type pressure-sensitive capacitive sensor (data acquisition module) and a data processing module in a floor mat, wherein the array type capacitive pressure sensor is arranged in 4×8 or 4×6, the floor mat size is 1.2m×1.2m, and the floor mat is installed at the entrance of the hotel guest room. The high sensitivity and accuracy of the pressure-sensitive capacitive sensor enable this floor mat to accurately capture the characteristics of people entering and leaving (such as weight, cadence, and stride) without disturbing the user. It can not only record the number of people entering and leaving, but also determine whether there are unregistered people entering the room by analyzing the pressure distribution pattern. This monitoring function based on pressure signals effectively reduces the need for manual room inspections and avoids the privacy infringement problems that may be caused by camera monitoring. In addition, the floor mat is simple in design and easy to install, and its cost is relatively low due to its small size, and it is suitable for various ground types and places. Through seamless docking with the hotel management system, the data collected by the floor mat can be transmitted in real time, helping hotel managers to grasp the status of guest rooms in a timely manner, thereby improving management efficiency and ensuring user safety. This technical solution not only enhances the hotel's safety management capabilities, but also improves the customer's stay experience.

[0074] The technical solution of the present invention is further described in detail below through several embodiments and in conjunction with the accompanying drawings. However, the selected embodiments are only used to illustrate the present invention, and do not limit the scope of the present invention.

[0075] Example 1

[0076] This embodiment designs a highly sensitive array pressure monitoring system based on the principle of pressure-sensitive capacitance sensor. Figure 1-3 As shown in the figure, the system consists of a data acquisition unit (array type pressure-sensitive capacitance sensor), a data processing unit (MCU module, power supply module, 4G module), a server cloud and an intelligent terminal.

[0077] The sensor module consists of 8×4 or 6×4 piezoceramic capacitive sensors. Each sensor, as the basic unit of the module, is responsible for sensing the pressure applied to it and converting it into an analog signal. Each sensor consists of a pair of parallel electrodes, and the electrodes are filled with a material with pressure-sensitive properties. When external pressure is applied to any piezoceramic capacitive sensor, the piezoceramic material will deform, causing the distance between the electrodes at that point to change, thereby causing a corresponding change in the capacitance value. Each piezoceramic capacitive sensor works independently and can accurately capture the pressure changes applied to it. By designing these piezoceramic capacitive sensors into a sensor array, the pressure changes at various locations and different intensities on the floor mat can be monitored in real time. Due to the array design, the system can work simultaneously with multiple piezoceramic capacitive sensors to form a dense sensor network. This design not only improves the sensitivity and response speed of the system, but also achieves full coverage of the floor mats at the door of the hotel guest rooms.

[0078] During the data acquisition process, the acquisition mainboard communicates with the pressure-sensitive capacitance sensor through the SPI interface, and uses the NSS chip select port to select different sensors to achieve one host and multiple slaves. The sensor module realizes time division multiplexing by traversing scanning. After each sensor detects the capacitance change, it converts the capacitance change into an analog electrical signal. This conversion is achieved by the built-in signal conditioning circuit of the pressure-sensitive capacitance sensor, which can effectively filter noise and enhance the strength of the signal. These analog signals are then converted into digital signals by the acquisition chip CDC (capacitance digital converter), so that the signals can be subsequently processed and analyzed in digital form, which is convenient for data storage and transmission, and ensures that the system can respond to abnormal situations in a timely manner during the monitoring process. The CDC chip not only has high-precision conversion capabilities, but also has the characteristics of fast response, and can sample and convert the signals of multiple sensors in a short time. After receiving the data from the CDC chip, the MCU module will perform further processing, including data filtering (such as mean filtering and Kalman filtering). In the data processing stage, fast-changing data is processed by Kalman filtering, while slowly changing data is processed using mean filtering to improve data quality. Through this signal processing process, the system can obtain the pressure change data of each sensor in real time, thereby improving the reliability and consistency of the data. In addition, the CDC chip uses advanced data analysis algorithms to deeply process these digital signals. These algorithms include real-time signal filtering, anomaly detection and pattern recognition, which can effectively extract useful information and eliminate noise interference. After standard capacitance calibration, the digital signal output by the CDC chip can correspond to the input capacitance through a linear fitting equation, which can be well applied to scenarios that are sensitive to capacitance changes.

[0079] All piezoceramic capacitive sensors are connected to the central processing circuit in parallel to form an efficient data collection network. This parallel design ensures that the signal of each piezoceramic capacitive sensor can be transmitted to the central processing unit quickly and accurately, thereby improving the response speed and flexibility of the system. The 4G module built into the central processing circuit realizes the real-time data upload function, so that the processed data can be quickly transmitted to the cloud server. The 4G module uses the MQTT protocol to interact with the cloud platform to support long connections and reduce data packet loss. This fast data transmission capability enables the system to monitor at any time and any place, thereby providing real-time situation feedback to the back-end managers. In the cloud, the uploaded data is first pre-processed, such as denoising and normalization, to eliminate external interference and improve the quality of the data. Subsequently, the system software extracts features from this data, identifies dynamic features such as cadence, stride, and pressure change rate, and corresponds these features to the registered users.

[0080] The power supply part of each floor mat of the above-mentioned monitoring system is powered by a DC power supply, and the voltage can be selected as 9V or 12V. It is specifically designed as two-way power supply: one of which is dedicated to providing power for the 4G module, and the other is used to supply other functional modules of the entire floor mat, such as piezoceramic capacitive sensors and CDC chips. The reason for this design is: since the peak power consumption of the 4G module can reach 3.8V / 1.5A, the current demand is large and changes rapidly, which may cause voltage output fluctuations. In order to avoid such fluctuations affecting other functions of the acquisition board, especially the interference with piezoceramic capacitive sensors and CDC chips, the system provided in this embodiment is designed to divide the power supply into two ways to ensure that the voltage fluctuation of the 4G module will not interfere with the stability and performance of the entire system.

[0081] On the cloud server side, the system can combine time information and use regression analysis (such as linear regression and support vector regression) to estimate the number of times people enter and exit the room. By analyzing the signals collected by each sensor, information such as pedaling force, cadence, and stride can be obtained. Specifically, the effective number of pedaling and the distance of each step can be calculated by analyzing the pressure values ​​and timestamps of multiple pressure-sensitive capacitive sensors. At the same time, machine learning algorithms (such as decision trees, random forests, convolutional neural networks (CNNs), etc.) can also be applied to classify different behavior patterns, including normal entry and exit, long stays, or abnormal activities (such as frequent entry and exit, falls, jumps, etc.). By training the model to identify the normal behavior baseline, once the data deviates from the baseline, the system will be able to quickly issue an alarm indicating that someone other than the registered tenant has entered the room; when the tenant checks out, the system will be reset to continue monitoring whether the tenant who enters the room again has abnormal behavior and has not registered to check in. In addition, the system also applies clustering algorithms (such as K-means and one-class support vector machine One-Class SVM) to further analyze and identify abnormal behavior. This technical solution ensures the efficiency and real-time performance of the system, which not only improves the data processing capabilities, but also enhances the accessibility of information, facilitating subsequent decision-making and management.

[0082] Based on the above implementation cases, it can be known that the technical solution proposed by the present invention has at least the following advantages:

[0083] (1) Real-time monitoring and learning: The floor mat can collect the user's weight, cadence, stride and other behavioral characteristics in real time. When the user enters the room after checking in, the floor mat will collect their weight, cadence, stride and other behavioral characteristics. The cloud server records the collected signals. During the stay, the floor mat can detect the user's entry and exit multiple times. The system continuously learns, corrects the user's behavioral characteristics and strengthens memory. After the user checks out, the system will clear this data to avoid privacy leakage. In a more preferred solution, the floor mats in the two areas of the registration desk and the room door are collaboratively screened to accurately match the behavioral characteristics of the person and the corresponding room to avoid interference, which is conducive to more efficient and refined management.

[0084] (2) Easy installation and maintenance: The functional modules are integrated into the floor mat rather than the floor, which simplifies hardware configuration and system maintenance. It only needs to be installed at the entrance of the guest rooms (in some preferred solutions, it only needs to be installed at the registration desk), which reduces costs and avoids the complexity of large-scale laying.

[0085] (3) Portability and mobility: The flexible and small size of the floor mat makes it easy to move. It can be used by simply connecting to a power source and can adapt to different surfaces with high flexibility.

[0086] (4) Focus on functions and stability: The system mainly records the basic behavioral characteristics of registered users and monitors and alarms unregistered visitors. Once the system detects a situation that does not match the recorded behavioral characteristics, it will perform exception processing. Therefore, the design of the data processing module is relatively simple and has low dependence on the network, which helps to improve the stability of the system.

[0087] (5) Since the data acquisition module uses a piezoceramic capacitive sensor, the signal acquisition process of the system is not affected by the external temperature and humidity. Compared with the widely used resistive and piezoelectric sensors on the market, the piezoceramic capacitive sensor has higher accuracy and resolution, and is more resistant to temperature and humidity interference, thus ensuring the accuracy and stability of the system operation.

[0088] (6) Enhanced security management capabilities: The system uses the data processing module and cloud server to compare the basic behavioral characteristics of the tenants collected with the registration information of the venue management system, which can achieve efficient personnel flow recording and management, thereby enhancing the security management capabilities of the venue.

[0089] It should be understood that the above embodiments are only for illustrating the technical concept and features of the present invention, and their purpose is to enable people familiar with the technology to understand the content of the present invention and implement it accordingly, and they cannot be used to limit the protection scope of the present invention. Any equivalent changes or modifications made according to the spirit of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for monitoring non-registered check-in, characterized in that: include: At least one array of pressure-sensitive capacitance sensors arranged in a floor mat at the door of the room is used to obtain stepping data, and a behavior feature is extracted based on the stepping data; Taking the behavior feature corresponding to the room currently recorded as the registered feature, when the array pressure-sensitive capacitive sensor identifies a new behavior feature that exceeds the range of the registered feature, it is determined that the room is unregistered; The behavioral characteristics include the weight, stride length, and step frequency of the person stepping on the mat.

2. The method for monitoring non-registered check-in according to claim 1, characterized in that: Also includes: When a room corresponding to any of the behavioral features is checked out, the records related to the corresponding behavioral features are deleted.

3. The method for monitoring non-registered check-in according to claim 1 or 2, characterized in that: Specifically include: A first detector is used to obtain first stepping data at the front desk registration desk, wherein the first detector includes a plurality of first pressure-sensitive capacitors and is arranged in an array in a first floor mat at the front desk registration desk; A second detector is used to obtain second stepping data at the door of the room, wherein the second detector includes a plurality of second pressure-sensitive capacitors and is arranged in an array on a second floor mat at the door of the room; Extracting a first behavior feature group from the first stepping data, and extracting a second behavior feature group from the second stepping information; The intersection of the first behavior feature group and the second behavior feature group is used as the registered feature.

4. The method for monitoring non-registered check-in according to claim 3, characterized in that: The process of identifying a room corresponding to any of the above-mentioned behavior features specifically includes: When the room is checked in, obtaining the behavior features to be selected in the first behavior feature group within a set time period before and after the check-in time; When the first stepping on the second floor mat by a person corresponding to any one of the to-be-selected behavior characteristics is received, it is identified that the behavior characteristic corresponds to the room.

5. The method for monitoring non-registered check-in according to claim 1, characterized in that: Also includes: A machine learning algorithm is used to classify the behavioral features into behavioral patterns, wherein the classification categories include normal entry and exit, long-term stay, and abnormal activities, wherein the abnormal activities include entry and exit frequency exceeding a preset value, falling, and jumping; When the behavior pattern corresponding to any of the behavior characteristics is identified as an abnormal entry and exit pattern, it is determined that the behavior of the corresponding person is abnormal.

6. The method for monitoring non-registered check-in according to claim 5, characterized in that: A clustering algorithm is used to perform cluster analysis on a plurality of the behavioral features in any of the behavioral patterns to form a plurality of subclasses and mark them.

7. A non-registered check-in monitoring system, characterized in that: include: A feature monitoring module, for obtaining stepping data by at least using an array pressure-sensitive capacitance sensor arranged in a floor mat at the door of a room, and extracting behavior features based on the stepping data; The feature comparison module is used to use the currently recorded behavior features corresponding to the room as registered features. When the array pressure-sensitive capacitive sensor identifies a new behavior feature that exceeds the range of the registered features, it is determined that the room is unregistered.

8. The non-registered check-in monitoring system according to claim 7, characterized in that It also includes a CDC chip and a communication module, wherein the CDC chip is electrically connected to the array type pressure sensitive capacitance sensor and is used to convert the analog signal fed back by the array type pressure sensitive capacitance sensor into a digital signal; The communication module is in communication connection with the CDC chip and is used for transmitting the digital signal to a data processing device.

9. The non-registered check-in monitoring system according to claim 8, characterized in that: It also includes a first power supply and a second power supply, wherein the first power supply supplies power to the array pressure-sensitive capacitive sensor and the CDC chip, and the second power supply supplies power to the communication module.

10. The non-registration check-in monitoring system according to claim 8, characterized in that: The data processing device includes a cloud server, and the communication module is a wireless data module that communicates wirelessly with the cloud server; the monitoring system also includes a data terminal, and the data terminal is communicatively connected to the cloud server.

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