Methods and systems for managing abnormal room status in long-term rental apartments

Abstract

This application provides a method and system for managing abnormal room status in long-term rental apartments. The management method includes: acquiring event data of the target room; generating an event feature set based on the event data; acquiring lease data to determine the room status identifier of the target room; confirming the baseline parameter set of the target room based on the room status identifier; calculating a deviation set based on the event feature set and the baseline parameter set, and generating an anomaly score based on the deviation set; determining the handling level based on the anomaly score; if the room status identifier indicates occupancy: when the handling level is the alert level, sending an alert message to the resident's terminal; when the handling level is the confirmation level, initiating a confirmation request to the resident's terminal, and initiating a confirmation request to a preset contact person if no confirmation feedback is received; when the handling level is the emergency intervention level, verifying the emergency entry authorization based on preset authorization chain rules, and generating an emergency electronic key when the verification passes.

Description

Technical Field

[0001] This application relates to the technical field of smart apartments, specifically to a method and system for managing abnormal room status in long-term rental apartments. Background Technology

[0002] Long-term rental apartments typically provide long-term accommodation services to single individuals or couples through standardized housing units and centralized operations. Projects can range in size from dozens to thousands of units. Unlike traditional individual rentals, long-term rental apartments have more concentrated housing units, higher occupancy rates, and faster occupancy rates. Operators need to continuously monitor the rooms for potential safety hazards, unusual occupancy, equipment malfunctions, and other risks without disrupting residents' normal lives.

[0003] Long-term rental apartment residents have significant privacy and independent living characteristics, making it difficult and inappropriate for operators to verify room status through frequent door-to-door checks. When residents are absent for extended periods, experience sudden illness, or have accidents, there is often a lack of timely warning signs and reliable evidence, making it difficult for operators to identify and intervene promptly. If a tenant experiences a sudden risk in their room that goes undetected, it can not only result in loss of life and property but also trigger subsequent issues related to liability determination, dispute resolution, and public opinion risks. Summary of the Invention

[0004] This application provides a method and system for managing abnormal room status in long-term rental apartments, which improves the accuracy of room status identification and the timeliness of handling abnormal room status.

[0005] Firstly, this embodiment provides a method for managing abnormal room status in long-term rental apartments, including the following steps: Acquire event data of the target room within a preset observation time window, wherein the event data includes at least access control data, resource metering data, and alarm data; Based on the event data, an event feature set for the target room is generated; Obtain the rental data of the target room to determine the room status identifier of the target room, the room status identifier including at least the occupied status and the vacant status; The baseline parameter set of the target room is determined based on the room status identifier, and the baseline parameter set includes at least a dynamic threshold set for the event feature set; Based on the event feature set and the baseline parameter set, a deviation set is calculated, and an anomaly score is generated based on the deviation set; The handling level is determined based on the anomaly score. When the room status is identified as occupied, the handling level includes at least an alert level, a confirmation level, and an emergency intervention level. If the room status is identified as occupied: When the handling level is a reminder level, a reminder message is sent to the resident's terminal; or, When the handling level is a confirmation level, a confirmation request is sent to the resident's terminal, and if no confirmation feedback is received, a confirmation request is sent to a preset contact person; or... When the handling level is the emergency intervention level, the emergency entry authorization is verified based on the preset authorization chain rules, and an emergency electronic key is generated when the verification is successful.

[0006] In some embodiments, the step of determining the baseline parameter set of the target room based on the room status identifier, wherein the baseline parameter set includes at least a dynamic threshold set for the event feature set, includes: When the room status is identified as occupied and the number of occupied sample data for the target room is greater than or equal to a first threshold, the baseline parameter set of the target room is determined as a personalized baseline parameter set. The personalized baseline parameter set is generated based on historical event data within the current lease period of the target room. The number of occupied sample data refers to the number of event data within the current lease period of the target room. When the room status is identified as occupied, and the number of occupied room samples is less than a first threshold and greater than a second threshold, a preliminary baseline parameter set is generated based on the number of occupied rooms, and a regular baseline parameter set is obtained. The regular baseline parameter set and the preliminary baseline parameter set are then fused based on dynamic weights to generate the baseline parameter set for the target room. The regular baseline parameter set is generated based on historical event data of rooms of the same type. When the room status is identified as occupied, and the number of occupied samples is less than or equal to the second threshold, the baseline parameter set of the target room is determined to be the regular baseline parameter set. When the room status is identified as vacant, the baseline parameter set of the target room is determined as the vacant baseline parameter set; the vacant baseline parameter set is generated based on historical vacant samples of the target room or similar vacant room samples.

[0007] In some embodiments, generating the baseline parameter set for the target room based on dynamically weighted fusion of the conventional baseline parameter set and the preliminary baseline parameter set includes: The fusion weight is calculated based on the number of in-housing samples N of the target room. fusion weight for: ,in N1 is the first threshold, and N2 is the second threshold.

[0008] In some embodiments, the deviation set includes: active offset and risk offset, and the step of calculating the deviation set based on the event feature set and the baseline parameter set, and generating anomaly scores based on the deviation set includes: Obtain the dynamic threshold ranges for access control data, resource metering data, and alarm data from the baseline parameter set; When the corresponding data of all the event feature sets fall within the corresponding dynamic threshold range, the deviation of the event feature is determined to be zero, and the anomaly score is zero; or, When the corresponding data of the event feature set does not fall into the corresponding dynamic threshold interval, a data deviation is generated based on the distance between the corresponding data and the dynamic threshold interval of the corresponding data, and the data deviation is normalized to limit the data deviation to a preset range. The active offset is determined based on the normalized data offset of access control data and resource metering data; The risk offset is determined based on the data offset after alarm data normalization. The anomaly score is determined based on the active offset and the risk offset.

[0009] In some embodiments, determining the anomaly score based on the active offset and the risk offset includes: When the risk offset is greater than or equal to the risk threshold, the anomaly score is configured as the anomaly score threshold; When the risk offset is less than the risk threshold, the active offset and the risk offset are weighted and calculated based on a preset weight to obtain the anomaly score; wherein the anomaly score satisfies: Wherein, S is the abnormal score. For the active offset, The risk offset is, and Preset weights.

[0010] In some embodiments, when the room status is identified as vacant, the handling level includes a recording level, a verification level, and an emergency intervention level. The long-term rental apartment room status anomaly control method further includes: If the room status indicator is vacant: When the handling level is the recording level, the allowed and unallowed entry time windows associated with the target room are obtained. Access control events that occur within the preset observation time window and fall into the set of allowed entry time windows are marked as operational access events, and operational trace records are generated. When the preset observation time window and the set of allowed entry time windows do not overlap, access control events that occur within the preset observation time window are marked as unallowed access events, and violation trace records are generated. When the handling level is the verification level, a verification request is initiated to the operation terminal. The verification request is used to trigger a preset verification operation. The preset verification operation includes at least one of on-site verification or freezing of the temporary electronic key associated with the target room. When the handling level is the emergency intervention level, the emergency entry authorization is verified based on the preset authorization chain rules, and an emergency electronic key is generated when the verification is successful.

[0011] In some embodiments, the emergency electronic key is configured to carry door lock binding information, effective time window information, and maximum number of uses information; the emergency electronic key is in an inactive state when it is generated, and switches from an inactive state to an active state after the on-site verification conditions are met.

[0012] In some embodiments, the preset authorization chain rule includes multi-party confirmation conditions, which include at least one of the following: confirmation is completed by two authorizers with different roles; or confirmation is completed by one authorizer and the abnormal score reaches the abnormal score threshold.

[0013] In some embodiments, obtaining the permitted and prohibited entry time windows associated with the target room includes: Obtain the operational task information of the target room; wherein, the operational task information includes at least: task type and appointment time window corresponding to the task type, and the task type includes at least one of showing, room turnover, inspection and maintenance; The permitted entry time window is determined based on the reservation time window in the operation task information, and the time period outside the permitted entry time window is determined as the non-permitted entry time window; the permitted entry time window is the union of at least one reservation time window that meets the preset valid conditions.

[0014] Secondly, a long-term rental apartment room status anomaly control system includes: The acquisition module is used to acquire event data of the target room within a preset observation time window. The event data includes at least access control data, resource metering data, and alarm data. An event feature generation module is used to generate an event feature set for the target room based on the event data; The room status confirmation module is used to obtain the rental data of the target room and determine the room status identifier of the target room, which includes at least the occupied status and the vacant status. The baseline parameter set confirmation module is used to confirm the baseline parameter set of the target room based on the room status identifier. The baseline parameter set includes at least a dynamic threshold set for the event feature set. The scoring module is used to calculate a deviation set based on the event feature set and the baseline parameter set, and to generate an anomaly score based on the deviation set; The level confirmation module is used to determine the handling level based on the anomaly score; when the room status is identified as occupied, the handling level includes at least an alert level, a confirmation level, and an emergency intervention level. The execution module is configured to: if the room status identifier indicates an occupied state; when the handling level is an alert level, send an alert message to the resident terminal; or, when the level is a confirmation level, initiate a confirmation request to the resident terminal and, if no confirmation feedback is received, initiate a confirmation request to a preset contact person; or, when the handling level is an emergency intervention level, verify the emergency entry authorization based on preset authorization chain rules and generate an emergency electronic key when the verification passes.

[0015] This embodiment of the application collects access control data, resource metering data, and alarm data of target rooms within a preset observation time window to generate an event feature set characterizing room behavior and risk status. This feature set is then combined with the target room's lease data to determine room status identifiers, thereby matching corresponding baseline parameter sets to different room statuses. Further, this embodiment compares the event feature set with a dynamic threshold set included in the baseline parameter set to calculate a deviation set, generating an anomaly score. Based on the anomaly score, it determines the handling levels, such as alerts, confirmations, and emergency interventions. In the occupancy status, a tiered process of "alert—confirmation—emergency intervention" triggers verification and handling by the resident and preset contacts. During emergency intervention, authorization is verified based on preset authorization chain rules, and an emergency electronic key is generated. Therefore, this embodiment achieves quantitative identification and tiered handling of room status anomalies without relying on frequent on-site inspections, improving the accuracy of room status anomaly identification and the timeliness of handling. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a flowchart illustrating a method for managing abnormal room status in long-term rental apartments provided in some embodiments of this application; Figure 2 This is another flowchart illustrating the method for managing abnormal room status in long-term rental apartments provided in some embodiments of this application; Figure 3 This is another flowchart illustrating a method for managing abnormal room status in long-term rental apartments provided in some embodiments of this application. Detailed Implementation

[0018] 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. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0019] "A and / or B" includes the following three combinations: A only, B only, and a combination of A and B.

[0020] The use of "applies to" or "configured to" in this application implies open and inclusive language, which does not exclude the applicability to or configuration to devices performing additional tasks or steps. Additionally, the use of "based on" implies openness and inclusivity, because processes, steps, calculations, or other actions "based on" one or more of the stated conditions or values ​​may in practice be based on additional conditions or values ​​beyond those stated.

[0021] In this application, the term "exemplary" is used to mean "used as an example, illustration, or description." Any embodiment described as "exemplary" in this application is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is provided to enable any person skilled in the art to make and use this application. Details are set forth in the following description for purposes of explanation. It should be understood that those skilled in the art will recognize that this application can be made without using these specific details. In other instances, well-known structures and processes are not described in detail to avoid obscuring the description of this application with unnecessary detail. Therefore, this application is not intended to be limited to the embodiments shown, but is consistent with the broadest scope of the principles and features disclosed in this application.

[0022] As described in the background section, long-term rental apartments typically provide long-term accommodation services to single individuals or couples through standardized housing units and centralized operations. Project sizes can range from dozens to thousands of units. Unlike traditional individual rentals, long-term rental apartments have more concentrated housing units, higher occupancy rates, and faster staff turnover. Operators need to continuously monitor for potential safety hazards, unusual occupancy, equipment malfunctions, and other risks in the rooms without disrupting residents' normal lives.

[0023] Long-term rental apartment residents have significant privacy and independent living characteristics, making it difficult and inappropriate for operators to verify room status through frequent door-to-door checks. When residents are absent for extended periods, experience sudden illness, or have accidents, there is often a lack of timely warning signs and reliable evidence, making it difficult for operators to identify and intervene promptly. If a tenant experiences a sudden risk in their room that goes undetected, it can not only result in loss of life and property but also trigger subsequent issues related to liability determination, dispute resolution, and public opinion risks.

[0024] Therefore, to improve the accuracy of identifying and promptly addressing abnormal room status in long-term rental apartments, this application discloses a method for managing abnormal room status in long-term rental apartments. (Refer to...) Figure 1 It includes: S100: Acquire event data of the target room within a preset observation time window, wherein the event data includes at least access control data, resource metering data, and alarm data; S200: Generate an event feature set for the target room based on the event data; S300: Obtain the rental data of the target room and determine the room status identifier of the target room, the room status identifier including at least the occupied status and the vacant status; S400: Confirm the baseline parameter set of the target room based on the room status identifier, wherein the baseline parameter set includes at least a dynamic threshold set for the event feature set; S500: Calculate the deviation set based on the event feature set and the baseline parameter set, and generate an anomaly score based on the deviation set; S600: Determine the handling level based on the anomaly score. When the room status is identified as occupied, the handling level includes at least an alert level, a confirmation level, and an emergency intervention level. S700: If the room status identifier indicates an occupied state: when the handling level is an alert level, send an alert message to the resident's terminal; or, when the handling level is a confirmation level, initiate a confirmation request to the resident's terminal, and if no confirmation feedback is received, initiate a confirmation request to a preset contact person; or, when the handling level is an emergency intervention level, verify the emergency entry authorization based on preset authorization chain rules, and generate an emergency electronic key when the verification passes.

[0025] This embodiment of the application collects access control data, resource metering data, and alarm data of target rooms within a preset observation time window to generate an event feature set characterizing room behavior and risk status. This feature set is then combined with the target room's lease data to determine room status identifiers, thereby matching corresponding baseline parameter sets to different room statuses. Further, this embodiment compares the event feature set with a dynamic threshold set included in the baseline parameter set to calculate a deviation set, generating an anomaly score. Based on the anomaly score, it determines the handling levels, such as alerts, confirmations, and emergency interventions. In the occupancy status, a tiered process of "alert—confirmation—emergency intervention" triggers verification and handling by the resident and preset contacts. During emergency intervention, authorization is verified based on preset authorization chain rules, and an emergency electronic key is generated. Therefore, this embodiment achieves quantitative identification and tiered handling of room status anomalies without relying on frequent on-site inspections, improving the accuracy of room status anomaly identification and the timeliness of handling.

[0026] Step S100: Obtain event data of the target room within a preset observation time window. The event data includes at least access control data, resource metering data, and alarm data.

[0027] In some embodiments, the preset observation time window is a time range for making a single determination of the room status of the target room. The length and update method of the time range can be pre-configured. For example, the preset observation time window can be a fixed-length window (e.g., every 24 hours, every 48 hours, or every 7 days). By setting a preset observation time window, multiple types of behavioral and risk information of the target room can be aggregated within the preset observation time window to make room status anomaly determination based on the combined characteristics over a period of time, avoiding misjudgment caused by relying solely on a single instantaneous event.

[0028] In some embodiments, access control data is used to characterize access event records corresponding to a target room. This data can be generated by room access control systems in public areas, such as building access control or elevator access control. The access control data includes at least access time information and a key identifier associated with the target room. The access control data allows for the acquisition of the number of entries and exits and the time periods for each entry and exit within a preset observation window. This access control data can provide a basis for identifying anomalies such as prolonged periods of no entry or exit while the room is occupied, and for identifying anomalies such as unauthorized entry during non-permitted periods while the room is vacant.

[0029] In some embodiments, resource metering data is used to characterize the resource consumption of a target room. This data can be collected and uploaded by smart meters, water meters, and gas meters, and may include, but is not limited to: resource readings or reading increments (e.g., electricity increments in kWh, water increments in m³), ​​collection period information (e.g., collected every 15 minutes, hourly, or daily), and abnormal reading markers (e.g., offline, missing, or abrupt changes). The resource metering data can be used to reflect the intensity and continuity of living activities in the target room within a preset observation time window, thereby assisting in identifying abnormal silence or abnormal energy consumption when the room is occupied, and assisting in identifying abnormal usage behaviors such as continuous electricity and water consumption during periods of vacancy when the room is vacant.

[0030] In some embodiments, alarm data is used to characterize security alarm events and their risk levels in a target room. The alarm data may be generated by security devices associated with the target room. Exemplarily, the security devices include at least one of a smoke detector, a gas detector, a water leak detector, and a temperature and humidity sensor. The alarm data includes at least one of an alarm type, an alarm trigger time, and an alarm level.

[0031] Step S200: Generate an event feature set for the target room based on the event data.

[0032] In some embodiments, the event feature set is a "set of digital indicators", each of which describes a behavior or risk status of the target room within the observation time window.

[0033] For example, when the preset observation time window is the most recent 24 hours, the event feature set of the target room is represented as follows: ; in, This indicates the number of entries and exits within 24 hours. Indicates the number of times you enter and exit at night. Indicates a continuous period without passage. Indicates the increase in electricity consumption. Indicates the increase in water consumption. Indicates a continuous period of low consumption. Indicates the number of alarms. This indicates the highest alert level.

[0034] Step S300: Obtain the rental data of the target room and determine the room status identifier of the target room, wherein the room status identifier includes at least the occupied status and the vacant status.

[0035] Lease data is used to characterize whether a target room has a valid lease and its business status within the current preset observation time window. For example, lease data may include lease start time, lease expiry time, lease status (e.g., occupied, vacated) and time information related to occupancy / vacation.

[0036] The room status identifier is a marker indicating the occupancy status of the target room within the current preset observation time window, including at least the occupied and vacant statuses. Specifically, when the lease data indicates that the target room is currently rented, the room status identifier of the target room is determined to be occupied; when the lease data indicates that the target room does not have a valid lease or has been vacated, the room status identifier of the target room is determined to be vacant.

[0037] Step S400: Confirm the baseline parameter set of the target room based on the room status identifier, wherein the baseline parameter set includes at least a dynamic threshold set for the event feature set.

[0038] The baseline parameter set represents the range of values ​​that each event characteristic of the target room should typically fall into under the corresponding room status. Event characteristics include, for example, the number of entries and exits within 24 hours. Number of times entering and exiting at night Continuous no-passage duration Electricity consumption increment Increased water usage Continuous low consumption time Number of alarms Highest alarm level .

[0039] Reference Figure 2 In some embodiments, step S400 includes the following specific steps: S401: When the room status is identified as occupied and the number of occupied sample data for the target room is greater than or equal to a first threshold, the baseline parameter set of the target room is determined to be a personalized baseline parameter set, which is generated based on historical event data within the current lease period of the target room; wherein, the number of occupied sample data refers to the number of event data within the current lease period of the target room.

[0040] For example, the preset observation time window is 24 hours, and the first threshold is set to 14 (i.e., at least 14 days of occupancy data are required). If the target room R1 is currently occupied and the occupant has been there for 20 days during the current lease term, then the occupancy sample size N=20, satisfying N≥14. At this point, the baseline parameter set for the target room R1 is a personalized baseline parameter set, and a dynamic threshold set is generated based on historical event data from these 20 days. For example, based on the historical data from these 20 days, if the number of entries and exits in 24 hours mostly falls between 2 and 6, then the dynamic threshold range for "number of entries and exits in 24 hours" is set to 2, 6; if the increase in electricity consumption in 24 hours mostly falls between 1.0 and 4.5 kWh, then the dynamic threshold range for "increase in electricity consumption in 24 hours" is set to 1.0, 4.5; and if the alarm level is usually 0, then the upper limit of the dynamic threshold for "alarm level" is set to 0.

[0041] S402: When the room status is identified as occupied, and the number of occupied room samples is less than a first threshold and greater than a second threshold, a preliminary baseline parameter set is generated based on the number of occupied rooms, and a regular baseline parameter set is obtained. The regular baseline parameter set and the preliminary baseline parameter set are then fused based on dynamic weights to generate the baseline parameter set for the target room. The regular baseline parameter set is generated based on historical event data of rooms of the same type.

[0042] Specifically, generating the baseline parameter set for the target room based on the dynamic weighted fusion of the conventional baseline parameter set and the preliminary baseline parameter set includes: The fusion weight is calculated based on the number of in-housing samples N of the target room. ; Fusion weights for: ,in N1 is the first threshold, and N2 is the second threshold.

[0043] For example, the preset observation time window is 24 hours, the first threshold N1 is set to 14, and the second threshold N2 is set to 3. If the target room R2 is currently occupied and the occupant has been staying for 7 days during the current lease period, then the sample size N=7 satisfies N2<N<N1. At this point, a preliminary baseline parameter set is generated based on historical event data from these 7 days, and a regular baseline parameter set for similar rooms is obtained. Further, the fusion weights are calculated based on the sample size N. , .

[0044] In this example, the dynamic threshold range for "24-hour entry / exit count" corresponding to the standard baseline parameter set is: The dynamic threshold range for "24-hour entry and exit frequency" corresponding to the initial baseline parameter set is: Then the dynamic threshold range of the merged "24-hour entry and exit count" is: ; Similarly, the dynamic threshold range for the "24-hour electricity consumption increment" corresponding to the standard baseline parameter set is: The dynamic threshold range for the "24-hour electricity consumption increment" corresponding to the preliminary baseline parameter set is: Then the dynamic threshold range of the merged "24-hour electricity consumption increment" is: ; The dynamic threshold ranges for other event characteristics are similar. Therefore, when the sample size in the early stages of resident occupancy is insufficient to support a fully personalized baseline, a dynamic threshold set that gradually transitions to personalization as the sample size increases can be obtained by dynamically weighting and fusing the conventional baseline and the initial baseline. This improves the stability of early anomaly detection and reduces false alarms.

[0045] S403: When the room status is identified as occupied, and the number of occupied samples is less than or equal to the second threshold, the baseline parameter set of the target room is determined to be the regular baseline parameter set.

[0046] S404: When the room status is identified as vacant, the baseline parameter set of the target room is determined as the vacant baseline parameter set; the vacant baseline parameter set is generated based on historical vacant samples of the target room or similar vacant room samples.

[0047] For example, if the preset observation time window is 24 hours and the target room R3 is in an vacant state, then the corresponding event data during the historical vacancy period of the target room R3 is extracted as vacancy samples to generate a vacancy baseline parameter set; when the historical vacancy samples of the target room R3 are insufficient, the same type of vacant room samples can be obtained from vacant rooms of the same type as the target room R3 to generate a vacancy baseline parameter set.

[0048] Furthermore, in some embodiments, the idle baseline parameter set includes a dynamic threshold set for the event feature set. For example, the upper limit of the dynamic threshold for "24-hour entry and exit count" is set not higher than a preset minimum value, the upper limit of the dynamic threshold for "24-hour electricity consumption increment" is set not higher than a preset idle electricity consumption threshold, the upper limit of the dynamic threshold for "24-hour water consumption increment" is set not higher than a preset idle water consumption threshold, and the upper limit of the dynamic threshold for "alarm level" is set to 0 or not higher than a preset safety threshold.

[0049] Step S500: Calculate the deviation set based on the event feature set and the baseline parameter set, and generate an anomaly score based on the deviation set.

[0050] In some embodiments, the deviation set includes: active deviation and risk deviation, and step S500 includes: First, obtain the dynamic threshold ranges for access control data, resource metering data, and alarm data from the baseline parameter set.

[0051] Taking a room status marked as occupied and the number of occupied samples in the target room being greater than or equal to a first threshold as an example, the baseline parameter set for the target room is a personalized baseline parameter set. Within this baseline parameter set, the dynamic threshold range for access control data includes one or more of the following: the number of entries and exits within 24 hours. Dynamic threshold range, number of entries and exits at night The dynamic threshold range, the duration of continuous no passage. The dynamic threshold range for resource metering data includes one or more of the following: electricity consumption increment. The dynamic threshold range, water increment The dynamic threshold range, continuous low consumption duration The dynamic threshold range for alarm data includes one or more of the following: number of alarms. The dynamic threshold range, the highest alarm level The dynamic threshold range.

[0052] Then, when the corresponding data of the event feature set falls into the corresponding dynamic threshold range, the deviation of the event feature is determined to be zero, and the anomaly score is zero. When the data of the corresponding feature value in the event feature set falls within its corresponding dynamic threshold interval, it indicates that the feature value is consistent with the baseline expectation or is within the allowable fluctuation range, and does not constitute an abnormal deviation. Therefore, the data deviation of the event feature is determined to be 0. Further, in this embodiment, the anomaly score is generated by the deviation set; when all types of event features fall within their corresponding dynamic threshold intervals within the preset observation time window, the deviation of each data is 0, and thus the active deviation and risk deviation are both 0. Therefore, the anomaly score is determined to be 0 to indicate that no room status anomalies were detected in the target room within the observation time window.

[0053] Then, when the corresponding data of the event feature set does not fall into the corresponding dynamic threshold interval, a data deviation is generated based on the distance between the corresponding data and the dynamic threshold interval of the corresponding data, and the data deviation is normalized to limit the data deviation to a preset range.

[0054] Then, the active offset is determined based on the normalized data offsets of access control data and resource metering data.

[0055] In some embodiments, offsets are calculated for each event feature corresponding to access control data and for each event feature corresponding to resource metering data, and then active offsets are determined based on access control offsets and resource metering offsets.

[0056] For example, taking the case where the target room R1 is in a vacant state and the vacant sample size meets the first threshold condition, the baseline parameter set is a personalized baseline parameter set.

[0057] Obtain the dynamic threshold set corresponding to the event feature set from the baseline parameter set. For any event feature in the event feature set... Obtain its corresponding dynamic threshold range When the event characteristics Falling into the dynamic threshold range At that time, determine the feature deviation of the event feature. =0; when the event feature is 0 Not falling within the dynamic threshold range At that time, based on the event characteristics With the dynamic threshold range Distance determines feature deviation .when hour, ;when hour, .

[0058] After obtaining the characteristic deviation Then, the feature deviation is normalized to obtain the normalized feature deviation. This limits the deviations of different units to a preset range (e.g., between 0 and 1), thereby facilitating the fusion calculation between different features. Furthermore, the deviations of multiple normalized features corresponding to the same type of data are aggregated to obtain the category deviation.

[0059] For example, the dynamic threshold range corresponding to the access control data may include: a dynamic threshold range for the number of entries and exits within 24 hours, a dynamic threshold range for the number of entries and exits at night, and a dynamic threshold range for continuous periods without passage; then the corresponding normalized feature deviations are obtained respectively. , , And generate access control deviation based on preset aggregation rules. In some embodiments, the preset aggregation rule can be at least one of a weighted summation rule, a maximum value rule, or a Top-K average rule.

[0060] For example, when using a weighted summation rule: Where w1, w2, and w3 are preset weights and satisfy w1 + w2 + w3 = 1; when using the maximum value rule, .

[0061] Similarly, the dynamic threshold intervals corresponding to resource metering data can include: dynamic threshold intervals for electricity consumption increments, dynamic threshold intervals for water consumption increments, and dynamic threshold intervals for continuous low consumption durations; the corresponding normalized feature deviations are then obtained respectively. , , Based on the preset aggregation rules, resource metering deviation is generated. .

[0062] Obtaining access control deviation Deviation from resource measurement Then, the active offset can be determined based on the preset weights. The active offset satisfies: ;in, Preset weights.

[0063] Then, the risk offset is determined based on the data offset after the alarm data has been normalized.

[0064] The dynamic threshold ranges corresponding to alarm data may include: the dynamic threshold range for the number of alarms and the dynamic threshold range for the highest alarm level; the corresponding normalized feature deviations are then obtained respectively. , And generate risk offset based on the preset aggregation rules. ; In some embodiments, to enhance sensitivity to high-risk alarms, the risk offset is determined using a maximum value rule, i.e. .

[0065] Finally, the anomaly score is determined based on the active offset and the risk offset.

[0066] In some embodiments, determining the anomaly score based on the active offset and the risk offset includes: When the risk offset is greater than or equal to the risk threshold, the anomaly score is configured as the anomaly score threshold.

[0067] It should be noted that when the risk offset is greater than or equal to the risk threshold, it indicates that the target room has a security risk requiring priority response within the current observation time window. To avoid other factors in the comprehensive scoring (such as access control, electricity consumption, and other active indicators) from lowering the normal score, this application directly configures the abnormal score as the abnormal score threshold, thereby enabling the system to prioritize high-level handling (such as directly following the emergency intervention process), improving the timeliness and safety of the handling.

[0068] When the risk offset is less than the risk threshold, the active offset and the risk offset are weighted and calculated based on a preset weight to obtain the anomaly score; wherein the anomaly score satisfies: Wherein, S is the abnormal score. For the active offset, The risk offset is, and Preset weights.

[0069] Step S600: Determine the handling level based on the anomaly score. When the room status is identified as occupied, the handling level includes at least an alert level, a confirmation level, and an emergency intervention level.

[0070] Step S700: If the room status identifier indicates an occupied state: when the handling level is an alert level, send an alert message to the resident terminal; or, when the handling level is a confirmation level, initiate a confirmation request to the resident terminal, and if no confirmation feedback is received, initiate a confirmation request to a preset contact person; or, when the handling level is an emergency intervention level, verify the emergency entry authorization based on preset authorization chain rules, and generate an emergency electronic key when the verification passes.

[0071] In some embodiments, step S600 is used to determine the level of action for the resident status based on the anomaly score obtained in step S500, so as to achieve a graded response from mild to severe without disturbing the resident's normal life.

[0072] Furthermore, multiple scoring thresholds can be preset to complete the hierarchical mapping. For example, when the abnormal score is lower than the first scoring threshold, it is determined to be an alert level; when the abnormal score is greater than or equal to the first scoring threshold but lower than the second scoring threshold, it is determined to be a confirmation level; when the abnormal score is greater than or equal to the second scoring threshold, it is determined to be an emergency intervention level. The abnormal score threshold is greater than the second scoring threshold.

[0073] Through the above-mentioned classification method, low-risk anomalies are given priority to be notified to residents in a light manner, while high-risk anomalies can be quickly initiated into the emergency response process.

[0074] In some embodiments, step S700 is used to perform corresponding handling operations according to the handling level when the room status is identified as occupied, so as to form a closed-loop process of "reminder-confirmation-emergency intervention". Specifically, when the handling level is the reminder level, a reminder message is sent to the resident's terminal to prompt the resident to pay attention to possible abnormal situations and encourage them to actively report them; when the handling level is the confirmation level, a confirmation request is initiated to the resident's terminal to obtain the resident's confirmation feedback on the abnormal situation; and if the confirmation feedback is not obtained within a preset waiting time, a confirmation request is initiated to a preset contact person, wherein the preset contact person can be the emergency contact person reserved by the resident when signing the contract or moving in, or the backup contact person set by the operator, so as to improve the success rate of abnormal verification in the event that the resident is out of contact or unable to respond in a timely manner.

[0075] In some embodiments, when the response level is emergency intervention level, emergency entry authorization is verified based on preset authorization chain rules, and an emergency electronic key is generated upon successful verification to trigger emergency entry into the target room. The preset authorization chain rules are used to constrain the triggering conditions and authorization paths for emergency entry, preventing abuse of emergency entry and improving traceability.

[0076] For example, the preset authorization chain rule includes multi-party confirmation conditions, which include at least one of the following: confirmation is completed by two authorized persons with different roles; or confirmation is completed by one authorized person and the anomaly score reaches the anomaly score threshold. The different roles may include at least two of the following: operations management personnel, security personnel, duty officers, or other roles with authorization authority, thereby providing auditable authorization basis for emergency entry in the process.

[0077] In some embodiments, the emergency electronic key is used to issue a temporary access pass to the door lock bound to the target room, and is configured to carry door lock binding information, valid time window information, and maximum usage information to form a "limited access, limited time, limited number of uses" constraint on entry behavior. Specifically, the door lock binding information limits the emergency electronic key to be effective only for the door lock corresponding to the target room; the valid time window information limits the start and end time of the emergency electronic key's availability; and the maximum usage information limits the maximum number of times the emergency electronic key can be used. Further, the emergency electronic key is in an inactive state when generated, and switches from an inactive state to an active state after meeting the on-site verification conditions. The on-site verification conditions ensure that emergency entry occurs after the designated personnel arrive at the target room, and may, exemplarily, include at least one of the following: operational terminal check-in, location verification, access control point proximity verification, or on-site scanning verification, to prevent the emergency electronic key from being remotely used in advance or misused.

[0078] Through the aforementioned tiered handling and emergency electronic key mechanism under the occupancy status, reminders and confirmations can be prioritized to reduce the impact of false alarms when the anomaly score is low. When the anomaly score is high or there is a significant risk, the emergency intervention process can be quickly initiated. During the emergency entry phase, the controllability and traceability of entry authorization are enhanced through authorization chain verification and a constraint mechanism of "limited access, limited time, limited number of times + on-site activation," thereby improving the timeliness of handling and reducing operational safety risks.

[0079] In other embodiments, when the room status is identified as vacant, the handling level includes recording level, verification level, and emergency intervention level. Compared to the occupied state, vacant rooms typically experience operational visits such as showings, room turnovers, inspections, and maintenance. There is also a risk of unauthorized entry, unauthorized occupancy, or misuse of resources. Therefore, this application introduces a "permitted entry time window / unpermitted entry time window" determination logic in the vacant state to achieve classified recording and tiered handling of access control events.

[0080] Reference Figure 3 Specifically, methods for managing abnormal room status in long-term rental apartments also include: S800: If the room status is vacant: When the handling level is the recording level, obtain the allowed and unallowed entry time windows associated with the target room, mark access control events occurring within the preset observation time window and falling into the allowed entry time window set as operational access events, and generate operational trace records; when the preset observation time window and the allowed entry time window set do not overlap, mark access control events occurring within the preset observation time window as unallowed access events, and generate violation trace records; when the handling level is the verification level, initiate a verification request to the operation terminal, the verification request is used to trigger a preset verification operation, the preset verification operation includes at least one of on-site visit verification or freezing of temporary electronic keys associated with the target room; when the handling level is the emergency intervention level, verify the emergency entry authorization based on the preset authorization chain rules, and generate an emergency electronic key when the verification passes.

[0081] Specifically, in some embodiments, obtaining the permitted and prohibited entry time windows associated with the target room includes: Obtain the operational task information of the target room; wherein, the operational task information includes at least: task type and appointment time window corresponding to the task type, and the task type includes at least one of showing, room turnover, inspection and maintenance; The permitted entry time window is determined based on the reservation time window in the operation task information, and the time period outside the permitted entry time window is determined as the non-permitted entry time window; the permitted entry time window is the union of at least one reservation time window that meets the preset valid conditions.

[0082] In some embodiments, when the handling level is verification level, a verification request is initiated to the operation terminal. This verification request triggers a preset verification operation to perform rapid verification and risk mitigation when an anomaly is suspected but emergency intervention conditions are not yet met. For example, the preset verification operation includes at least one of the following: on-site verification to confirm whether the room has been entered without authorization, illegally occupied, or improperly used; or freezing the temporary electronic key associated with the target room to block potential further entry risks during the verification period, until the verification is completed and the key is restored or reissued.

[0083] In some embodiments, when the handling level is emergency intervention level, emergency entry authorization is verified based on preset authorization chain rules, and an emergency electronic key is generated upon successful verification to trigger emergency entry into the target room. The preset authorization chain rules can adopt the aforementioned multi-party confirmation mechanism and combine it with high-risk triggering conditions in vacant scenarios to ensure the compliance and traceability of emergency entry authorization; the emergency electronic key can also carry door lock binding information, effective time window information, and maximum number of uses information, and can be activated after meeting the on-site verification conditions, thereby forming a controllable constraint on the emergency entry process of vacant rooms.

[0084] Through the aforementioned hierarchical handling mechanism of "record-verify-emergency intervention" in the vacant state, and the distinction and recording of operational access and non-permitted access based on the permitted access time window, the embodiments of this application can achieve compliant recording and traceability when there is operational access to vacant rooms. At the same time, it can promptly detect and trigger verification or emergency intervention for entry during non-permitted periods, thereby reducing the risk of unauthorized entry, occupancy, or misuse of resources in vacant rooms.

[0085] In some embodiments, this application also discloses a long-term rental apartment room status anomaly control system, including: The acquisition module is used to acquire event data of the target room within a preset observation time window. The event data includes at least access control data, resource metering data, and alarm data. An event feature generation module is used to generate an event feature set for the target room based on the event data; The room status confirmation module is used to obtain the rental data of the target room and determine the room status identifier of the target room, which includes at least the occupied status and the vacant status. The baseline parameter set confirmation module is used to confirm the baseline parameter set of the target room based on the room status identifier. The baseline parameter set includes at least a dynamic threshold set for the event feature set. The scoring module is used to calculate a deviation set based on the event feature set and the baseline parameter set, and to generate an anomaly score based on the deviation set; The level confirmation module is used to determine the handling level based on the anomaly score; when the room status is identified as occupied, the handling level includes at least an alert level, a confirmation level, and an emergency intervention level. The execution module is configured to: if the room status identifier indicates an occupied state; when the handling level is an alert level, send an alert message to the resident terminal; or, when the level is a confirmation level, initiate a confirmation request to the resident terminal and, if no confirmation feedback is received, initiate a confirmation request to a preset contact person; or, when the handling level is an emergency intervention level, verify the emergency entry authorization based on preset authorization chain rules and generate an emergency electronic key when the verification passes.

[0086] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0087] The above provides a detailed description of a method and system for managing abnormal room status in long-term rental apartments, as provided in the embodiments of this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for managing abnormal room status in long-term rental apartments, characterized in that, include: Acquire event data of the target room within a preset observation time window, wherein the event data includes at least access control data, resource metering data, and alarm data; Based on the event data, an event feature set for the target room is generated; Obtain the rental data of the target room to determine the room status identifier of the target room, the room status identifier including at least the occupied status and the vacant status; The baseline parameter set of the target room is determined based on the room status identifier, and the baseline parameter set includes at least a dynamic threshold set for the event feature set; Based on the event feature set and the baseline parameter set, a deviation set is calculated, and an anomaly score is generated based on the deviation set; The handling level is determined based on the anomaly score. When the room status is identified as occupied, the handling level includes at least an alert level, a confirmation level, and an emergency intervention level. If the room status is identified as occupied: When the handling level is a reminder level, a reminder message is sent to the resident's terminal; or, When the handling level is a confirmation level, a confirmation request is sent to the resident's terminal, and if no confirmation feedback is received, a confirmation request is sent to a preset contact person; or... When the handling level is the emergency intervention level, the emergency entry authorization is verified based on the preset authorization chain rules, and an emergency electronic key is generated when the verification is successful.

2. The method for managing abnormal room status in long-term rental apartments according to claim 1, characterized in that, The step of determining the baseline parameter set of the target room based on the room status identifier, wherein the baseline parameter set includes at least a dynamic threshold set for the event feature set, includes: When the room status is identified as occupied and the number of occupied sample data for the target room is greater than or equal to a first threshold, the baseline parameter set of the target room is determined as a personalized baseline parameter set. The personalized baseline parameter set is generated based on historical event data within the current lease period of the target room. The number of occupied sample data refers to the number of event data within the current lease period of the target room. When the room status is identified as occupied, and the number of occupied room samples is less than a first threshold and greater than a second threshold, a preliminary baseline parameter set is generated based on the number of occupied rooms, and a regular baseline parameter set is obtained. The regular baseline parameter set and the preliminary baseline parameter set are then fused based on dynamic weights to generate the baseline parameter set for the target room. The regular baseline parameter set is generated based on historical event data of rooms of the same type. When the room status is identified as occupied, and the number of occupied samples is less than or equal to the second threshold, the baseline parameter set of the target room is determined to be the regular baseline parameter set. When the room status is identified as vacant, the baseline parameter set of the target room is determined as the vacant baseline parameter set; the vacant baseline parameter set is generated based on historical vacant samples of the target room or similar vacant room samples.

3. The method for managing abnormal room status in long-term rental apartments according to claim 2, characterized in that, The baseline parameter set for the target room is generated by dynamically weighting and fusing the conventional baseline parameter set and the preliminary baseline parameter set, including: The fusion weight is calculated based on the number of in-housing samples N of the target room. ; Among them, the fusion weight for: ,in N1 is the first threshold, and N2 is the second threshold.

4. The method for managing abnormal room status in long-term rental apartments according to claim 1, characterized in that, The deviation set includes: active deviation and risk deviation. The process of calculating the deviation set based on the event feature set and the baseline parameter set, and generating anomaly scores based on the deviation set, includes: Obtain the dynamic threshold ranges for access control data, resource metering data, and alarm data from the baseline parameter set; When the corresponding data of all the event feature sets fall within the corresponding dynamic threshold range, the deviation of the event feature is determined to be zero, and the anomaly score is zero; or, When the corresponding data of the event feature set does not fall into the corresponding dynamic threshold interval, a data deviation is generated based on the distance between the corresponding data and the dynamic threshold interval of the corresponding data, and the data deviation is normalized to limit the data deviation to a preset range. The active offset is determined based on the normalized data offset of access control data and resource metering data; The risk offset is determined based on the data offset after alarm data normalization. The anomaly score is determined based on the active offset and the risk offset.

5. The method for managing abnormal room status in long-term rental apartments according to claim 4, characterized in that, Determining the anomaly score based on the active offset and the risk offset includes: When the risk offset is greater than or equal to the risk threshold, the anomaly score is configured as the anomaly score threshold; When the risk offset is less than the risk threshold, the active offset and the risk offset are weighted and calculated based on a preset weight to obtain the anomaly score; Wherein, the anomaly score satisfies: Wherein, S is the abnormal score. For the active offset, The risk offset is, and Preset weights.

6. The method for managing abnormal room status in long-term rental apartments according to claim 1, characterized in that, When the room status is identified as vacant, the handling level includes recording level, verification level, and emergency intervention level. The long-term rental apartment room status anomaly control method also includes: If the room status indicator is vacant: When the handling level is the recording level, the allowed and unallowed entry time windows associated with the target room are obtained. Access control events that occur within the preset observation time window and fall into the set of allowed entry time windows are marked as operational access events, and operational trace records are generated. When the preset observation time window and the set of allowed entry time windows do not overlap, access control events that occur within the preset observation time window are marked as unallowed access events, and violation trace records are generated. When the handling level is the verification level, a verification request is initiated to the operation terminal. The verification request is used to trigger a preset verification operation. The preset verification operation includes at least one of on-site verification or freezing of the temporary electronic key associated with the target room. When the handling level is the emergency intervention level, the emergency entry authorization is verified based on the preset authorization chain rules, and an emergency electronic key is generated when the verification is successful.

7. The method for managing abnormal room status in long-term rental apartments according to claim 6, characterized in that, The emergency electronic key is configured to carry door lock binding information, effective time window information, and maximum number of uses information; the emergency electronic key is in an inactive state when it is generated, and switches from an inactive state to an active state after the on-site verification conditions are met.

8. The method for managing abnormal room status in long-term rental apartments according to claim 6, characterized in that, The preset authorization chain rules include multi-party confirmation conditions, which include at least one of the following: confirmation is completed by two authorizers with different roles; or confirmation is completed by one authorizer and the abnormal score reaches the abnormal score threshold.

9. The method for managing abnormal room status in long-term rental apartments according to claim 6, characterized in that, The process of obtaining the permitted and prohibited entry time windows associated with the target room includes: Obtain the operational task information of the target room; wherein, the operational task information includes at least: task type and appointment time window corresponding to the task type, and the task type includes at least one of showing, room turnover, inspection and maintenance; The permitted entry time window is determined based on the reservation time window in the operation task information, and the time period outside the permitted entry time window is determined as the non-permitted entry time window; the permitted entry time window is the union of at least one reservation time window that meets the preset valid conditions.

10. A long-term rental apartment room status anomaly control system, characterized in that, include: The acquisition module is used to acquire event data of the target room within a preset observation time window. The event data includes at least access control data, resource metering data, and alarm data. An event feature generation module is used to generate an event feature set for the target room based on the event data; The room status confirmation module is used to obtain the rental data of the target room and determine the room status identifier of the target room, which includes at least the occupied status and the vacant status; The baseline parameter set confirmation module is used to confirm the baseline parameter set of the target room based on the room status identifier. The baseline parameter set includes at least a dynamic threshold set for the event feature set. The scoring module is used to calculate a deviation set based on the event feature set and the baseline parameter set, and to generate an anomaly score based on the deviation set; The level confirmation module is used to determine the handling level based on the anomaly score; When the room status is identified as occupied, the handling level includes at least an alert level, a confirmation level, and an emergency intervention level; The execution module is configured to: if the room status identifier indicates an occupied state; when the handling level is an alert level, send an alert message to the resident terminal; or, when the level is a confirmation level, initiate a confirmation request to the resident terminal and, if no confirmation feedback is received, initiate a confirmation request to a preset contact person; or, when the handling level is an emergency intervention level, verify the emergency entry authorization based on preset authorization chain rules and generate an emergency electronic key when the verification passes.

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