A method and system for allocating energy consumption in a property

Abstract

This invention relates to a method and system for allocating energy consumption in a property, specifically in the field of energy consumption allocation technology. The method includes: obtaining user IDs and a user data table; retrieving corresponding user water and electricity data from the user data table based on the user ID; analyzing the user water and electricity data to determine the user's residential status, including both residential and non-residential status; when the residential status is residential, retrieving corresponding user information from the user data table based on the user ID; substituting the user information into a preset shared energy calculation model to calculate the allocated energy consumption; generating shared energy information based on the user ID, user information, and allocated energy consumption, and outputting the shared energy information based on the user information; when the residential status is non-residential, generating exemption information based on the user ID, and outputting the exemption information based on the user information. This invention improves the rationality of energy consumption allocation.

Description

Technical Field

[0001] This invention relates to the field of energy consumption allocation technology, and in particular to a method and system for allocating energy consumption in a property. Background Technology

[0002] In property management, the energy costs generated by public areas (such as corridor lighting, elevator operation, landscape pools, central air conditioning, etc.) need to be shared among all or some owners. A reasonable energy sharing mechanism is not only related to the efficiency of property operation cost recovery, but also directly affects the fairness and satisfaction among owners.

[0003] In related technologies, the common method of allocating property energy consumption is to allocate it proportionally according to the building area or number of households. Specifically, property management personnel first calculate the total energy consumption cost generated in the common areas of the community or building within a fixed common area period, and then calculate the average energy consumption cost that each household should bear.

[0004] Regarding the aforementioned technologies, the method of allocating energy costs proportionally based on building area or number of households does not take into account situations where some owners do not reside in the building for extended periods or use the common areas very infrequently. These owners still need to bear the same shared energy costs as the permanent residents, making the allocation of energy consumption unreasonable. Summary of the Invention

[0005] To improve the rationality of energy consumption allocation, this invention provides a method and system for allocating energy consumption in properties.

[0006] In a first aspect, the present invention provides a method for allocating energy consumption in a property, employing the following technical solution: A method for allocating energy consumption in a property includes: Step 1: Obtain user IDs and user data tables; Step 2: Find the corresponding user's water and electricity data from the user data table based on the user ID; Step 3: Analyze the user's water and electricity data to obtain the user's living situation, which includes living status and non-living status; Step 30: When the residence status is "resident", retrieve the corresponding user information from the user data table based on the user ID; Step 31: Substitute the user information into the preset common area calculation model to calculate the amortized energy consumption; Step 32: Generate shared information based on user ID, user information, and amortized energy consumption, and output the shared information based on user information; Step 33: When the residence status is non-residential, generate the exemption information based on the user ID, and output the exemption information based on the user information.

[0007] By adopting the above technical solution, the user's water and electricity data is first obtained to determine the actual living situation of the owner. If the owner is living in the property, the shared energy consumption is calculated and the shared information is output. If the owner is not living in the property for a long time, the shared energy consumption is exempted. This way, the owner who is not living in the property will no longer bear the shared energy consumption. Compared with the method of sharing according to area or number of households, this method fully considers the actual situation of the owner's use of the public area and can effectively improve the rationality of property energy consumption allocation.

[0008] Optionally, methods for analyzing user water and electricity data to obtain information about user living conditions include: Step 300: Extract the current water consumption and current electricity consumption from the user's water and electricity data; Step 301: If the current water consumption is greater than the preset minimum water consumption or the current electricity consumption is greater than the preset minimum electricity consumption, define the living situation as a living state. Step 302: If the water consumption in the current stage is less than the water consumption in the lowest stage and the electricity consumption in the current stage is less than the electricity consumption in the lowest stage, define the residential status as non-residential.

[0009] By adopting the above technical solution, the current water and electricity consumption can be compared with preset thresholds to quickly distinguish the approximate living conditions of homeowners. The judgment logic is simple, the data requirements are low, and it is easy to quickly complete the preliminary screening of living conditions.

[0010] Optionally, it also includes an optimization method for defining the living situation as the living state if the current water consumption is greater than the preset minimum water consumption or the current electricity consumption is greater than the preset minimum electricity consumption. This method includes: Step 3010: If the water consumption in the current stage is greater than the water consumption in the lowest stage or the electricity consumption in the current stage is greater than the electricity consumption in the lowest stage, obtain the corresponding energy consumption rate curve; Step 3011: Filter the energy consumption rate curves according to the preset minimum energy consumption rate to obtain the high energy consumption rate curve segment. Step 3012: Obtain the longest energy consumption rate curve segment and the longest energy consumption time based on the large energy consumption rate curve segment; Step 3013: When the maximum energy consumption time is greater than the preset normal energy consumption time, analyze the maximum energy consumption rate curve segment to obtain the real-time change rate of the curve. Step 3014: When the real-time rate of change of the curve is greater than the preset minimum rate of change threshold, the living situation is defined as the living status; Step 3015: When the real-time rate of change of the curve is less than the minimum rate of change threshold, the residential status is defined as non-residential status, and a preset energy consumption warning signal is output according to the user number.

[0011] By adopting the above technical solutions, for situations where some homeowners may not live in their homes for extended periods, but their homes still experience continuous energy consumption due to abnormal conditions such as electrical malfunctions or leaks, the accuracy of the assessment of occupancy status is further optimized, reducing misjudgments. At the same time, timely energy consumption anomaly alerts are sent to homeowners, helping them to promptly identify energy consumption faults in their homes and reduce unnecessary energy waste and property damage.

[0012] Optionally, if the current water consumption is less than the minimum water consumption and the current electricity consumption is less than the minimum electricity consumption, the optimization of defining the residential status as non-residential includes: Step 3020: If the water consumption in the current stage is less than the water consumption in the lowest stage and the electricity consumption in the current stage is less than the electricity consumption in the lowest stage, obtain the daily energy consumption time period and the total number of energy consumption days. Step 3021: Compare the daily energy consumption periods according to time to obtain the number of repeated energy consumption days; Step 3022: Calculate the percentage of repeated energy consumption based on the number of days of repeated energy consumption and the total number of days of energy consumption; Step 3023: When the proportion of repeated energy consumption is greater than the preset repeated proportion threshold, the living situation is defined as the living state; Step 3024: When the proportion of repeated energy consumption is less than the repetition proportion threshold, the residential status is defined as a non-residential status.

[0013] By adopting the above technical solution, in response to the situation where some homeowners habitually maintain a daily living state with extremely low water and electricity consumption, directly judging them as non-residential status by total amount threshold is easy to misjudge. By analyzing the time distribution pattern of daily energy consumption, the judgment result is further corrected, thereby improving the overall accuracy of residential status judgment.

[0014] Optional, also includes: Step 4: After outputting the shared area information, obtain feedback information; Step 5: Analyze the feedback information to extract confirmation features, which include the acceptance status and the questioning status; Step 6: When the confirmation feature is in the receiving state, output the common information and feedback information together; Step 7: When the feature is confirmed to be in a questionable state, analyze the feedback information to obtain the questioning information; Step 8: Analyze the questioning information based on user information to determine its reasonableness; Step 9: When the reasonableness is greater than the preset reasonable threshold, update the amortized energy consumption according to the question information to obtain the correct amortized energy consumption, and output the correct amortized energy consumption according to the user information; Step 10: When the reasonableness is less than the reasonable threshold, generate unreasonable information based on the user information for the questioning information, and output the unreasonable information based on the user information.

[0015] By adopting the above technical solution and adding a user feedback processing step, it is possible to respond promptly to user objections to the energy consumption allocation results, further revise the allocation results based on the actual usage of users, and balance the accuracy of the overall judgment with the flexibility of individual differences, thereby further improving the rationality of property energy consumption allocation.

[0016] Optionally, methods for analyzing the challenge information based on user information to determine its reasonableness include: Step 80: Extract the energy consumption of the challenge from the challenge information; Step 81: Based on the questioned energy consumption, search for the corresponding questioned energy consumption area from the preset shared area database; Step 82: Analyze the shared area database and user information to obtain the user activity area; Step 83: Calculate the reasonableness based on the questioned energy consumption area and user activity area.

[0017] By adopting the above technical solution and combining the matching degree between the questioned energy consumption area and the user's actual activity area to quantitatively analyze the rationality of the user's question, compared with direct manual review of user questions, the judgment process is more in line with the user's actual use of public areas, which can improve the accuracy of the rationality judgment.

[0018] Optionally, when the reasonableness exceeds a reasonable threshold, the optimized method of updating the amortized energy consumption based on the questioning information to obtain the correct amortized energy consumption, and outputting the correct amortized energy consumption based on user information, includes: Step 90: When the reasonableness exceeds the reasonable threshold, obtain the statistical period; Step 91: Select testing dates evenly from the statistical period; Step 92: Obtain the image of the questioned area based on the detection date and the questioned energy consumption area; Step 93: Analyze the image of the questioned area based on user information to obtain user characteristics, and define the detection date corresponding to the image of the questioned area with user characteristics as the user activity date; Step 94: Calculate the user activity frequency based on the detection date and the user activity date; Step 95: When the frequency of user activity exceeds the preset frequency threshold, generate unreasonable information based on the user information and output the unreasonable information based on the user information. Step 96: When the user activity frequency is less than the frequency threshold, update the amortized energy consumption according to the question information to obtain the correct amortized energy consumption, and output the correct amortized energy consumption according to the user information.

[0019] By adopting the above technical solution, and by retrieving public area surveillance images to identify the frequency of users actually entering and exiting the energy consumption area under question, it is possible to further verify whether the user's question is consistent with the actual situation based on objective activity data, avoid malicious and unreasonable questioning corrections, and at the same time ensure that users who actually meet the adjustment conditions receive accurate allocation results, thereby further improving the accuracy and fairness of energy consumption allocation results.

[0020] Optionally, methods for uniformly selecting detection dates from the statistical period include: Step 910: Extract user travel information from user information; Step 911: Divide the statistical period into travel period segments based on user travel information; Step 912: Randomly select one day from each travel cycle as the test date.

[0021] By adopting the above technical solution, combining the travel information filled in by the user to divide the statistical period, and then selecting the detection date from each period, the distribution of detection dates can be made to better match the user's actual travel patterns, thus making the final energy consumption allocation correction result more reliable.

[0022] Optionally, optimizations for retrieving corresponding user water and electricity data from the user data table based on user ID include: Step 20: Find the user's water and electricity consumption from the user data table based on the user ID; Step 21: When the user's water and electricity consumption falls within the preset reasonable water and electricity consumption range, the user's water and electricity consumption is defined as user water and electricity consumption data; Step 22: When a user's water and electricity consumption is outside the reasonable range, generate water and electricity anomaly information based on the user ID and the user's water and electricity consumption. Step 23: Output the water and electricity anomaly information according to the user information.

[0023] By adopting the above technical solutions, the water and electricity data itself is screened and verified. When the water and electricity data is abnormal and exceeds the reasonable range, the relevant owners are notified in a timely manner. This makes it easier for owners to check the faults of their water and electricity meters in a timely manner, and can also reduce misjudgments of living status caused by inaccurate water and electricity data, thereby further improving the accuracy of the basic data of the entire allocation method.

[0024] Secondly, the present invention provides a property energy consumption allocation system, which adopts the following technical solution: A property energy consumption sharing system, comprising: The acquisition module is used to retrieve user IDs and user data tables; A memory for storing a program for a property energy consumption allocation method as described above; The processor loads and executes programs from memory.

[0025] By adopting the above technical solution, the system can automatically execute the above property energy consumption allocation method, complete the entire process from judging the living status to outputting the allocation calculation results, without the need for property management personnel to manually check the living status of each household. While improving the rationality of energy consumption allocation, it can also reduce the workload of property management personnel and improve the overall efficiency of energy consumption allocation work.

[0026] In summary, the present invention has at least one of the following beneficial technical effects: 1. By intelligently judging the living status of homeowners through water and electricity data, distinguishing between residential and non-residential users, the allocation of shared energy consumption is more in line with actual usage, significantly improving the rationality of allocation; 2. An energy consumption rate curve analysis and feedback handling mechanism is introduced to effectively correct misjudgments of abnormal energy consumption and objectively verify user objections, ensuring the accuracy of the allocation results. Attached Figure Description

[0027] Figure 1 This is a flowchart of a property energy consumption allocation method according to an embodiment of this application; Figure 2 This is a flowchart of a method for determining whether to define a residential situation as a residential state in an embodiment of this application. Detailed Implementation

[0028] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments.

[0029] This invention discloses a method for allocating energy consumption in a property. (Refer to...) Figure 1 One method for allocating energy consumption in a property includes: Step 1: Obtain the user ID and user data table.

[0030] A user ID is a unique identifier used to distinguish different users. Each user within the property management area has a unique and non-repeating user ID, which is linked to the housing information under the user's name and stored in the user data table. The user ID is assigned based on the user's residential location. For example, the user residing on the 14th floor of Building A with apartment number 16 has the user ID A1416.

[0031] A user data table is a database that stores basic information about all users, such as a user's residential address, number of residents, water meter information, and electricity meter information. User data tables are created by staff recording, organizing, and entering this information into the tables.

[0032] Step 2: Find the corresponding user's water and electricity data from the user data table based on the user ID.

[0033] User water and electricity data refers to the water and electricity consumption records generated by users within the statistical period, including the total actual water and electricity consumption during the statistical period. User water and electricity data is obtained by querying and retrieving data from the user data table using the user's ID as the search term.

[0034] Step 3: Analyze the user's water and electricity data to obtain the user's living situation, which includes living status and non-living status.

[0035] User occupancy status refers to whether a user is currently residing in a property long-term within the statistical period. User occupancy status includes occupancy status and non-occupancy status. Occupancy status indicates that someone is living in the property regularly, while non-occupancy status indicates that the property is vacant or unoccupied. The method for obtaining user occupancy status is described in detail in steps 300 to 302.

[0036] Step 30: When the residence status is "residential", retrieve the corresponding user information from the user data table based on the user ID.

[0037] When the occupancy status is "residential," it means that someone is actually living in the house long-term, and the house should be included in the public energy consumption allocation for the current statistical period.

[0038] User information refers to a user's basic housing information, including house area, floor level, and number of permanent residents. User information is retrieved by searching the user data table using the user's ID as the search term.

[0039] Step 31: Substitute the user information into the preset common area calculation model to calculate the amortized energy consumption.

[0040] The shared area calculation model is a calculation model used to calculate the proportion and specific value of public area energy consumption that each user needs to bear within a statistical period. This model is pre-constructed based on the total public energy consumption within the property area, the total benefit area of ​​the community, and specific parameters such as the user's own house area. It can automatically calculate the energy consumption value that the user needs to share in the current statistical period by combining the various parameters in the input user information. The shared area calculation model is formed by the staff setting the calculation weights corresponding to each parameter in advance. After obtaining the user information, it can be directly substituted into the formula to complete the calculation of the energy consumption to be shared.

[0041] Deferred energy consumption refers to the amount of public energy consumption that users need to pay within the current statistical period, and the corresponding cost of this public energy consumption can also be calculated simultaneously. Deferred energy consumption is a specific numerical result obtained by inputting various parameters of user information into the public energy consumption calculation model and then having the model calculate and output the result.

[0042] Step 32: Generate shared information based on user ID, user information and energy consumption, and output the shared information based on user information.

[0043] Shared energy consumption information refers to information including user ID, user details, and a summary of energy consumption to be paid within the current statistical period. After the shared energy consumption information is generated, it is output to each user's corresponding terminal, such as a mobile phone, based on the user information. It can also be simultaneously uploaded to the property management mini-program and pushed to the user's account, allowing users to easily view the shared energy consumption fees they need to pay in a timely manner.

[0044] Step 33: When the residence status is non-residential, generate the exemption information based on the user ID, and output the exemption information based on the user information.

[0045] The "exemption from sharing" information informs users that their property is not included in the sharing of public energy consumption during the current statistical period and therefore does not need to pay any shared energy consumption fees. After the exemption information is generated, it will also be pushed to the user's corresponding terminal according to their information, so that the user is aware of the sharing results.

[0046] Methods for analyzing user water and electricity data to understand user living conditions include: Step 300: Extract the current water consumption and current electricity consumption from the user's water and electricity data.

[0047] Current water consumption refers to the total water consumption generated by the user within the current statistical period, and current electricity consumption refers to the total electricity consumption generated by the user within the current statistical period. Both current water consumption and current electricity consumption can be directly read from the user's water and electricity data, and both are pre-read and recorded in the user's water and electricity data by staff.

[0048] Step 301: If the current water consumption is greater than the preset minimum water consumption or the current electricity consumption is greater than the preset minimum electricity consumption, define the living situation as a living state.

[0049] Minimum water consumption refers to the minimum water consumption a user consumes during a normal residential period. This minimum water consumption is pre-set by staff based on local residents' general water consumption standards.

[0050] Minimum electricity consumption refers to the lowest electricity consumption a user consumes during a normal residential period. This minimum electricity consumption is pre-set by staff based on local residential electricity consumption standards.

[0051] If the current water consumption is greater than the preset minimum water consumption or the current electricity consumption is greater than the preset minimum electricity consumption, it means that the house has generated water or electricity consumption that meets the normal living standards within the statistical period. It can be determined that someone is actually living in the house, so the living situation is defined as living status, and the user needs to participate in this public energy consumption sharing.

[0052] Step 302: If the water consumption in the current stage is less than the water consumption in the lowest stage and the electricity consumption in the current stage is less than the electricity consumption in the lowest stage, define the residential status as non-residential.

[0053] If the current water consumption is less than the minimum water consumption and the current electricity consumption is less than the minimum electricity consumption, it means that the water and electricity consumption generated by the house during the statistical period have not reached the minimum standard for normal residence. It can be determined that no one is actually living in the house. Therefore, the residence status is defined as non-residential status, and the user does not need to participate in this public energy consumption sharing.

[0054] Reference Figure 2 It also includes an optimization method for defining the living situation as the living state if the current water consumption is greater than the preset minimum water consumption or the current electricity consumption is greater than the preset minimum electricity consumption. This method includes: Step 3010: If the water consumption in the current stage is greater than the water consumption in the lowest stage or the electricity consumption in the current stage is greater than the electricity consumption in the lowest stage, obtain the corresponding energy consumption rate curve.

[0055] An energy consumption rate curve is a curve showing the change in a user's energy consumption rate over time within a statistical period when their water or electricity consumption exceeds the minimum normal usage value. The curve is plotted with energy consumption rate on the ordinate and time on the abscissa. For example, if only the current water consumption exceeds the minimum water consumption, the energy consumption rate curve represents the water consumption rate on the ordinate and time on the abscissa. Similarly, if only the current electricity consumption exceeds the minimum electricity consumption, the energy consumption rate curve represents the electricity consumption rate on the ordinate and time on the abscissa. If both current water consumption and current electricity consumption exceed the minimum water and electricity consumption, both curves are obtained. The energy consumption rate curve is obtained by extracting water and electricity consumption data for different time points from the user's water and electricity data, calculating the water and electricity consumption rates for different time periods, and then fitting the calculated rates in chronological order to generate the corresponding energy consumption rate curve.

[0056] Step 3011: Select the high energy consumption rate curve segment by filtering the energy consumption rate curve according to the preset minimum energy consumption rate.

[0057] The minimum energy consumption rate refers to the lowest rate at which a user consumes energy when using household appliances or water normally. The minimum energy consumption rate is preset by staff based on the average minimum usage rate of water and electricity in a household's daily life. Under normal circumstances, the minimum energy consumption rate when using water is 0, while the minimum energy consumption rate when using electricity is the energy consumption of appliances such as refrigerators in standby mode.

[0058] The high energy consumption rate curve segment refers to a continuous curve segment in the energy consumption rate curve where the energy consumption rate is higher than the minimum energy consumption rate. The high energy consumption rate curve segment is obtained by comparing the energy consumption rate of each point on the energy consumption rate curve with the minimum energy consumption rate one by one, and retaining all continuous segments with rates greater than the minimum energy consumption rate.

[0059] Step 3012: Obtain the longest energy consumption rate curve segment and the longest energy consumption time based on the large energy consumption rate curve segment.

[0060] The longest energy consumption rate curve segment refers to the segment with the longest continuous duration among all high energy consumption rate curve segments. The longest energy consumption rate curve segment is obtained by calculating the continuous duration of each of the high energy consumption rate curve segments and comparing them; the segment with the longest duration is the longest energy consumption rate curve segment.

[0061] The longest energy consumption time refers to the total duration of the longest energy consumption rate curve segment, that is, the total time length from the start point to the end point of that segment. The longest energy consumption time is obtained by subtracting the start point from the end point of the longest energy consumption rate curve segment.

[0062] Step 3013: When the maximum energy consumption time is greater than the preset normal energy consumption time, analyze the maximum energy consumption rate curve segment to obtain the real-time change rate of the curve.

[0063] The real-time rate of change of the curve refers to the magnitude of the change in energy consumption rate between two adjacent time points on the large energy consumption rate curve segment, used to reflect the changing patterns of users' water and electricity consumption. The real-time rate of change of the curve is obtained by calculating the difference in energy consumption rate between adjacent time points and dividing it by the corresponding time interval, which can reflect the fluctuation of energy consumption rate over time.

[0064] Step 3014: When the real-time rate of change of the curve is greater than the preset minimum rate of change threshold, the living situation is defined as the living status.

[0065] The minimum rate of change threshold refers to the minimum average magnitude of energy consumption rate changes caused by the use of different appliances and different water usage scenarios at different times during a user's daily water and electricity consumption process. It is obtained by staff based on energy consumption data from a large number of normal residential users.

[0066] When the real-time rate of change of the curve is greater than the minimum rate of change threshold, it indicates that the energy consumption rate of the house conforms to the fluctuation pattern of water and electricity consumption of normal residents, rather than maintaining a constant energy consumption. Therefore, it can be further confirmed that someone is actually living in the house, and the living situation is defined as the living status.

[0067] Step 3015: When the real-time rate of change of the curve is less than the minimum rate of change threshold, the residential status is defined as non-residential status, and a preset energy consumption warning signal is output according to the user number.

[0068] An energy consumption warning signal is a signal that alerts a user to abnormal energy consumption in their home. The energy consumption warning signal is output to the user's terminal device based on the user's ID, such as through SMS push notifications.

[0069] When the real-time rate of change of the curve is less than the minimum rate of change threshold, it indicates that the energy consumption rate of the house is relatively high and has remained stable for a long time, with basically no fluctuations that conform to the daily living pattern. It may be that the user forgot to turn off the air conditioner or the faucet and was not living there. Therefore, the living situation is defined as non-living state, and an energy consumption warning signal is output according to the user number to remind the user of the abnormal water and electricity situation.

[0070] Among them, if the current water consumption is less than the minimum water consumption and the current electricity consumption is less than the minimum electricity consumption, the optimization of defining the residential situation as a non-residential state includes: Step 3020: If the water consumption in the current stage is less than the water consumption in the lowest stage and the electricity consumption in the current stage is less than the electricity consumption in the lowest stage, obtain the daily energy consumption time period and the total number of energy consumption days.

[0071] Daily energy consumption time period refers to the time period during which users consume energy each day within the statistical period. The daily energy consumption time period is obtained by looking up the user data table using the user ID.

[0072] Total energy consumption days refer to the total number of days a user has energy consumption records within the statistical period. Total energy consumption days are also obtained by looking up the user's ID in the user data table.

[0073] Step 3021: Compare the daily energy consumption periods according to time to obtain the number of repeated energy consumption days.

[0074] Repeated energy consumption days refer to the total number of days in which energy consumption occurs at the same time each day. Repeated energy consumption days are calculated by iterating through the daily energy consumption time periods for all dates within the statistical period and comparing the frequency of energy consumption occurring at the same time period.

[0075] Step 3022: Calculate the repeated energy consumption ratio based on the number of repeated energy consumption days and the total number of energy consumption days.

[0076] The energy reuse ratio is the ratio of repeated energy consumption days to the total number of energy consumption days. It is calculated by dividing the repeated energy consumption days by the total number of energy consumption days.

[0077] Step 3023: When the proportion of repeated energy consumption is greater than the preset repeated proportion threshold, the living situation is defined as the living state.

[0078] The repetition rate threshold refers to the minimum percentage of energy consumption generated within the same fixed time period to determine whether a user is a long-term resident. It is preset by staff based on the daily routines of normal residents. When the repetition rate exceeds the threshold, it indicates that the house generates energy consumption within the same fixed time period over a long period, consistent with the daily routines of permanent residents. Even if the total water and electricity consumption does not reach the minimum standard, it may be due to a small number of residents or frugal use of electricity. Therefore, it should be determined as a resident status, and the user should be required to participate in this public energy consumption sharing.

[0079] Step 3024: When the proportion of repeated energy consumption is less than the repetition proportion threshold, the residential status is defined as a non-residential status.

[0080] When the proportion of repeated energy consumption is less than the threshold for repeated energy consumption, it indicates that the time period during which the house generates energy consumption is not fixed and has not formed a pattern that conforms to the daily routine of permanent residents. The small amount of energy consumption is likely generated by temporary window opening for ventilation, temporary water discharge for maintenance, and other non-long-term residential scenarios. Therefore, the non-residential status is maintained, and the user does not need to participate in this public energy consumption sharing.

[0081] This also includes: Step 4: Output the shared area information and obtain feedback information.

[0082] Feedback information refers to the information users submit through their terminals after receiving the shared area information. This may include objections and questions about the current allocation results, or requests for corrections to the assessment of their living situation. Users can submit feedback information through the corresponding feedback portal, or they can directly contact property management staff for them to enter the information into the system.

[0083] Step 5: Analyze the feedback information to extract confirmation features, which include the acceptance status and the questioning status.

[0084] The confirmation characteristic refers to the user's feedback status after receiving information about shared or exempted expenses, including a "received" status and a "questioning" status. A "received" status indicates that the user has viewed the information and has no objection to the result, while a "questioning" status indicates that the user has doubts or objections to the result and does not accept the current assessment of the living situation and the allocation result.

[0085] Step 6: When the feature is confirmed to be in the receiving state, output the common information and feedback information together.

[0086] When the confirmation feature is in the receiving state, it means that the user has no objection to the result of this public energy consumption allocation. The confirmed public allocation information and the user's feedback are directly archived and output to the system.

[0087] Step 7: When the feature is confirmed to be in a questionable state, analyze the feedback information to obtain the questionable information.

[0088] Question information refers to the specific reasons why a user does not agree with the current cost-sharing results. Generally, it is because the user has objections to the determination of their own living situation. The user can fill in the explanation directly when providing feedback, or the system can extract and categorize it from common question options.

[0089] Step 8: Analyze the questioning information based on user information to determine its reasonableness.

[0090] Reasonableness refers to the criteria used to judge whether the information raised by the user is consistent with the actual situation. The methods for obtaining reasonableness are described in detail in steps 80 to 83.

[0091] Step 9: When the reasonableness is greater than the preset reasonable threshold, update the amortized energy consumption according to the question information to obtain the correct amortized energy consumption, and output the correct amortized energy consumption according to the user information.

[0092] A reasonable threshold is the minimum standard for judging whether a user's complaint is valid, and it is pre-set by property management staff according to the allocation rules. When the reasonableness exceeds the reasonable threshold, it indicates that the user's complaint is true and valid, the original residential status assessment was incorrect, and the assessment result needs to be corrected.

[0093] The correct apportionable energy consumption refers to the energy cost that the user actually needs to share. The correct apportionable energy consumption is obtained by the user filling in the query information. The shared information will list in detail the various energy consumptions that the user needs to share. The user can obtain the correct apportionable energy consumption by removing the shared energy consumptions that they believe they do not need to bear in the query information.

[0094] Step 10: When the reasonableness is less than the reasonable threshold, generate unreasonable information based on the user information for the questioning information, and output the unreasonable information based on the user information.

[0095] Unreasonable information refers to explanatory information that contradicts the user's claims. Unreasonable information will clearly indicate the reason for maintaining the original allocation result and will be displayed on the corresponding user's terminal.

[0096] Among these methods are: analyzing user information to determine the reasonableness of the challenged information. Step 80: Extract the energy consumption of questioning from the questioning information.

[0097] "Questionable energy consumption" refers to the energy consumption items that users disagree with in the current energy allocation results, specifically those corresponding to their share. Questionable energy consumption is extracted directly from user feedback by using natural language processing to extract keywords.

[0098] Step 81: Based on the questioned energy consumption, search for the corresponding questioned energy consumption area from the preset shared area database.

[0099] The shared area database is a database that stores information about the shared areas corresponding to different shared energy consumption items. Each shared energy consumption item is linked to a specific energy consumption area, allowing direct retrieval of the corresponding area information based on the energy consumption item. The shared area database is created by staff who input data based on the actual distribution of shared areas.

[0100] The questioned energy consumption area refers to the shared energy consumption area corresponding to the questioned energy consumption, that is, the public area where the shared energy consumption is actually generated. The corresponding area information can be directly retrieved through the shared area database.

[0101] Step 82: Analyze the shared area database and user information to obtain the user activity area.

[0102] The user activity area refers to the area that users pass through and actually use in the shared area's public facilities during their daily activities. The user activity area is derived through spatial correlation analysis based on information such as the user's address, combined with the location distribution of various shared facilities in the shared area database. For example, based on the location of the user's house and the shared area database, the public areas that the user inevitably passes through or uses during their daily activities can be deduced, including elevators, corridors, streetlights, etc.

[0103] Step 83: Calculate the reasonableness based on the questioned energy consumption area and user activity area.

[0104] The energy consumption area in question is compared with the user's activity area. If the energy consumption area in question does not belong to the user's activity area at all (for example, the user objects to the electricity cost of an elevator they have never used), the user's objection is deemed valid. If the energy consumption area in question overlaps with or is completely included in the user's activity area (for example, the user objects to the electricity cost of the elevator in their own building), the user's objection is deemed invalid.

[0105] Among them, the optimization method for updating the amortized energy consumption to obtain the correct amortized energy consumption based on the questioning information when the reasonableness exceeds the reasonable threshold, and outputting the correct amortized energy consumption based on user information, includes: Step 90: When the reasonableness is greater than the reasonable threshold, obtain the statistical period.

[0106] The statistical period refers to the duration of energy consumption statistics corresponding to this public energy consumption allocation. The statistical period is set in advance by property management staff based on the actual situation, and is generally one calendar month.

[0107] Step 91: Select testing dates evenly from the statistical period.

[0108] The detection date refers to the sampling date used to verify the user's residence status. The method for selecting the detection date is described in detail in steps 910 to 912.

[0109] Step 92: Obtain the image of the questioned area based on the detection date and the questioned energy consumption area.

[0110] Images of questionable areas refer to images captured by surveillance cameras installed within the questionable energy consumption area. These images are obtained by retrieving video recordings from the monitoring system for the corresponding detection date; simply extracting screenshots from different time periods within that date is sufficient.

[0111] Step 93: Analyze the image of the questioned area based on user information to obtain user characteristics, and define the detection date corresponding to the image of the questioned area with user characteristics as the user activity date.

[0112] User characteristics refer to the unique physical features of a user that distinguish them from other residents. User characteristics are obtained through facial features input by the user in advance.

[0113] User activity date refers to the date within the detection period when a corresponding user can be identified as appearing in the questioned energy consumption area. User features are extracted from the image of the questioned area using facial recognition and compared; if a match is found, the detection date is recorded as the user activity date.

[0114] Step 94: Calculate the user activity frequency based on the detection date and the user activity date.

[0115] User activity frequency refers to the ratio of the number of days with identified user activity to the total number of days detected. User activity frequency is obtained by dividing the number of active user days by the total number of selected detection days, and it reflects how frequently users actually enter and exit the shared area in question.

[0116] Step 95: When the user activity frequency is greater than the preset frequency threshold, generate unreasonable information based on the user information and output the unreasonable information based on the user information.

[0117] The frequency threshold refers to the minimum activity frequency standard for determining whether a user actually uses the shared area. The frequency threshold is set by the property management based on the actual usage requirements of the shared area. When a user's activity frequency exceeds the frequency threshold, it indicates that the user frequently enters and exits the shared area in question, and the user's objection does not match the actual usage. Therefore, an unreasonable message is generated to inform the user to maintain the original allocation result, and this message is output to the user's terminal.

[0118] Step 96: When the user activity frequency is less than the frequency threshold, update the amortized energy consumption according to the question information to obtain the correct amortized energy consumption, and output the correct amortized energy consumption according to the user information.

[0119] Correctly allocated energy consumption refers to the shared energy consumption that users should bear after the residential status assessment is corrected and recalculated to reflect the actual usage situation. During the calculation, the allocation ratio will be adjusted according to the user's actual residential status, and the energy consumption corresponding to the shared area that the user did not actually use will be deducted, so as to generate an allocation result that reflects the actual situation.

[0120] The methods for uniformly selecting detection dates from the statistical period include: Step 910: Extract user travel information from user information.

[0121] User travel information refers to the travel information of a user that can be collected within a statistical period. User travel information is generally obtained through the access control system within the property area. When users swipe their access cards or scan QR codes to enter or exit the area, corresponding travel records are left behind. By organizing these records, user travel information can be extracted.

[0122] Step 911: Divide the statistical period into travel period segments based on user travel information.

[0123] A travel cycle segment refers to each time period during which a user travels consecutively, such as every Monday to Friday. Travel cycle segments are determined by the intervals between the user's travel information entry and exit records. If there are no return records for more than a certain number of consecutive days, it is divided into an independent travel cycle segment; if there are return records, adjacent travel information is grouped into the same cycle segment.

[0124] Step 912: Randomly select one day from each travel cycle as the test date.

[0125] By randomly selecting one day from each travel cycle as the testing date, the selected testing date is ensured to cover different travel stages of users, avoiding the bias caused by the sampling being concentrated in a certain time period, and making the sampling test results more in line with the actual situation of users' use of the shared area.

[0126] The optimization of retrieving corresponding user water and electricity data from the user data table based on user ID includes: Step 20: Find the user's water and electricity consumption from the user data table based on the user ID.

[0127] User water and electricity consumption refers to the water and electricity consumption of a user within a statistical period, retrieved from the user data table. The user data table has pre-stored water and electricity data for each statistical period, categorized by user ID. The required user water and electricity data can be directly retrieved based on the corresponding user ID.

[0128] Step 21: When the user's water and electricity consumption falls within the preset reasonable water and electricity consumption range, the user's water and electricity consumption is defined as user water and electricity data.

[0129] The reasonable water and electricity range refers to the range of water and electricity consumption that a normal resident user would generate within a statistical period. This range is set by property management staff based on local average water and electricity consumption levels. When a user's water and electricity consumption falls within this range, it indicates that their consumption is consistent with that of a normal resident user, and this data can be directly used to assess the user's water and electricity usage in subsequent assessments of resident conditions.

[0130] Step 22: When a user's water and electricity consumption is outside the reasonable range, generate water and electricity anomaly information based on the user number and the user's water and electricity consumption.

[0131] Water and electricity anomaly information refers to the notification message indicating that a user's water and electricity consumption deviates from the normal range for resident users. This information is generated by binding the user's ID with the corresponding abnormal water and electricity consumption.

[0132] Step 23: Output the water and electricity anomaly information according to the user information.

[0133] The system outputs abnormal water and electricity usage information based on user information, thereby alerting users that there may be abnormalities in water and electricity consumption.

[0134] Based on the same inventive concept, embodiments of the present invention provide a property energy consumption allocation system.

[0135] A property energy consumption sharing system, comprising: The acquisition module is used to retrieve user IDs and user data tables; A memory used to store a program for a property energy consumption allocation method; The processor loads and executes programs from memory.

[0136] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0137] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principle of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A method for allocating energy consumption in a property, characterized in that, include: Step 1: Obtain user IDs and user data tables; Step 2: Find the corresponding user's water and electricity data from the user data table based on the user ID; Step 3: Analyze the user's water and electricity data to obtain the user's living situation, which includes living status and non-living status; Step 30: When the residence status is "resident", retrieve the corresponding user information from the user data table based on the user ID; Step 31: Substitute the user information into the preset common area calculation model to calculate the amortized energy consumption; Step 32: Generate shared information based on user ID, user information, and amortized energy consumption, and output the shared information based on user information; Step 33: When the residence status is non-residential, generate the exemption information based on the user ID, and output the exemption information based on the user information.

2. The property energy consumption allocation method according to claim 1, characterized in that, Methods for analyzing user water and electricity data to understand user living conditions include: Step 300: Extract the current water consumption and current electricity consumption from the user's water and electricity data; Step 301: If the current water consumption is greater than the preset minimum water consumption or the current electricity consumption is greater than the preset minimum electricity consumption, define the living situation as a living state. Step 302: If the water consumption in the current stage is less than the water consumption in the lowest stage and the electricity consumption in the current stage is less than the electricity consumption in the lowest stage, define the residential status as non-residential.

3. The property energy consumption allocation method according to claim 2, characterized in that, It also includes an optimization method for defining the living situation as the living state if the current water consumption is greater than the preset minimum water consumption or the current electricity consumption is greater than the preset minimum electricity consumption. This method includes: Step 3010: If the water consumption in the current stage is greater than the water consumption in the lowest stage or the electricity consumption in the current stage is greater than the electricity consumption in the lowest stage, obtain the corresponding energy consumption rate curve; Step 3011: Filter the energy consumption rate curves according to the preset minimum energy consumption rate to obtain the high energy consumption rate curve segment. Step 3012: Obtain the longest energy consumption rate curve segment and the longest energy consumption time based on the large energy consumption rate curve segment; Step 3013: When the maximum energy consumption time is greater than the preset normal energy consumption time, analyze the maximum energy consumption rate curve segment to obtain the real-time change rate of the curve. Step 3014: When the real-time rate of change of the curve is greater than the preset minimum rate of change threshold, the living situation is defined as the living status; Step 3015: When the real-time rate of change of the curve is less than the minimum rate of change threshold, the residential status is defined as non-residential status, and a preset energy consumption warning signal is output according to the user number.

4. The property energy consumption allocation method according to claim 2, characterized in that, If the current water consumption is less than the minimum water consumption and the current electricity consumption is less than the minimum electricity consumption, the optimization of defining the residential situation as a non-residential state includes: Step 3020: If the water consumption in the current stage is less than the water consumption in the lowest stage and the electricity consumption in the current stage is less than the electricity consumption in the lowest stage, obtain the daily energy consumption time period and the total number of energy consumption days. Step 3021: Compare the daily energy consumption periods according to time to obtain the number of repeated energy consumption days; Step 3022: Calculate the percentage of repeated energy consumption based on the number of days of repeated energy consumption and the total number of days of energy consumption; Step 3023: When the proportion of repeated energy consumption is greater than the preset repeated proportion threshold, the living situation is defined as the living state; Step 3024: When the proportion of repeated energy consumption is less than the repetition proportion threshold, the residential status is defined as a non-residential status.

5. The property energy consumption allocation method according to claim 1, characterized in that, Also includes: Step 4: After outputting the shared area information, obtain feedback information; Step 5: Analyze the feedback information to extract confirmation features, which include the acceptance status and the questioning status; Step 6: When the confirmation feature is in the receiving state, output the common information and feedback information together; Step 7: When the feature is confirmed to be in a questionable state, analyze the feedback information to obtain the questioning information; Step 8: Analyze the questioning information based on user information to determine its reasonableness; Step 9: When the reasonableness is greater than the preset reasonable threshold, update the amortized energy consumption according to the question information to obtain the correct amortized energy consumption, and output the correct amortized energy consumption according to the user information; Step 10: When the reasonableness is less than the reasonable threshold, generate unreasonable information based on the user information for the questioning information, and output the unreasonable information based on the user information.

6. The property energy consumption allocation method according to claim 5, characterized in that, Methods for analyzing questioning information based on user information to determine its reasonableness include: Step 80: Extract the energy consumption of the challenge from the challenge information; Step 81: Based on the questioned energy consumption, search for the corresponding questioned energy consumption area from the preset shared area database; Step 82: Analyze the shared area database and user information to obtain the user activity area; Step 83: Calculate the reasonableness based on the questioned energy consumption area and user activity area.

7. A property energy consumption allocation method according to claim 6, characterized in that, When the reasonableness exceeds the reasonable threshold, the optimization method of updating the amortized energy consumption based on the questioning information to obtain the correct amortized energy consumption, and outputting the correct amortized energy consumption based on user information, includes: Step 90: When the reasonableness exceeds the reasonable threshold, obtain the statistical period; Step 91: Select testing dates evenly from the statistical period; Step 92: Obtain the image of the questioned area based on the detection date and the questioned energy consumption area; Step 93: Analyze the image of the questioned area based on user information to obtain user characteristics, and define the detection date corresponding to the image of the questioned area with user characteristics as the user activity date; Step 94: Calculate the user activity frequency based on the detection date and the user activity date; Step 95: When the frequency of user activity exceeds the preset frequency threshold, generate unreasonable information based on the user information and output the unreasonable information based on the user information. Step 96: When the user activity frequency is less than the frequency threshold, update the amortized energy consumption according to the question information to obtain the correct amortized energy consumption, and output the correct amortized energy consumption according to the user information.

8. A property energy consumption allocation method according to claim 7, characterized in that, Methods for uniformly selecting detection dates from a statistical period include: Step 910: Extract user travel information from user information; Step 911: Divide the statistical period into travel period segments based on user travel information; Step 912: Randomly select one day from each travel cycle as the test date.

9. A method for allocating property energy consumption according to claim 1, characterized in that, The optimization of retrieving corresponding user water and electricity data from the user data table based on user ID includes: Step 20: Find the user's water and electricity consumption from the user data table based on the user ID; Step 21: When the user's water and electricity consumption falls within the preset reasonable water and electricity consumption range, the user's water and electricity consumption is defined as user water and electricity consumption data; Step 22: When a user's water and electricity consumption is outside the reasonable range, generate water and electricity anomaly information based on the user ID and the user's water and electricity consumption. Step 23: Output the water and electricity anomaly information according to the user information.

10. A property energy consumption allocation system, characterized in that, include: The acquisition module is used to retrieve user IDs and user data tables; A memory for storing a program of a property energy consumption allocation method as described in any one of claims 1 to 9; The processor loads and executes programs from memory.

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