A method and system for renting house based on edge computing

Abstract

The application relates to a kind of based on edge computing's house renting management method and system, is related to housing rental billing technical field, it includes obtaining current room number;Current room number corresponding day electricity data is collected, day electricity data includes single day cumulative electricity consumption and effective electricity duration;If single day cumulative electricity consumption exceeds house source electricity determination threshold, cumulative effective occupancy days are determined;Based on effective occupancy days, the last day is determined, and effective electricity duration is determined;Based on effective electricity duration, the number of hours of occupancy is determined, and the total cost of hourly occupancy is determined according to hourly standard rent;Based on effective occupancy days and the last day, the corrected effective occupancy days are determined;Based on the corrected effective occupancy days and single day standard rent, the total cost of occupancy days is determined;Based on the total cost of occupancy days and the total cost of hourly occupancy, the settlement bill of house renting is determined.The application has the effect of identifying empty period based on electricity data to realize empty free billing, and taking into account the interests of both parties.

Description

Technical Field

[0001] This invention relates to the field of housing rental billing technology, and in particular to a rental management method and system based on edge computing. Background Technology

[0002] The rental industry typically uses a fixed monthly or daily billing model for rent calculation. This billing method does not distinguish the actual length of time the tenant stays in the house. Even if the tenant is away for a long time and the house is vacant, the full daily rent still needs to be paid. The billing rules are inflexible, and unnecessary rent loss can easily occur when the tenant is away and the house is vacant. This leads to frequent billing disputes between the tenant and the landlord, which is a common drawback of the traditional rental system.

[0003] To optimize billing methods, existing technologies have led to the development of a billing system that uses electricity consumption data to determine the actual occupancy status of tenants and calculates rent based on the actual length of stay. By collecting room electricity consumption parameters, it can determine whether a house is occupied. When tenants are away on business trips or the house is vacant and has no effective electricity consumption, no rent will be charged for that day, effectively avoiding the problem of vacancy billing and balancing the rights and interests of both tenants and landlords.

[0004] Regarding the aforementioned technologies, existing rental settlement methods rely solely on the actual electricity usage time measured by the electricity meter to calculate the final day's fee for the lease term. This method cannot identify malicious arbitrage behavior by tenants who use energy storage appliances such as air conditioners and water heaters to store energy for short periods, and then remain in the sealed house for extended periods after the power is cut off. The actual measured electricity usage time is significantly shorter than the actual stay time, resulting in errors in rent calculation. Summary of the Invention

[0005] To prevent tenants from using energy storage appliances to store cold or heat and then being stranded due to power outages, which could reduce the accuracy of rent calculations, this invention provides a rental management method and system based on edge computing.

[0006] In a first aspect, the present invention provides a rental management method based on edge computing, which adopts the following technical solution:

[0007] A rental management method based on edge computing includes:

[0008] In response to the acquired signal, obtain the current room number;

[0009] Collect the daily electricity consumption data corresponding to the current room number. The daily electricity consumption data includes the cumulative daily electricity consumption and the effective electricity consumption duration.

[0010] If the cumulative daily electricity consumption exceeds the preset threshold for determining the electricity consumption of the property, the cumulative number of valid occupancy days will be counted.

[0011] The last day is determined based on the number of valid stay days, and the valid electricity usage time is determined based on the last day;

[0012] The number of hours of stay is determined based on the effective electricity usage time, and the total hourly stay cost is determined according to the preset hourly standard rent.

[0013] The revised number of valid stay days is determined based on the number of valid stay days and the last day.

[0014] The total cost for the number of nights is determined based on the adjusted valid number of nights and the preset standard daily rent.

[0015] The rental settlement bill is determined based on the total cost of the number of nights and the total cost of the number of hours of stay.

[0016] By adopting the above technical solution, edge computing is used to complete the collection and preliminary processing of electricity consumption data locally on the property. This reduces the bandwidth consumption of data transmission while improving the efficiency of billing. The system first determines whether the room is in a valid occupancy status by accumulating the daily electricity consumption. Only the number of days actually occupied is counted, and days that are vacant and have no valid electricity consumption are not included in the billing days, thus achieving rent exemption for vacant days. Then, the actual occupancy time is identified separately for the last day of the lease, and the hourly fee for the last day is separated from the daily fee for the remaining days. Compared with the overall daily billing method, the rent can be calculated more accurately and the settlement error can be reduced.

[0017] Optionally, methods for determining the effective electricity usage duration based on the last day include:

[0018] The target electricity consumption data is determined based on the last day;

[0019] Find the historical electricity usage data corresponding to the current room number;

[0020] When historical electricity consumption data exists, similar historical electricity consumption data are determined based on the historical electricity consumption data and the target electricity consumption data;

[0021] Determine the number of days with similar electricity consumption based on historical similar electricity consumption data;

[0022] The proportion of similar electricity consumption days is determined based on the number of similar electricity consumption days and the number of valid occupancy days.

[0023] When the proportion of similar electricity consumption days exceeds the preset reliable proportion threshold, the target electricity consumption duration is determined based on the target electricity consumption data, and the target electricity consumption duration is output as the effective electricity consumption duration.

[0024] When there is no similar historical electricity consumption data, the effective electricity consumption time is determined according to the preset standard check-out time.

[0025] By adopting the above technical solution and combining the historical electricity consumption patterns of the room, we can determine whether the current last-day electricity consumption data is reliable. When the proportion of similar historical electricity consumption data is high enough, it indicates that the current target electricity consumption duration is consistent with the room's regular usage patterns. Therefore, we can directly use the target electricity consumption duration to calculate the cost, thereby improving the relevance of the billing results.

[0026] Optionally, it also includes a method for determining the effective electricity usage duration when the proportion of similar electricity usage days does not exceed the reliable proportion threshold, the method including:

[0027] Find the target weather temperature corresponding to the target electricity consumption data;

[0028] Find the historical weather temperatures corresponding to similar historical electricity consumption data;

[0029] The temperature difference is determined based on the target weather temperature and historical weather temperatures;

[0030] When the temperature difference falls within the preset appropriate temperature difference range, the target power consumption time will be output as the effective power consumption time.

[0031] When the temperature difference does not fall within the appropriate temperature difference range, the effective electricity usage time shall be determined according to the standard check-out time.

[0032] By adopting the above technical solution, when the proportion of similar electricity consumption patterns is insufficient, the weather temperature dimension is introduced to further verify the rationality of the target electricity consumption duration. If the temperature difference is small, it means that the current energy storage demand is close to the historical situation. At this time, directly using the target electricity consumption duration will not produce a large error. If the temperature difference is too large, it means that the energy storage demand is significantly different from the historical situation. It is not possible to directly refer to similar electricity consumption data. Subsequent steps need to be taken to determine whether the tenant has engaged in malicious arbitrage, thereby reducing the impact of malicious arbitrage on the accuracy of billing.

[0033] Optionally, methods for determining the effective electricity usage time based on the standard check-out time include:

[0034] The energy storage temperature type is determined based on the target weather temperature, and the energy storage temperature type is divided into cold energy storage temperature type and hot energy storage temperature type;

[0035] When the energy storage temperature type is cold energy storage temperature type, historical weather temperatures are searched based on the target weather temperature to determine the first similar weather temperature;

[0036] Obtain the historical target temperature of the cold storage equipment corresponding to the first similar weather temperature;

[0037] Obtain the target temperature of the current cold storage equipment corresponding to the target weather temperature;

[0038] If the current target temperature of the cold energy storage device is greater than the historical target temperature of the cold energy storage device, the target power consumption time will be output as the effective power consumption time.

[0039] If the current target temperature of the cold storage equipment is lower than the historical target temperature of the cold storage equipment, the effective electricity usage time shall be determined according to the standard return period.

[0040] By adopting the above technical solution, for the cold energy storage scenario, by comparing the current target temperature of the cold energy storage equipment with the historical records under the same weather temperature, if the current target temperature is higher, it means that the tenant did not lower the temperature in advance for additional cold storage, and there is no malicious arbitrage behavior. Therefore, the billing can be directly based on the collected target electricity usage time. If the current target temperature is lower, it means that there is a possibility that the air conditioner was turned on in advance to lower the room temperature for energy storage and then the power was cut off. In this case, the effective electricity usage time can be directly calculated according to the standard check-out time, which can avoid the billing error caused by malicious arbitrage.

[0041] Optional, also includes:

[0042] When the energy storage temperature type is thermal energy storage temperature type, historical weather temperatures are searched based on the target weather temperature to determine the second similar weather temperature;

[0043] Obtain the historical target temperature of thermal energy storage equipment corresponding to the second similar weather temperature;

[0044] If the current target temperature of the thermal energy storage device is lower than the historical target temperature of the thermal energy storage device, the target power consumption time will be output as the effective power consumption time.

[0045] If the current target temperature of the thermal energy storage equipment is greater than the historical target temperature of the thermal energy storage equipment, the effective electricity usage time shall be determined according to the standard return period.

[0046] By adopting the above technical solution, for the thermal energy storage scenario, by comparing the current target temperature of the thermal energy storage equipment with the historical records under the same weather temperature, if the current target temperature is lower, it means that the tenant has not raised the temperature in advance for additional heat storage, and there is no malicious arbitrage behavior. Therefore, the billing can be directly based on the collected target electricity usage time. If the current target temperature is higher, it means that there is a possibility that the thermal energy storage equipment was turned on in advance to raise the room temperature for energy storage and then the power was cut off. In this case, the effective electricity usage time can be directly calculated according to the standard check-out time, which can avoid the billing error caused by malicious arbitrage.

[0047] Optional, also includes:

[0048] When no first similar weather temperature exists, the effective first sample weather temperature is determined based on the target weather temperature and historical weather temperatures.

[0049] Determine the effective historical target temperature for cold energy storage equipment based on the first sample of weather temperature.

[0050] If the current target temperature of the cold energy storage device is greater than the effective historical target temperature of the cold energy storage device, perform a sample judgment operation;

[0051] If the current target temperature of the cold storage equipment is lower than the effective historical target temperature of the cold storage equipment, the effective electricity usage time shall be determined according to the standard check-out time.

[0052] When no second similar weather temperature exists, the effective second sample weather temperature is determined based on the target weather temperature and historical weather temperatures.

[0053] Determine the target temperature for effective historical thermal energy storage equipment based on the second sample of weather temperatures;

[0054] If the current target temperature of the thermal energy storage device is lower than the effective historical target temperature of the thermal energy storage device, perform a sample judgment operation;

[0055] If the current target temperature of the thermal energy storage equipment is greater than the effective historical target temperature of the thermal energy storage equipment, the effective electricity usage time shall be determined according to the standard check-out time.

[0056] By adopting the above technical solution, when there is not enough matching historical data of the same temperature in the room for comparison, a sample weather temperature close to the target temperature is selected for secondary verification. It is still possible to determine whether the target temperature of the current energy storage device is abnormal based on the existing historical data, ensuring that the determination of effective power consumption time will not be interrupted due to the lack of matching similar weather temperatures, and improving the integrity and adaptability of the billing determination process.

[0057] Optionally, methods for performing sample judgment operations include:

[0058] If the current target temperature of the cold energy storage device is greater than the target temperature of the effective historical cold energy storage device, the first sample count is accumulated, and the target temperature of the effective historical cold energy storage device is re-determined to perform the cold energy storage device comparison operation.

[0059] If the first sample count is 1 and there is no target temperature for the current cold storage equipment, perform a comparison operation with tenants in the same building.

[0060] If the first sample count is greater than 1, the target power consumption time will be output as the effective power consumption time.

[0061] If the current target temperature of the thermal energy storage device is lower than the target temperature of the effective historical thermal energy storage device, the second sample count is accumulated, and the target temperature of the effective historical thermal energy storage device is re-determined to perform the thermal energy storage device comparison operation.

[0062] If the second sample count is 1 and there is no target temperature for the current thermal energy storage device, perform a comparison operation between tenants in the same building.

[0063] If the number of the second sample is greater than 1, the target power consumption time will be output as the effective power consumption time.

[0064] If the above technical solution is adopted and the conditions are still met after multiple sample comparisons, it indicates that the target temperature of the current energy storage equipment is likely to be reasonable. At this time, the target power consumption time can be used directly. Only when a single sample meets the abnormal conditions, the data of the tenant in the same building can be called for further verification to ensure the accuracy of the judgment.

[0065] Optionally, methods for performing in-building tenant comparison operations include:

[0066] Search global historical data and determine global similar weather temperatures based on the target weather temperature;

[0067] Determine the global average temperature of thermal energy storage equipment and the global average temperature of cold energy storage equipment based on globally similar weather temperatures;

[0068] When a global average temperature of the thermal energy storage device exists, the target temperature of the thermal energy storage device is determined based on the current target temperature of the thermal energy storage device and the preset fluctuation range.

[0069] If the target temperature of the thermal energy storage device is less than the global average temperature of the thermal energy storage device, the target power consumption time will be output as the effective power consumption time.

[0070] If the target temperature of the thermal energy storage device is greater than the global average temperature of the thermal energy storage device, the effective electricity usage time shall be determined according to the standard check-out time.

[0071] By adopting the above technical solution, for short-term tenants, there is not enough sample size. Therefore, global historical data of other tenants in the same building are introduced for comparison and verification to keep the billing process running normally. When there are enough samples of the same weather temperature in the same building, the global average temperature of the energy storage equipment can reflect the normal target temperature setting under that weather temperature. When the verified target temperature is lower than the average level of the same building, it indicates that there is no abnormal situation of additional heat storage, and the target electricity usage time can be used directly for billing. Otherwise, there is a possibility of malicious heat storage arbitrage. Determining the effective duration according to the standard check-out time can ensure accurate billing.

[0072] Optional, also includes:

[0073] When a global average temperature of the cold energy storage device exists, the target temperature of the cold energy storage device is determined based on the current target temperature and fluctuation range of the cold energy storage device.

[0074] If the target temperature of the cold energy storage device is greater than the global average temperature of the cold energy storage device, the target power consumption time will be output as the effective power consumption time.

[0075] If the target temperature of the cold storage equipment is lower than the global average temperature of the cold storage equipment, the effective electricity usage time shall be determined according to the standard check-out time.

[0076] By adopting the above technical solution, verification is completed for the cold storage scenario by combining global data of tenants in the same building. When the current target temperature of the cold storage is higher than the global average temperature of the cold storage in the same building, it means that the tenant has not lowered the temperature for cold storage and there is no malicious arbitrage. The collected target electricity usage time can be used directly for settlement. If the current target temperature of the cold storage is lower than the global average temperature, it means that there is a possibility of additional cold storage. The effective electricity usage time can be calculated according to the standard check-out time, which further ensures the accuracy of the rental settlement for short-term tenants and avoids rent arbitrage errors.

[0077] Secondly, the present invention provides a rental management system based on edge computing, which adopts the following technical solution:

[0078] A rental management system based on edge computing includes:

[0079] The acquisition module is used to obtain the current room number;

[0080] A memory for storing a program for a rental management method based on edge computing as described above;

[0081] The processor loads and executes programs from memory.

[0082] By adopting the above technical solutions, electricity data processing and rent calculation can be completed locally by relying on edge nodes, reducing the data transmission pressure on the cloud. At the same time, through multi-dimensional verification, the behavior of tenants maliciously arbitrage using energy storage appliances can be identified, and accurate rental settlement bills can be automatically generated to protect the rights and interests of both landlords and tenants.

[0083] In summary, the present invention has at least one of the following beneficial technical effects:

[0084] 1. The actual occupancy status of a room is determined by the electricity consumption threshold of the property. When a house is vacant or the electricity consumption is below standard, it is not counted as a valid billing day. Tenants do not need to pay rent for vacant rooms when they are away on business trips. This eliminates the drawbacks of traditional fixed daily billing and effectively reduces rental billing disputes.

[0085] 2. By comparing historical electricity consumption in the room, matching ambient temperature, verifying the set temperature of cold and hot energy storage devices, statistically analyzing sample frequency, and using shared data from the same building as a backup, the system identifies tenants who use energy storage devices such as air conditioners and water heaters to store cold or hot energy and then leave after power outages, or who deliberately reduce the actual measured electricity consumption time to pay less rent. The system automatically corrects the billing time on the last day of the lease term to prevent landlords from losing rent. Attached Figure Description

[0086] Figure 1 This is a flowchart of a rental management method based on edge computing in an embodiment of this application. Detailed Implementation

[0087] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments.

[0088] This invention discloses a rental management method based on edge computing. (Refer to...) Figure 1 A rental management method based on edge computing includes:

[0089] Step 1: In response to the acquisition signal, obtain the current room number.

[0090] The acquisition signal refers to the periodically triggered data acquisition command signal from the edge electricity data acquisition terminal (which integrates a smart meter acquisition module and an edge computing module) deployed in each rental unit. This signal includes hardware pulse signals and timed polling trigger signals, serving as the trigger source for initiating electricity data acquisition. The smart meter acquisition module is the hardware acquisition unit within the edge electricity data acquisition terminal, physically connected to the smart meter in the room, responsible for reading raw electricity data such as meter pulse signals and instantaneous power. The edge computing module refers to the embedded main control chip and local storage unit integrated within the same terminal. It receives the raw data uploaded by the acquisition module and performs data storage, logical judgment, and cost calculation locally on the device. The edge electricity data acquisition terminal has a built-in timer that autonomously generates timed acquisition signals according to the acquisition cycle. The acquisition cycle refers to the data sampling interval pre-configured locally on the edge electricity data acquisition terminal, used to control the smart meter acquisition module to periodically read meter data. It can be configured as 10 minutes, 30 minutes, or 1 hour, and the configuration parameters are stored in the local memory of the edge computing module.

[0091] The current room number refers to the room code pre-entered on the edge terminal. One room number corresponds to one code, which is used to distinguish different rental rooms. For example, room 302 in building A is coded A0302, which serves as a data binding identifier.

[0092] Step 2: Collect the daily electricity consumption data corresponding to the current room number. The daily electricity consumption data includes the cumulative daily electricity consumption and the effective electricity consumption duration.

[0093] The daily electricity usage data refers to all the electricity usage statistics output by the smart meter for the corresponding room within a calendar day, that is, from 00:00 to 24:00. Specifically, it consists of two indicators: the cumulative daily electricity consumption and the effective electricity usage time, which are used to determine the tenant's occupancy status.

[0094] Daily cumulative electricity consumption refers to the total electrical energy consumed by all electrical equipment in the room during a natural day, measured in kilowatt-hours (kWh), and is obtained by real-time collection of meter pulse data from the edge power consumption acquisition terminal.

[0095] Effective power consumption duration refers to the cumulative power-on time within a natural day when the instantaneous power consumption of a room exceeds its static idle power consumption. Invalid durations corresponding to fixed standby power consumption from devices such as meters and low-voltage routers are excluded. This data is generated by the edge computing module based on time-of-use power data. The time-of-use power data consists of time-series data of the instantaneous power collected by the smart meter's data acquisition module according to the collection cycle. The edge computing module compares each piece of time-of-use power data with power consumption thresholds and accumulates compliant periods to generate the effective power consumption duration. The collection time refers to the specific time point recorded each time the smart meter's data acquisition module initiates a power consumption sampling action. This time point is generated by the clock built into the edge power consumption acquisition terminal and stored locally.

[0096] Instantaneous power refers to the real-time power consumption of all electrical appliances in the rental room at the instant mentioned above. The unit of measurement is watts. This value is calculated by the metering element inside the smart meter and then read and output by the smart meter's data acquisition module to determine whether the room is generating effective occupancy electricity at that moment.

[0097] Step 3: If the cumulative daily electricity consumption exceeds the preset threshold for determining the electricity consumption of the property, the cumulative number of valid occupancy days will be counted.

[0098] The electricity consumption threshold for a property refers to the minimum daily electricity consumption threshold pre-entered into the edge computing module, which serves as the standard for classifying properties as vacant or occupied.

[0099] Valid occupancy days refer to the total number of natural days that are determined to be actual occupancy days by the tenant within a single rental period after verification of the property's electricity consumption threshold.

[0100] When the cumulative daily electricity consumption exceeds the threshold for determining the electricity consumption of a property, it indicates that the tenant has actually checked in that day, and the number of valid check-in days is incremented by one.

[0101] Step 4: Determine the last day based on the number of valid stay days, and determine the valid electricity usage duration based on the last day.

[0102] The last day refers to the settlement date at the end of the lease term as stipulated in the lease contract.

[0103] Effective electricity usage duration refers to the duration used to calculate the hourly rental fee after historical electricity usage data and historical weather temperature corrections are applied to the last day of the rental period. The specific process will be introduced in subsequent steps 40 to 4134.

[0104] Step 5: Determine the number of hours of stay based on the effective electricity usage time, and determine the total hourly stay cost according to the preset hourly standard rent.

[0105] The number of hours of stay refers to the billable occupancy time determined at the end of the lease term. Under normal circumstances, it is taken from the actual effective electricity usage time. In case of abnormal arbitrage, it is obtained after correction based on historical electricity usage data and historical weather temperature.

[0106] In this context, "normal situation" refers to situations where the tenant's electricity usage pattern on the last day of the lease term is similar to the historical electricity usage pattern of the room, the proportion of similar electricity usage days reaches the reliable proportion threshold, there is no deliberate modification of the electricity usage pattern, and the effective electricity usage time obtained from the actual electricity meter reading is directly adopted as the occupancy hours.

[0107] Abnormal arbitrage refers to situations where tenants deliberately adjust their electricity usage strategy on the last day of the lease term. For example, they may turn on the air conditioner briefly and then turn off all appliances, or stay in a closed room, relying on the pre-existing cold to achieve a long stay. In this case, with all appliances turned off and electricity consumption at 0, the system may mistakenly judge that the tenant has left. It is necessary to re-determine and correct the number of hours of stay by combining historical electricity usage data and historical weather temperature.

[0108] The hourly standard rental fee refers to the unit hourly rental fee calculated by retrieving the pre-stored daily standard rental fee from the edge computing module. The conversion rule is to divide the daily standard rental fee by twenty-four, and the conversion calculation is completed locally at the edge power consumption collection terminal.

[0109] The total hourly occupancy cost refers to the rent cost calculated separately on the last day of the lease based on the hourly rate. It is calculated by multiplying the number of occupancy hours by the standard hourly rate.

[0110] Step 6: Determine the revised number of valid stay days based on the number of valid stay days and the last day.

[0111] The corrected valid occupancy days refer to the remaining days after deducting the last day of the rental period from the original total valid occupancy days. Since the last day is no longer charged on a full-day basis but on an hourly basis, the last day needs to be deducted from the full-day billing statistics. The calculation formula is: Corrected valid occupancy days equals the original valid occupancy days minus one.

[0112] Step 7: Determine the total cost for the number of nights based on the corrected valid stay days and the preset daily standard rent.

[0113] The standard daily rent refers to the full rent for a single natural day as stipulated in the rental contract.

[0114] The total cost per stay refers to the total rent for all eligible stays within the lease period, excluding the last day of the lease term. It is calculated by multiplying the number of valid stays by the standard daily rent.

[0115] Step 8: Determine the rental settlement bill based on the total cost for the number of nights and the total cost for the number of hours.

[0116] A rental settlement bill is an electronic settlement document automatically generated by the edge computing module after summarizing the total cost for the number of nights stayed, the total cost for each hour of stay, the daily electricity consumption details for the entire period, and the daily check-in records. The raw data of the rental settlement bill is stored locally in the edge electricity consumption collection terminal. After the terminal is connected to the network, it is automatically synchronized and sent to the corresponding management terminals of the landlord and tenant for reconciliation and record keeping by both parties.

[0117] The methods for determining the effective electricity usage time based on the last day include:

[0118] Step 40: Determine the target electricity consumption data based on the last day.

[0119] The target electricity consumption data refers to the full amount of time-of-use electricity consumption data collected by the smart meter acquisition module according to the acquisition cycle and stored locally by the edge computing module on the last day of the lease term.

[0120] Step 41: Find the historical electricity usage data corresponding to the current room number.

[0121] Historical electricity consumption data refers to the complete electricity consumption records of the same room for each past rental day, which are archived and stored locally by the edge computing module. Specifically, it includes the cumulative daily electricity consumption, hourly power data, and ambient temperature for the corresponding date. The ambient temperature for the day refers to the average indoor temperature for that day, collected by the temperature sensor deployed on the edge electricity consumption acquisition terminal.

[0122] Step 410: When historical electricity consumption data exists, determine similar historical electricity consumption data based on the historical electricity consumption data and the target electricity consumption data.

[0123] Historical similar electricity consumption data refers to the historical daily electricity consumption records that the edge computing module selects from historical electricity consumption data, and finds those whose electricity load change patterns are similar to the target electricity consumption data characteristics at the end of the lease term. The selection and calculation are completed locally on the edge terminal.

[0124] Energy storage electrical equipment refers to electrical equipment that can store cold or heat when powered on, and can maintain a comfortable room temperature for a relatively long time after the power is off, relying on its own stored energy. Tenants can turn on the equipment for a short time to store energy and then turn it off to leave it in the house. Rental scenarios mainly include equipment such as air conditioners, storage water heaters, and electric heaters.

[0125] The pattern of electricity load variation refers to the temporal fluctuations of instantaneous power and the distribution characteristics of appliance start-up and shutdown at different times during a natural day.

[0126] If, during the last day of the rental period, the tenant sets the air conditioner to 16 degrees Celsius for nearly an hour, the historical electricity usage records of the same operation can be matched with the historical electricity usage data based on the electricity load change pattern of the corresponding device. These records are the historical similar electricity usage data.

[0127] Step 411: Determine the number of similar electricity consumption days based on historical similar electricity consumption data.

[0128] Similar electricity consumption days refer to the total number of historical days that meet the similar electricity consumption characteristics selected from historical electricity consumption data. For each historical electricity consumption record that meets the requirements, the number of similar electricity consumption days is incremented by one.

[0129] Step 412: Determine the percentage of similar electricity consumption days based on similar electricity consumption days and valid occupancy days.

[0130] The percentage of similar electricity usage days refers to the percentage of similar electricity usage days that meet the temperature matching conditions out of the total number of valid occupancy days. The calculation formula is to divide the number of similar electricity usage days that meet the temperature matching requirements by the total number of valid occupancy days, and then multiply by 100% to obtain the final percentage value.

[0131] Step 413: When the proportion of similar electricity consumption days exceeds the preset reliable proportion threshold, determine the target electricity consumption duration based on the target electricity consumption data, and output the target electricity consumption duration as the effective electricity consumption duration.

[0132] The reliability ratio threshold is a threshold pre-set in the edge computing module to determine whether a tenant is deliberately engaging in energy storage arbitrage. Its determination method is as follows:

[0133] The target electricity usage duration refers to the actual effective electricity usage duration measured on the last day of the lease term, obtained from the statistical analysis of target electricity usage data.

[0134] When the proportion of similar electricity usage days exceeds the reliable proportion threshold, it indicates that the electricity usage pattern at the end of the current lease term matches the electricity usage pattern of similar operations in the past for this room with a high degree of consistency, confirming that the tenant is simply using the equipment according to personal habits and there is no deliberate energy storage arbitrage behavior.

[0135] Step 420: When there is no similar historical electricity consumption data, determine the effective electricity consumption time according to the preset standard check-out time.

[0136] The standard move-out period refers to the maximum time limit stipulated in the housing lease contract for the tenant to vacate the house and complete the handover procedures in advance. It serves as a minimum calculation period when no reference data is available.

[0137] When there is no historical similar electricity consumption data, it means that the property lacks a reference for past rental electricity consumption samples, and the authenticity of the electricity consumption on the day cannot be verified by historical electricity consumption patterns. Therefore, in order to avoid tenants' malicious energy storage arbitrage behavior, the final settlement fee is calculated directly according to the standard check-out time.

[0138] This also includes a method for determining the effective electricity usage duration when the proportion of similar electricity usage days does not exceed the reliable proportion threshold. This method includes:

[0139] Step 4130: Find the target weather temperature corresponding to the target electricity consumption data.

[0140] The target weather temperature refers to the average indoor temperature of the last day of the rental period, which is collected by the temperature sensor built into the edge power consumption acquisition terminal. It is used to compare with the ambient temperature of the same day in similar historical power consumption records to eliminate matching interference caused by differences in power consumption patterns under different temperature conditions.

[0141] Step 4131: Find the historical weather temperature corresponding to similar historical electricity consumption data.

[0142] Historical weather temperature refers to the outdoor ambient temperature of the corresponding date that is bound to and synchronously archived with similar historical electricity usage data. The outdoor ambient temperature can be used to verify the tenant's habits of using the corresponding equipment. For example, when the outdoor temperature is 34 degrees, it can be determined that the tenant's habit of turning on the air conditioner in the historical electricity usage data corresponds to the air conditioner temperature of 26 degrees. However, on the last day of the lease, when the outdoor temperature is 34 degrees, the tenant turns on the air conditioner at 16 degrees, indicating that the tenant is deliberately storing energy to cool down.

[0143] Step 4132: Determine the temperature difference based on the target weather temperature and historical weather temperatures.

[0144] Temperature difference refers to the difference (calculated by taking the absolute value) between the target weather temperature and the corresponding historical weather temperature for each historical similar electricity consumption data point, used to determine whether the temperature environment of two electricity consumption operations is similar.

[0145] Step 4133: When the temperature difference falls within the preset appropriate temperature difference range, the target power consumption time is output as the effective power consumption time.

[0146] The appropriate temperature difference range refers to the maximum allowable range within which the temperature environment of two electrical operations can differ. In this embodiment, it is set to no more than 3 degrees Celsius.

[0147] When the temperature difference falls within a suitable temperature difference range, it indicates that the tenant's electricity usage habits are similar under the same temperature environment, and the tenant is not deliberately using energy storage to achieve arbitrage. Therefore, the target electricity usage time is directly used as the final calculated effective electricity usage time.

[0148] Step 4134: When the temperature difference does not fall within the appropriate temperature difference range, determine the effective electricity usage time according to the standard check-out time.

[0149] When the temperature difference does not fall within the appropriate temperature difference range, it indicates that there is a significant difference between the tenant's electricity usage strategy and normal electricity usage habits under the same temperature environment. Steps 4200 to 42014 need to be executed to determine whether the tenant is deliberately storing energy for arbitrage. If the tenant is deliberately storing energy for arbitrage, the effective electricity usage time is determined according to the standard check-out time.

[0150] The methods for determining the effective electricity usage time based on the standard check-out time include:

[0151] Step 4200: Determine the energy storage temperature type based on the target weather temperature.

[0152] Energy storage temperature types are divided into cold energy storage temperature types and hot energy storage temperature types.

[0153] Energy storage temperature type refers to a classification identifier for tenant energy storage behavior based on the ambient temperature of the day. It distinguishes between two arbitrage scenarios: tenants storing cold energy or storing heat energy using electrical appliances. This is automatically determined by the edge computing module in conjunction with the target weather temperature. Specifically, a corresponding cold energy storage temperature threshold and a hot energy storage temperature threshold are set. When the target weather temperature is greater than the cold energy storage temperature threshold or less than the hot energy storage temperature threshold, the corresponding energy storage temperature type is determined. The cold energy storage temperature threshold refers to the minimum outdoor temperature required for the tenant to achieve cold energy storage. The hot energy storage temperature threshold refers to the maximum outdoor temperature required for the tenant to achieve heat storage. The determination of the above two threshold values ​​can be flexibly set according to the normal climate of the location of the house and the tenant's habits of using air conditioning and heating equipment. For example, in southern cities of my country, the critical value of cold energy storage temperature can be set at 28 degrees Celsius. When the target weather temperature is higher than 28 degrees Celsius, it can be determined as a cold energy storage temperature type. In northern my country, during the heating season, the critical value of thermal energy storage temperature can be set at 10 degrees Celsius. When the target weather temperature is lower than 10 degrees Celsius, it can be determined as a thermal energy storage temperature type.

[0154] Cold storage temperature type refers to the classification of scenarios where the outdoor ambient temperature is high and tenants rely on cooling energy storage appliances such as air conditioners to store cold energy.

[0155] Thermal energy storage temperature type refers to the classification of scenarios where the outdoor ambient temperature is low and tenants rely on heating energy storage appliances such as electric heaters and storage water heaters to store heat.

[0156] Step 42010: When the energy storage temperature type is cold energy storage temperature type, search for historical weather temperatures based on the target weather temperature to determine the first similar weather temperature.

[0157] The first similar weather temperature refers to the outdoor high temperature environment temperature that is archived in history and whose difference from the current target weather temperature falls within a suitable temperature difference range.

[0158] When the energy storage temperature type is cold energy storage temperature type, it means that the ambient temperature is relatively high on that day. Tenants have the arbitrage opportunity to store cold energy by setting the air conditioner to a low temperature, turn it on for a short time and then turn it off to stay in the house. It is necessary to compare the set temperature of the equipment to identify abnormal operation.

[0159] Step 42011: Obtain the historical target temperature of the cold storage equipment corresponding to the first similar weather temperature.

[0160] The target temperature of historical cold storage equipment refers to the daily set temperature of air conditioners and other cold storage appliances during the tenant's normal tenancy period on the historical date corresponding to the first similar weather temperature. The data is stored locally along with the historical electricity consumption data.

[0161] Step 42012: Obtain the target temperature of the current cold storage equipment corresponding to the target weather temperature.

[0162] The target temperature for the current cold storage equipment refers to the actual operating temperature set by the tenant on the last day of the rental period. It is obtained by the edge power consumption acquisition terminal in combination with power consumption analysis. All energy storage devices in the rooms are IoT smart devices, and the set temperature can be directly read and stored by the edge module through the device communication interface.

[0163] Step 42013: If the current target temperature of the cold energy storage device is greater than the historical target temperature of the cold energy storage device, output the target power consumption duration as the effective power consumption duration.

[0164] If the current target temperature of the cold storage equipment is higher than the historical target temperature of the cold storage equipment, it means that the renter's equipment setting temperature is higher than the usual temperature in the past, and there is no deliberate low-temperature storage behavior. The target electricity usage time can be directly used as the effective electricity usage time for billing.

[0165] Step 42014: If the current target temperature of the cold storage equipment is lower than the historical target temperature of the cold storage equipment, determine the effective electricity usage time according to the standard check-out time.

[0166] If the current target temperature of the cold storage equipment is lower than the historical target temperature of the cold storage equipment, it means that the tenant's equipment setting temperature is lower than the usual temperature in the past, indicating that there is a deliberate act of storing cold at a low temperature. Therefore, the effective electricity usage time should be determined according to the standard check-out time.

[0167] This also includes:

[0168] Step 42020: When the energy storage temperature type is thermal energy storage temperature type, search for historical weather temperatures based on the target weather temperature to determine the second similar weather temperature.

[0169] The second similar weather temperature refers to the outdoor low temperature environment temperature that is archived in history and whose difference from the current target weather temperature falls within a suitable temperature difference range.

[0170] When the energy storage temperature type is thermal energy storage temperature type, it means that the ambient temperature is low on that day. Tenants can store heat through heating equipment such as electric heaters and water heaters. At this time, the outdoor temperature is suitable for arbitrage by turning off the equipment and retaining heat. It is necessary to compare the set temperature of the equipment to determine whether it is abnormal.

[0171] Step 42021: Obtain the historical target temperature of the thermal energy storage device corresponding to the second similar weather temperature.

[0172] The target temperature of historical thermal energy storage equipment refers to the operating temperature that tenants normally set when using heating-type energy storage appliances on historical rental days corresponding to the second most similar weather temperature. It is stored in conjunction with historical electricity consumption data.

[0173] Step 42022: If the current target temperature of the thermal energy storage device is lower than the historical target temperature of the thermal energy storage device, output the target power consumption duration as the effective power consumption duration.

[0174] If the current target temperature of the thermal energy storage equipment is lower than the historical target temperature of the thermal energy storage equipment, it means that the tenant's equipment setting temperature is lower than the usual heating temperature in the past, there is no deliberate high-temperature thermal energy storage arbitrage behavior, and the actual measured electricity usage time is valid.

[0175] Step 42023: If the current target temperature of the thermal energy storage device is greater than the historical target temperature of the thermal energy storage device, determine the effective electricity usage time according to the standard check-out time.

[0176] If the current target temperature of the thermal energy storage equipment is greater than the historical target temperature of the thermal energy storage equipment, it indicates that the tenant deliberately increased the temperature of the heating equipment to hoard heat, and there is an arbitrage behavior of staying in the property after the power is cut off and paying less rent. The standard check-out time should be used to calculate the billing time.

[0177] This also includes:

[0178] Step 42030: When there is no first similar weather temperature, determine the effective first sample weather temperature based on the target weather temperature and historical weather temperatures.

[0179] The effective first sample weather temperature refers to the temperature sample selected from all historical weather temperatures when there is no matching first similar weather temperature. The temperature sample with the smallest temperature difference from the target weather temperature is selected as the alternative reference temperature for cold energy storage scenarios.

[0180] When there is no first similar weather temperature, it means that there is no historical reference temperature within the appropriate temperature difference range, and it is impossible to directly match the data of normal use during the same period. Instead, the nearest historical temperature on the low-temperature side is used as the comparison benchmark for subsequent judgment processes.

[0181] Step 42031: Determine the target temperature for effective historical cold storage equipment based on the weather temperature of the first sample.

[0182] The effective historical target temperature for cold storage devices refers to the average set temperature of the tenants' normal use of cold storage appliances in the historical rental records corresponding to the effective first sample weather temperature.

[0183] Step 42032: If the current target temperature of the cold energy storage device is greater than the effective historical target temperature of the cold energy storage device, perform the sample judgment operation.

[0184] Sample judgment operation refers to the statistical analysis of the number of comparisons of equipment temperature control, and the final result is judged based on the number of times the data is analyzed. This is used to avoid arbitrage by misjudging single data fluctuations.

[0185] If the current target temperature of the cold storage equipment is greater than the effective historical target temperature of the cold storage equipment, it means that the tenant's set temperature of the refrigeration equipment is higher than the historical normal temperature, and there is no behavior of lowering the refrigeration temperature to hoard cold energy for arbitrage. In this case, it is necessary to obtain the number of samples where the current target temperature of the cold storage equipment is less than the effective historical target temperature of the cold storage equipment in order to determine whether to accept the measured target electricity consumption time for settlement.

[0186] Step 42033: If the current target temperature of the cold storage equipment is lower than the effective historical target temperature of the cold storage equipment, the effective electricity usage time shall be determined according to the standard check-out time.

[0187] If the current target temperature of the cold storage equipment is lower than the effective historical target temperature of the cold storage equipment, it indicates that the tenant has lowered the cooling temperature to hoard cold energy, and there is an arbitrage behavior of short-term cold storage and long-term stay after shutdown to pay less rent. The standard check-out time is used to calculate the billing time.

[0188] Step 42034: When there is no second similar weather temperature, determine the effective second sample weather temperature based on the target weather temperature and historical weather temperatures.

[0189] The effective second sample weather temperature refers to the temperature sample selected from all historical weather temperatures when there is no matching second similar weather temperature. The temperature sample with the smallest temperature difference from the target weather temperature is selected as the alternative reference temperature for the thermal energy storage scenario.

[0190] When there is no second similar weather temperature, it means that there is no historical reference temperature that falls within the appropriate temperature difference range, and there is a lack of directly matching normal usage samples. Therefore, the nearest historical temperature on the high-temperature side is used as the comparison benchmark.

[0191] Step 42035: Determine the target temperature for effective historical thermal energy storage equipment based on the weather temperature of the second sample.

[0192] The effective historical thermal energy storage device target temperature refers to the average set temperature of heating energy storage appliances normally used by tenants in the historical rental records corresponding to the effective second sample weather temperature.

[0193] Step 42036: If the current target temperature of the thermal energy storage device is lower than the effective historical target temperature of the thermal energy storage device, perform the sample judgment operation.

[0194] If the current target temperature of the thermal energy storage device is lower than the effective historical target temperature of the thermal energy storage device, it means that the tenant's heating equipment setting temperature is lower than the historical normal temperature and that heat is not deliberately stored. In this case, it is necessary to obtain the number of samples where the current target temperature of the thermal energy storage device is lower than the effective historical target temperature of the thermal energy storage device in order to determine whether to accept the measured target electricity consumption time for settlement.

[0195] Step 42037: If the current target temperature of the thermal energy storage device is greater than the effective historical target temperature of the thermal energy storage device, the effective electricity usage time shall be determined according to the standard check-out time.

[0196] If the current target temperature of the thermal energy storage device is greater than the effective historical target temperature of the thermal energy storage device, it indicates that the tenant deliberately increased the heating temperature to accumulate heat, and there is an arbitrage situation where the tenant remains in the house after the power is cut off after storing energy. The actual measured time should be discarded and the calculation should be based on the standard check-out time.

[0197] The methods for performing sample judgment operations include:

[0198] Step 420380: If the current target temperature of the cold energy storage device is greater than the target temperature of the effective historical cold energy storage device, accumulate the first sample count and redetermine the target temperature of the effective historical cold energy storage device to perform the cold energy storage device comparison operation.

[0199] The first sample count refers to the statistical frequency of times, in multiple verifications, that the current target temperature of the cold energy storage device is greater than the effective historical target temperature of the cold energy storage device.

[0200] The comparison operation of cold energy storage equipment refers to sequentially comparing the target temperatures of all historical cold energy storage equipment corresponding to the valid first sample weather temperature, continuously accumulating the number of first samples that meet the judgment conditions, and updating the accumulated number of times after each comparison is completed.

[0201] If the current target temperature of the cold energy storage device is greater than the effective historical target temperature of the cold energy storage device, it means that the current single comparison meets the no-arbitrage judgment, and the result of this comparison will be included in the cumulative statistics.

[0202] Step 420381: If the first sample count is 1 and there is no target temperature for the current cold storage equipment, perform a comparison operation between tenants in the same building.

[0203] Because each time the first sample count is updated, the target temperature of the current cold storage device needs to be redefined. Therefore, if the first sample count is 1 and there is no target temperature for the current cold storage device, it means that the rental record only has a single valid sample and lacks sufficient reference data in the same environment. In this case, it is also necessary to use the temperature settings of other tenants in the same building for further judgment to ensure that the judgment result is not biased due to insufficient samples.

[0204] Step 420382: If the first sample count is greater than 1, output the target power consumption duration as the effective power consumption duration.

[0205] If the first sample count is greater than 1, it means that multiple comparisons meet the no-arbitrage criteria and there is no random bias in the single comparison result. Therefore, it is confirmed that the tenant has no intentional cold storage arbitrage behavior, and the actual measured target electricity usage time is accepted for billing.

[0206] Step 420383: If the current target temperature of the thermal energy storage device is lower than the target temperature of the effective historical thermal energy storage device, accumulate the second sample count and redetermine the target temperature of the effective historical thermal energy storage device to perform the thermal energy storage device comparison operation.

[0207] The second sample count refers to the statistical frequency of times, in multiple verifications, that the current target temperature of the thermal energy storage device is lower than the effective historical target temperature of the thermal energy storage device.

[0208] The thermal energy storage equipment comparison operation refers to sequentially comparing the target temperatures of all historical thermal energy storage equipment corresponding to the valid second sample weather temperature, continuously accumulating the number of second samples that meet the judgment conditions, and updating the accumulated number of times after each comparison is completed.

[0209] If the current target temperature of the thermal energy storage device is lower than the effective historical target temperature of the thermal energy storage device, it means that the current single comparison meets the no-arbitrage judgment, and the result of this comparison will be included in the cumulative statistics.

[0210] Step 420384: If the second sample count is 1 and there is no target temperature for the current thermal energy storage device, perform a comparison operation between tenants in the same building.

[0211] The same-building tenant comparison operation refers to the operation of retrieving the normal equipment setting temperature of other tenants in the same building, with the same apartment type and the same equipment under the same temperature environment when there is not enough historical samples to complete the judgment, so as to complete the arbitrage behavior judgment.

[0212] If the second sample count is 1 and there is no target temperature for the current thermal energy storage device, it means that the rental record only has a single valid sample and lacks sufficient reference data in the same environment. Further judgment needs to be made by referring to the temperature settings of other tenants in the same building.

[0213] Step 420385: If the number of the second sample is greater than 1, output the target power consumption time as the effective power consumption time.

[0214] If the second sample count is greater than 1, it means that multiple comparisons meet the no-arbitrage criteria and there is no random bias in the single comparison result. Therefore, it is confirmed that the tenant has no intentional thermal storage arbitrage behavior, and the actual measured target electricity usage time is accepted for billing.

[0215] The methods for performing the comparison operation of tenants in the same building include:

[0216] Step 420386: Locate global historical data and determine global similar weather temperatures based on the target weather temperature.

[0217] Globally similar weather temperature refers to the ambient temperature data selected from the historical temperature data of all rooms in the entire building stored locally on the edge terminal, where the temperature difference with the target weather temperature falls within a suitable range.

[0218] Step 420387: Determine the global average temperature of thermal energy storage equipment and the global average temperature of cold energy storage equipment based on global similar weather temperatures.

[0219] The global average thermal energy storage device temperature refers to the arithmetic mean of the set temperatures of each room's heating energy storage appliances in the historical records of all matching global similar weather temperatures.

[0220] The global average temperature of the cold storage equipment refers to the arithmetic mean of the set temperatures of each room's cooling energy storage appliances in the historical records of all matching global similar weather temperatures.

[0221] Step 420388: When a global average thermal energy storage device temperature exists, determine the target temperature of the thermal energy storage device to be verified based on the current target temperature of the thermal energy storage device and the preset fluctuation range.

[0222] The floating range refers to the pre-entered temperature tolerance range of the edge computing module. This range is used to offset individual differences in the daily heating and cooling habits of different tenants, making reasonable adjustments to the original equipment temperature settings. This ensures that the compared values ​​conform to the general usage range, avoiding misjudgments caused by individual usage preferences. Verifying the target temperature of thermal energy storage equipment involves adjusting the tolerance based on the current target temperature of the thermal energy storage equipment; verifying the target temperature of cold energy storage equipment involves adjusting the tolerance based on the current target temperature of the cold energy storage equipment.

[0223] Verifying the target temperature of thermal energy storage equipment refers to obtaining the corrected temperature value by adding a floating range correction value to the current target temperature of the thermal energy storage equipment.

[0224] Step 420389: If the target temperature of the thermal energy storage device is less than the global average temperature of the thermal energy storage device, output the target power consumption duration as the effective power consumption duration.

[0225] When a global average temperature of the thermal energy storage device exists, it indicates that there are sufficient samples of normal heating use in the entire building under the same environment, and the average temperature can be used as a reference benchmark.

[0226] If the target temperature of the thermal energy storage device is lower than the global average temperature of the thermal energy storage device, it means that the tenant's heating setting temperature, after adjusting for fluctuation range, is lower than the average level of the entire building in the same environment. There is no deliberate high-temperature thermal energy storage arbitrage behavior, and the actual measurement duration is accepted.

[0227] Step 420390: If the target temperature of the thermal energy storage device is greater than the global average temperature of the thermal energy storage device, determine the effective electricity usage time according to the standard check-out time.

[0228] If the target temperature of the thermal energy storage device is greater than the global average temperature of the thermal energy storage device, it means that even if the heating temperature is reduced by passing the fluctuation range, the result is still far beyond the standard commonly used in the same environment. There is a suspicion of deliberately storing heat at high temperatures and profiting from power outages. The standard check-out time should be used for billing.

[0229] This also includes:

[0230] Step 420391: When a global average temperature of the cold energy storage device exists, determine the target temperature of the cold energy storage device to be verified based on the current target temperature and fluctuation range of the cold energy storage device.

[0231] Verifying the target temperature of a cold energy storage device refers to the temperature value after fault tolerance correction based on the current target temperature of the cold energy storage device and the fluctuation range.

[0232] When a global average temperature of the cold storage equipment exists, it indicates that there are sufficient normal cooling usage samples in the entire building under the same environment, and the average temperature can be used as a reference benchmark.

[0233] Step 420392: If the target temperature of the verified cold energy storage device is greater than the global average temperature of the cold energy storage device, output the target power consumption duration as the effective power consumption duration.

[0234] If the target temperature of the verified cold storage equipment is greater than the global average temperature of the cold storage equipment, it means that after the floating range fault correction, the set temperature of the equipment is higher than the average cooling temperature of the building during the same period. There is no arbitrage behavior of deliberately lowering the temperature to hoard cold energy, and the actual measured target electricity usage time is directly adopted for billing.

[0235] Step 420393: If the target temperature of the cold storage equipment is less than the global average temperature of the cold storage equipment, determine the effective electricity usage time according to the standard check-out time.

[0236] If the target temperature of the refrigerated energy storage device is lower than the global average temperature of the refrigerated energy storage device, it means that even if the cooling temperature is increased by passing the fluctuation range, the result is still far lower than the standard commonly used in the same environment. This indicates that there is a deliberate hoarding of cold energy for arbitrage, and the standard check-out time billing should be changed.

[0237] Based on the same inventive concept, embodiments of the present invention provide a rental management system based on edge computing.

[0238] A rental management system based on edge computing includes:

[0239] The acquisition module is used to obtain the current room number;

[0240] Memory for storing a program for a rental management method based on edge computing;

[0241] The processor loads and executes programs from memory.

[0242] 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.

[0243] 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 principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A rental management method based on edge computing, characterized in that, include: In response to the acquired signal, obtain the current room number; Collect the daily electricity consumption data corresponding to the current room number. The daily electricity consumption data includes the cumulative daily electricity consumption and the effective electricity consumption duration. If the cumulative daily electricity consumption exceeds the preset threshold for determining the electricity consumption of the property, the cumulative number of valid occupancy days will be counted. The last day is determined based on the number of valid stay days, and the valid electricity usage time is determined based on the last day; The number of hours of stay is determined based on the effective electricity usage time, and the total hourly stay cost is determined according to the preset hourly standard rent. The revised number of valid stay days is determined based on the number of valid stay days and the last day. The total cost for the number of nights is determined based on the adjusted valid number of nights and the preset standard daily rent. The rental settlement bill is determined based on the total cost of the number of nights and the total cost of the number of hours of stay.

2. The rental management method based on edge computing according to claim 1, characterized in that, Methods for determining the effective electricity usage duration based on the last day include: The target electricity consumption data is determined based on the last day; Find the historical electricity usage data corresponding to the current room number; When historical electricity consumption data exists, similar historical electricity consumption data are determined based on the historical electricity consumption data and the target electricity consumption data; Determine the number of days with similar electricity consumption based on historical similar electricity consumption data; The proportion of similar electricity consumption days is determined based on the number of similar electricity consumption days and the number of valid occupancy days. When the proportion of similar electricity consumption days exceeds the preset reliable proportion threshold, the target electricity consumption duration is determined based on the target electricity consumption data, and the target electricity consumption duration is output as the effective electricity consumption duration. When there is no similar historical electricity consumption data, the effective electricity consumption time is determined according to the preset standard check-out time.

3. The rental management method based on edge computing according to claim 2, characterized in that, It also includes a method for determining the effective electricity usage duration when the proportion of similar electricity usage days does not exceed the reliable proportion threshold. This method includes: Find the target weather temperature corresponding to the target electricity consumption data; Find the historical weather temperatures corresponding to similar historical electricity consumption data; The temperature difference is determined based on the target weather temperature and historical weather temperatures; When the temperature difference falls within the preset appropriate temperature difference range, the target power consumption time will be output as the effective power consumption time. When the temperature difference does not fall within the appropriate temperature difference range, the effective electricity usage time shall be determined according to the standard check-out time.

4. The rental management method based on edge computing according to claim 3, characterized in that, Methods for determining effective electricity usage time based on standard check-out duration include: The energy storage temperature type is determined based on the target weather temperature, and the energy storage temperature type is divided into cold energy storage temperature type and hot energy storage temperature type; When the energy storage temperature type is cold energy storage temperature type, historical weather temperatures are searched based on the target weather temperature to determine the first similar weather temperature; Obtain the historical target temperature of the cold storage equipment corresponding to the first similar weather temperature; Obtain the target temperature of the current cold storage equipment corresponding to the target weather temperature; If the current target temperature of the cold energy storage device is greater than the historical target temperature of the cold energy storage device, the target power consumption time will be output as the effective power consumption time. If the current target temperature of the cold storage equipment is lower than the historical target temperature of the cold storage equipment, the effective electricity usage time shall be determined according to the standard return period.

5. The rental management method based on edge computing according to claim 4, characterized in that, Also includes: When the energy storage temperature type is thermal energy storage temperature type, historical weather temperatures are searched based on the target weather temperature to determine the second similar weather temperature; Obtain the historical target temperature of thermal energy storage equipment corresponding to the second similar weather temperature; If the current target temperature of the thermal energy storage device is lower than the historical target temperature of the thermal energy storage device, the target power consumption time will be output as the effective power consumption time. If the current target temperature of the thermal energy storage equipment is greater than the historical target temperature of the thermal energy storage equipment, the effective electricity usage time shall be determined according to the standard return period.

6. The rental management method based on edge computing according to claim 5, characterized in that, Also includes: When no first similar weather temperature exists, the effective first sample weather temperature is determined based on the target weather temperature and historical weather temperatures. Determine the effective historical target temperature for cold energy storage equipment based on the first sample of weather temperature. If the current target temperature of the cold energy storage device is greater than the effective historical target temperature of the cold energy storage device, perform a sample judgment operation; If the current target temperature of the cold storage equipment is lower than the effective historical target temperature of the cold storage equipment, the effective electricity usage time shall be determined according to the standard check-out time. When no second similar weather temperature exists, the effective second sample weather temperature is determined based on the target weather temperature and historical weather temperatures. Determine the target temperature for effective historical thermal energy storage equipment based on the second sample of weather temperatures; If the current target temperature of the thermal energy storage device is lower than the effective historical target temperature of the thermal energy storage device, perform a sample judgment operation; If the current target temperature of the thermal energy storage equipment is greater than the effective historical target temperature of the thermal energy storage equipment, the effective electricity usage time shall be determined according to the standard check-out time.

7. The rental management method based on edge computing according to claim 6, characterized in that, The methods for performing sample judgment operations include: If the current target temperature of the cold energy storage device is greater than the target temperature of the effective historical cold energy storage device, the first sample count is accumulated, and the target temperature of the effective historical cold energy storage device is re-determined to perform the cold energy storage device comparison operation. If the first sample count is 1 and there is no target temperature for the current cold storage equipment, perform a comparison operation with tenants in the same building. If the first sample count is greater than 1, the target power consumption time will be output as the effective power consumption time. If the current target temperature of the thermal energy storage device is lower than the target temperature of the effective historical thermal energy storage device, the second sample count is accumulated, and the target temperature of the effective historical thermal energy storage device is re-determined to perform the thermal energy storage device comparison operation. If the second sample count is 1 and there is no target temperature for the current thermal energy storage device, perform a comparison operation between tenants in the same building. If the number of the second sample is greater than 1, the target power consumption time will be output as the effective power consumption time.

8. The rental management method based on edge computing according to claim 7, characterized in that, Methods for performing comparison operations of tenants in the same building include: Search global historical data and determine global similar weather temperatures based on the target weather temperature; Determine the global average temperature of thermal energy storage equipment and the global average temperature of cold energy storage equipment based on globally similar weather temperatures; When a global average temperature of the thermal energy storage device exists, the target temperature of the thermal energy storage device is determined based on the current target temperature of the thermal energy storage device and the preset fluctuation range. If the target temperature of the thermal energy storage device is less than the global average temperature of the thermal energy storage device, the target power consumption time will be output as the effective power consumption time. If the target temperature of the thermal energy storage device is greater than the global average temperature of the thermal energy storage device, the effective electricity usage time shall be determined according to the standard check-out time.

9. A rental management method based on edge computing according to claim 8, characterized in that, Also includes: When a global average temperature of the cold energy storage device exists, the target temperature of the cold energy storage device is determined based on the current target temperature and fluctuation range of the cold energy storage device. If the target temperature of the cold energy storage device is greater than the global average temperature of the cold energy storage device, the target power consumption time will be output as the effective power consumption time. If the target temperature of the cold storage equipment is lower than the global average temperature of the cold storage equipment, the effective electricity usage time shall be determined according to the standard check-out time.

10. A rental management system based on edge computing, characterized in that, include: The acquisition module is used to obtain the current room number; A memory for storing a program of a rental management method based on edge computing as described in any one of claims 1 to 9; The processor loads and executes programs from memory.

Images