A green building operation carbon emission intelligent monitoring method and system

Abstract

The application discloses a kind of green building operation carbon emission intelligent monitoring method and system, related to carbon emission monitoring technical field, the periodic data of monitoring sensor related to green building operation carbon emission is defined as data train, and each data train is equipped with patrol mechanism;Based on the carbon emission monitoring demand related features of each data train, data train is distributed to high-speed, medium-speed or low-speed channel for transmission;Utilize patrol mechanism to identify the delay data related to green building operation carbon emission, and then update the organization of data train, based on the updated data train features, execute lane-changing operation;Automatic update temporary parking capacity, when identifying that all data trains arrive corresponding temporary parking, the data of all data trains is packaged as carbon emission monitoring data packet, and the carbon emission of green building operation is intelligently monitored using carbon emission monitoring data packet.Solve the transmission delay and fragmentation problem of carbon emission periodic sensor data.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of carbon emission monitoring, in particular to a green building operation carbon emission intelligent monitoring method and system. BACKGROUND

[0002] The building industry is a major carbon emitter, and efficient carbon emission monitoring technology is urgently needed. In the operation of green buildings, there are many sensors, complex data types, and dynamic changes in data characteristics with equipment operating status.

[0003] Traditional monitoring systems lack dynamic adjustment mechanisms and cannot flexibly allocate transmission channels according to data characteristics, resulting in delays or waste of bandwidth resources for high-priority data, and real-time energy consumption data cannot be used for device control in time; sensors may generate delayed data related to green building operation carbon emissions during the data collection period, but traditional methods cannot accurately identify and integrate these data, resulting in damage to the integrity and accuracy of periodic data and affecting the reliability of carbon emission assessment.

[0004] Therefore, in view of the above problems, there is an urgent need for a green building operation carbon emission intelligent monitoring method and system. SUMMARY

[0005] In view of the deficiencies of the prior art, the present application provides a green building operation carbon emission intelligent monitoring method and system, which solves the problems of transmission delay and fragmentation of carbon emission periodic sensor data, and resource rigidity bottleneck of traditional fixed green building operation carbon emission monitoring data transmission bandwidth channel.

[0006] To achieve the above purpose, the present application is realized by the following technical scheme: a green building operation carbon emission intelligent monitoring method, comprising the following steps: receiving periodic data of monitoring sensors related to green building operation carbon emission, defining the data collected by each monitoring sensor in each period as a data train, and based on the adhesion chain, each data train is equipped with a patrol mechanism; based on the carbon emission monitoring demand related characteristics of each data train, the data train is allocated to a high-speed, medium-speed or low-speed channel for transmission; in the data train transmission process, the patrol mechanism is used to identify the green building operation carbon emission related delayed data generated by the same monitoring sensor in the same period, the data train is updated in combination with the green building operation carbon emission related delayed data, and based on the updated data train characteristics, the patrol mechanism is used to perform lane changing operation; the mapping between the patrol mechanism and the temporary parking space is used to automatically update the temporary parking space capacity, when all data trains are identified to arrive at the corresponding temporary parking space, the data of all data trains is packaged as carbon emission monitoring data packet, and the carbon emission monitoring data packet is used to intelligently monitor the carbon emission of the green building operation.

[0007] Further, the circulating mechanism comprises an identification storage unit, a feature perception unit, an association matching unit, a decision control unit and an interaction execution unit; the circulating mechanism is specifically used for: pre-writing the unique identification of the data train by using the identification storage unit, the unique identification information comprising a monitoring sensor ID and a data generation cycle number; capturing the feature vector of the data train in the transmission process in real time by using the feature perception unit, and feeding back the feature vector to the decision control unit, the feature vector comprising a data volume, a carbon emission data type identifier and a real-time transmission speed priority; comparing the delay data with the unique identification of the data train by using the association matching unit, determining the attribution relationship, driving the delay data to be integrated into the target data train by the interaction execution unit; matching the target channel and determining the lane changing position based on the updated features by using the decision control unit, controlling the circulating mechanism to separate from the data train by using the interaction execution unit, and creating a temporary virtual transmission tunnel at the same time; transmitting the circulating mechanism carrying the condensed features to the target channel positioning through the temporary virtual transmission tunnel by using the interaction execution unit, completing the recombination after the data train arrives, and destroying the temporary virtual transmission tunnel; and mapping the temporary parking space by using the association matching unit through the unique identification.

[0008] Further, the specific analysis of the data train being allocated to the high-speed, medium-speed or low-speed channel for transmission is: extracting the carbon emission monitoring demand related features of each data train by using the circulating mechanism, the carbon emission monitoring demand related features comprising a data real-time demand, a data volume and an influence weight of the data on the carbon emission evaluation, setting the transmission adaptation conditions of the high-speed channel, the medium-speed channel and the low-speed channel based on the carbon emission monitoring demand related features, and transmitting each data train to the matched transmission channel.

[0009] Further, the specific analysis of performing the lane changing operation through the cruising mechanism is as follows: updating the data train with the delay data related to the carbon emission of the green building operation, extracting the updated data train features, the updated data train features including the updated data size, the real-time data requirement change, and the influence weight adjustment; comparing the updated data train features with the transmission adaptation conditions of the current channel and other channels, and matching the target channel; predicting the predicted lane changing position of the updated data train from the original channel to the target channel through the cruising mechanism; extracting the condensed features of the updated data train, writing the condensed features into the cruising mechanism, and then separating the cruising mechanism carrying the condensed features from the updated data train by automatically triggering the rupture of the adhesive chain, the condensed features including the data train identifier, the target channel information, and the lane changing position information; transmitting the separated cruising mechanism to a position where the target channel and the lane changing position are consistent in the transmission space distance, establishing a temporary virtual transmission tunnel at the position, and transmitting the cruising mechanism carrying the condensed features to the target channel through the virtual transmission tunnel, the temporary virtual transmission tunnel connecting the target channel and the original channel; when the updated data train passes through the temporary virtual transmission tunnel, transmitting the updated data train to the target channel through the temporary virtual transmission tunnel, and matching the cruising mechanism in the target channel through the condensed features, and recombining the cruising mechanism and the updated data train through adhesive chain regeneration; when receiving the instruction of recombining the cruising mechanism and the updated data train, automatically destroying the temporary virtual transmission tunnel.

[0010] Further, the specific analysis of updating the data train with the delay data related to the carbon emission of the green building operation is as follows: when the data train has entered the transmission channel, identifying whether there is new data generated by the monitoring sensor in the same cycle, marking the new data as delay data of the data train, the delay data carrying the monitoring sensor ID and the data generation cycle number; using the cruising mechanism to scan the delay data related to the carbon emission of the green building operation outside the transmission channel in real time, identifying the target data train belonging to the same monitoring sensor in the same cycle by comparing the monitoring sensor ID and the data generation cycle number of the delay data related to the carbon emission of the green building operation; sending the target data train association instruction to the delay data through the cruising mechanism, and directing the delay data to the corresponding target data train.

[0011] Further, the specific prediction method of the predicted lane changing position is as follows: based on the current position of the data train in the original channel, the transmission speed difference between the original channel and the target channel, and the predetermined arrival synchronization requirement, using the cruising mechanism to determine the predicted lane changing position of the data train.

[0012] Further, the specific analysis of the automatic updating of the temporary parking space capacity is that: a temporary parking space is set for each data train in the temporary data train parking garage, each temporary parking space has a unique mapping relationship with the corresponding monitoring sensor in the data train patrol mechanism in a specific period, and the mapping relationship is associated through the monitoring sensor ID and the data generation period number in the patrol mechanism; the data volume of the data train is obtained in real time during the data train transmission process by using the patrol mechanism, and the data volume is transmitted to the corresponding temporary parking space; the temporary parking space capacity is automatically adjusted according to the received data volume, and a data buffer space is reserved in each temporary parking space; when the data train is updated and assembled, the updated data volume is sent to the temporary parking space by using the patrol mechanism, and the parking space capacity is adjusted again according to the updated data volume.

[0013] Further, the specific analysis of the carbon emission smart monitoring of the green building operation by using the carbon emission monitoring data packet is that: the original data collected by each monitoring sensor in the same period is extracted by using the carbon emission monitoring data packet, the original data includes energy consumption data of building energy-using equipment, indoor environmental parameter data and building material carbon emission factor related data, the influence weight of each original data on carbon emission evaluation is matched by using the carbon emission monitoring demand related features of each data train, the carbon emission status of the green building operation in the period is identified in combination with the influence weight, and the carbon emission change trend of the green building operation is identified based on the carbon emission monitoring data packet of the historical period.

[0014] A green building operation carbon emission smart monitoring system, which applies the green building operation carbon emission smart monitoring method, comprises: a data receiving and defining module, which is used for receiving the periodic data of the monitoring sensor related to the carbon emission of the green building operation, defining the data collected by each monitoring sensor in each period as a data train, and providing each data train with a patrol mechanism based on a bonding chain; a channel allocation module, which is used for allocating the data train to a high-speed, medium-speed or low-speed channel for transmission based on the carbon emission monitoring demand related features of each data train; a lane changing processing module, which is used for identifying the green building operation carbon emission related delayed data generated by the same monitoring sensor in the same period during the data train transmission process by using the patrol mechanism, updating the assembly of the data train in combination with the green building operation carbon emission related delayed data, and performing the lane changing operation by using the patrol mechanism based on the updated data train features; and a parking garage management and monitoring module, which is used for automatically updating the temporary parking space capacity by using the mapping between the patrol mechanism and the temporary parking space, packing all the data trains into a carbon emission monitoring data packet when all the data trains arrive at the corresponding temporary parking space, and performing the carbon emission smart monitoring of the green building operation by using the carbon emission monitoring data packet.

[0015] The present application has the following advantages:

[0016] The green building operation carbon emission intelligent monitoring method and system define the data collected by each monitoring sensor in each cycle as a data train, and equip each data train with a patrol mechanism, so that the data of each sensor and each cycle can be independently and effectively tracked and managed, which helps to more accurately grasp the data situation and provide a reliable basis for subsequent analysis; based on the carbon emission monitoring demand related features of each data train, the data train is distributed to a high-speed, medium-speed or low-speed channel for transmission, the layered transmission strategy can reasonably allocate network resources according to the importance and urgency of the data, ensure the rapid transmission of key data, improve the overall data transmission efficiency, avoid network congestion, and ensure the timeliness of the carbon emission monitoring data; in the data train transmission process, the patrol mechanism is used to identify the green building operation carbon emission related delayed data generated by the same monitoring sensor in the same cycle, and the data train is updated based on the green building operation carbon emission related delayed data, which effectively solves the delay problem that may occur in the data transmission process, ensures the completeness and accuracy of the data of each cycle, avoids the deviation of the monitoring result caused by data loss or error, and improves the reliability of the carbon emission monitoring; based on the updated data train features, the patrol mechanism performs a lane change operation, so that the data transmission can be dynamically adjusted according to the real-time situation, further optimizing the transmission path, adapting to the changes of the network environment, enhancing the flexibility and adaptability of the entire monitoring system, and ensuring stable operation under different conditions; the mapping between the patrol mechanism and the temporary parking space is used to automatically update the capacity of the temporary parking space, and the intelligent resource management method can dynamically adjust the temporary storage resources according to the actual situation of the data train, avoid resource waste or shortage, improve the resource utilization efficiency, and reduce the system operation cost; when all the data trains arrive at the corresponding temporary parking space, the data of all the data trains is automatically summarized and packaged as a carbon emission monitoring data packet, and the data packet is used to intelligently monitor the carbon emission of the green building operation, making the carbon emission monitoring more scientific and efficient.

[0017] Of course, implementing any product of the present application does not necessarily require all the advantages described above. BRIEF DESCRIPTION OF DRAWINGS

[0018] Figure 1 A green building operation carbon emission intelligent monitoring method flow chart of the present application.

[0019] Figure 2 A lane change operation schematic diagram in a green building operation carbon emission intelligent monitoring method of the present application.

[0020] Figure 3 A green building operation carbon emission intelligent monitoring system structure diagram of the present application. DETAILED DESCRIPTION

[0021] The embodiment of the application provides a green building operation carbon emission intelligent monitoring method and system, which solves the core defects of traditional monitoring systems in data transmission, storage and analysis through dynamic channel allocation, delay data integration related to green building operation carbon emission and intelligent capacity management, and provides a systematic solution for real-time, accurate and intelligent management of green building carbon emission.

[0022] The general idea of the embodiment of the application is as follows:

[0023] The green building operation carbon emission monitoring sensor data stream is abstracted as a data train, and the data collected in each cycle forms an independent train unit; a high-speed, medium-speed and low-speed three-channel transmission system is established to realize differentiated data transmission guarantee; the data train is equipped with a patrol mechanism to realize delay data identification and compensation related to green building operation carbon emission, real-time feature-based transmission channel dynamic switching, data integrity verification and temporary storage buffer design.

[0024] Please refer to Figure 1 、 Figure 2 The embodiment of the application provides a technical solution: a green building operation carbon emission intelligent monitoring method, comprising the following steps: receiving periodic data of monitoring sensors related to green building operation carbon emission, defining the data collected by each monitoring sensor in each cycle as a data train, and based on the adhesive chain, each data train is equipped with a patrol mechanism; based on the carbon emission monitoring demand related features of each data train, the data train is allocated to a high-speed, medium-speed or low-speed channel for transmission; in the data train transmission process, the patrol mechanism is used to identify the delay data related to green building operation carbon emission generated by the same monitoring sensor in the same cycle, the data train is updated in combination with the delay data related to green building operation carbon emission, and based on the updated data train features, the patrol mechanism performs a lane change operation; the mapping between the patrol mechanism and the temporary parking space is used to automatically update the temporary parking space capacity, when all data trains arrive at the corresponding temporary parking space, the data of all data trains is aggregated and packaged as a carbon emission monitoring data packet, and the carbon emission monitoring data packet is used to intelligently monitor the carbon emission of the green building operation.

[0025] Specifically, the periodic data of the monitoring sensors related to the carbon emissions of green building operation includes, but is not limited to, the following categories: indoor environmental parameter data: carbon dioxide concentration, temperature, humidity and other parameters in the air are collected by carbon dioxide concentration sensors and temperature and humidity sensors, reflecting indoor air quality and user activity intensity; building energy consumption equipment data: energy consumption information of air conditioners, lighting, elevators, water pumps and other equipment is collected by power metering, gas metering and other energy consumption sensors; building material carbon emission factor related data: carbon emission factors of building materials in the use stage are collected by integrating external databases or material identification, which are used to calculate the amount of implicit carbon emissions; external environment and weather data: outdoor temperature, humidity, wind speed, solar radiation and other factors are collected to assist in analyzing the relationship between building energy consumption changes and carbon emissions.

[0026] The data train refers to the data set collected by each monitoring sensor in a period, which contains the original values of all sampling points in the period and necessary time labels, and has characteristics such as data volume, importance, real-time demand, etc.

[0027] The patrol mechanism is the core logic unit for the whole life cycle management of the data train, and its functions include: storing the unique identification information of the data train, which contains the monitoring sensor ID and the data generation cycle number, and associating and binding all data generated by the same monitoring sensor in the same period through the identification; collecting and updating the feature vector of the data train in real time, including but not limited to data volume, carbon emission data type identifier, real-time transmission speed priority, updated data volume change and influence weight adjustment, etc.; scanning the delayed data outside the transmission channel, identifying the target data train to which the delayed data belongs by comparing the monitoring sensor ID and cycle number carried by the delayed data, and transmitting the delayed data to update the data train composition; based on the updated data train features, matching the target transmission channel, predicting the lane change position, controlling the separation of the patrol mechanism and the data train, the pre-positioning of the target channel and the recombination, and managing the creation and destruction of the temporary virtual transmission tunnel; through the establishment of a unique mapping relationship with the temporary parking space, the data volume of the data train is transmitted to the corresponding parking space in real time, driving the dynamic adjustment of the parking space capacity and the reservation of the buffer space.

[0028] In the embodiment, the circulating mechanism includes an identification storage unit, a feature perception unit, an association matching unit, a decision control unit, and an interactive execution unit, wherein: the identification storage unit is configured to solidify unique identification information of the data train to form an association reference; the feature perception unit is configured to collect and analyze static features and dynamic features of the data train in real time; the association matching unit is configured to realize directional association of the delayed data and the target data train based on the unique identification, and mapping association of the circulating mechanism and the temporary parking space; the decision control unit is configured to make decisions on channel matching, lane change position prediction, and separation or generation of the data train according to the feature perception result; and the interactive execution unit is configured to execute generation or separation operation of the data train, creation or destruction instruction of the temporary virtual transmission tunnel, and interaction with the capacity information of the parking space.

[0029] The circulating mechanism realizes the above functions through the cooperation of the units: the identification storage unit prewrites the unique identification of the data train to provide a reference for association matching; the feature perception unit captures feature changes of the data train in the transmission process in real time, such as an increase in data volume caused by delayed data joining, and feeds back the feature data to the decision control unit; the association matching unit determines the ownership relationship by comparing the unique identification of the delayed data and the data train, and drives the interactive execution unit to integrate the delayed data into the target data train; the decision control unit matches the target channel and calculates the lane change position based on the updated features, controls the separation of the circulating mechanism and the data train through the interactive execution unit, and creates a temporary virtual transmission tunnel; the interactive execution unit transmits the circulating mechanism carrying condensed features to the target channel through the temporary virtual transmission tunnel, completes recombination after the data train arrives, and destroys the temporary virtual transmission tunnel; the association matching unit maps the temporary parking space through the unique identification, and the feature perception unit transmits the data volume information to the parking space to drive dynamic capacity adjustment.

[0030] The circulating mechanism is paired with the data train through the adhesive chain, which adopts a distributed chain structure with an encrypted identification as the core and dynamic instructions as the control. The core of the chain depends on a unique encrypted feature code to ensure the uniqueness and security of the binding, which is different from the static binding based on a single identification in the prior art. The breakage and regeneration of the adhesive chain are triggered by logical instructions to realize dynamic association of the circulating mechanism and the data train, and adapt to flexible switching of the data train among multiple channels.

[0031] The circulating mechanism is different from the simple message queue tag in the prior art, which not only records the basic identification of the data train, but also dynamically records the updated features of the data train in the transmission process, and realizes the lane change, merging, and matching functions of the data train through the logical connection of the circulating mechanism, thereby improving the real-time performance and data integration efficiency.

[0032] Specifically, based on the carbon emission monitoring demand related features of each data train, the data train is assigned to a high-speed, medium-speed or low-speed channel for transmission, which is achieved by the following steps:

[0033] The carbon emission monitoring demand related features are extracted from each data train through a patrol mechanism, including: real-time demand: describes the timeliness requirement of the data train for carbon emission evaluation, which can be divided into high, medium and low levels, for example, sudden changes in indoor carbon dioxide concentration require quick response, the real-time requirement is high, building energy statistics data can be moderately delayed, the real-time requirement is medium, and the building material factor update frequency is low, the real-time requirement is low; data size: the overall volume of the data train; data influence weight on carbon emission evaluation: the importance of data in the data train for carbon emission evaluation, such as carbon dioxide concentration and energy consumption have high weight on emission calculation, and external environmental parameters have low weight.

[0034] According to the system operation experience and demand, the adaptation conditions of each channel are set in advance: the high-speed channel is suitable for data trains with high real-time requirement, small data size and high influence weight; the medium-speed channel is suitable for data trains with medium real-time requirement, medium data size and medium influence weight; and the low-speed channel is suitable for data trains with low real-time requirement, large data size and small influence weight.

[0035] Multi-attribute matching algorithms such as weighted scoring or decision matrix are used to compare the data train features with the three channel adaptation conditions, calculate the matching degree, and assign the data train to the channel with the highest matching degree, if the matching degree is within the boundary range, then dynamically adjust it according to the current channel load.

[0036] In this embodiment, the channel allocation considers real-time, data size and influence weight, ensures that important and urgent data is given priority to pass through the high-speed channel, and secondary data is occupied in the medium and low-speed channels, so that the network resources are optimally configured, and the disadvantages of resource waste or information delay caused by simply dividing channels according to data size in the prior art are avoided.

[0037] Specifically, please refer to Figure 2The specific steps of performing the lane changing operation by the circulating mechanism are as follows: when the system receives the green building operation carbon emission related delayed data belonging to the same sensor and the same cycle, the circulating mechanism merges the green building operation carbon emission related delayed data with the data train, and recalculates the updated data train size, real-time requirement change and influence weight adjustment; the updated data train characteristics are compared with the transmission adaptation conditions of the current channel and other channels, the matching degrees of each channel are calculated, and the target channel with the highest matching degree is selected, if the target channel is the same as the current channel, no lane changing is needed; the circulating mechanism calculates the predicted lane changing position in combination with the current position of the data train in the original channel, the transmission speed difference between the original channel and the target channel and the system synchronization requirement; the updated condensed features are extracted from the data train, including the data train identifier, the target channel information and the lane changing position information, and are written into the circulating mechanism, and then the circulating mechanism carrying the condensed features is separated from the updated data train by automatically triggering the breakage of the adhesive chain; a temporary virtual transmission tunnel is established between the original channel and the target channel according to the predicted lane changing position, so that the two channels are logically connected at this position, and the circulating mechanism carrying the condensed features moves to the same position in the target channel in advance along the temporary virtual transmission tunnel; when the data train runs to the predicted lane changing position in the original channel, the data train is guided into the target channel through the temporary virtual transmission tunnel, and the circulating mechanism is recombined with the updated data train through adhesive chain regeneration; after the circulating mechanism is recombined with the data train, the system automatically destroys the temporary virtual transmission tunnel, and restores the isolation of the original channel and the target channel.

[0038] The lane changing operation ensures that the data train is switched to the appropriate channel in time according to the feature change during transmission, guarantees the data real-time performance and synchronization, and can avoid channel congestion and data loss by pre-calculating the lane changing position and establishing a temporary virtual transmission tunnel, which has a significant advantage compared with the delay and conflict caused by simply jumping to the channel in the prior art.

[0039] In the embodiment, the green building operation carbon emission related delay data generated by the same monitoring sensor in the same period is identified by using the patrol mechanism, and the composition of the data train is updated in combination with the green building operation carbon emission related delay data. The following steps are used to achieve the above: after the data train has entered the transmission channel, the data from each sensor is continuously received, and the input data with the same sensor ID and period number and arriving time later than the created data train is marked as green building operation carbon emission related delay data; the patrol mechanism periodically scans the green building operation carbon emission related delay data buffer area, quickly finds the corresponding target data train by comparing the monitoring sensor ID and the data generation period number carried by the green building operation carbon emission related delay data, and uses the patrol mechanism to locate to avoid traversing all data trains, thereby greatly improving the matching efficiency; the patrol mechanism sends an association instruction to the green building operation carbon emission related delay data, instructs it to transmit the data packet to the target data train, appends the green building operation carbon emission related delay data to the end of the data train according to the data protocol, and synchronously updates the characteristics of the data train; after the green building operation carbon emission related delay data is merged, if the real-time requirement, data volume or influence weight of the data train changes greatly, the lane changing decision process is entered; otherwise, the data train continues to transmit along the original channel.

[0040] The green building operation carbon emission related delay data updating mechanism ensures that all data generated by the same sensor in the same period can be attributed to the same data train, avoiding data fragmentation or loss. Through the patrol mechanism, the target data train is quickly located, solving the problem of low efficiency of green building operation carbon emission related delay data processing in the prior art, and ensuring the accuracy of subsequent decision-making through dynamic updating of characteristics.

[0041] The lane-changing position is predicted by the following steps: obtaining the current position of the data train in the original lane, the transmission rate of the current lane, and the transmission rate of the target lane in real time, and predicting the remaining distance of the lane and the synchronous arrival time of the data train in the current period; obtaining the difference between the remaining distance of the lane and the current position of the data train in the original lane, and then obtaining the predicted arrival time of the data train in the original lane by dividing the difference by the transmission rate of the current lane; obtaining the predicted arrival time of the data train in the target lane by the transmission rate of the target lane, and if the difference between the predicted arrival time of the data train in the original lane and the predicted arrival time of the data train in the target lane and the synchronous arrival time of the data train in the current period is greater than a preset time deviation threshold, calculating the switching position point; setting the lane safety interval and the data train length constraint to obtain a switching interval that satisfies the safety interval, and identifying the switching position point that makes the arrival time as close as possible to the synchronous arrival time of the data train in the current period after switching the data train to the target lane in the switching interval; since other data trains may also change lanes at the same time, the switching position point calculation result is updated in real time to ensure that multiple lane-changing operations do not conflict.

[0042] By predicting the optimal switching position before lane-changing, the time of the data train driving in the target lane can be accurately adjusted, so that the data trains arrive at the lane end almost simultaneously. Compared with the prior art of fixed lane-changing point, the time synchronization accuracy and lane utilization efficiency are greatly improved, considering the difference in lane speed, current position and arrival time requirements.

[0043] The specific analysis of separating the patrol mechanism carrying the condensed feature from the updated data train by automatically triggering the breakage of the adhesive chain is as follows: when the lane-changing operation needs to be performed, the patrol mechanism and the data train are separated by triggering the breakage of the adhesive chain through the condensed feature. The specific steps are as follows: the decision control unit of the patrol mechanism extracts the condensed feature of the data train and writes it into its own storage area, and at this time a separation trigger signal is generated; the separation trigger signal is transmitted to the core link of the adhesive chain, and the feature comparison logic is built-in the link. When it is detected that the patrol mechanism has carried the condensed feature, the breakage instruction of the adhesive chain is automatically executed; after the breakage of the adhesive chain, the patrol mechanism and the data train are unbonded, the patrol mechanism is driven by the interactive execution unit and is transmitted to the predetermined position of the target lane through a temporary virtual transmission tunnel in advance, and the data train continues to transmit along the original lane, and its metadata area only retains the breakage mark of the adhesive chain for subsequent combination verification.

[0044] The specific analysis of recombining the circulating mechanism with the updated data train through the adhesion chain regeneration is as follows: for the circulating mechanism that arrives at the target channel for positioning, a binding request signal is released through the interactive execution unit, and the signal carries a complete encryption feature code; when the data train arrives at the target channel through the temporary virtual transmission tunnel, the broken mark of the metadata area of the data train, i.e., the encrypted feature code fragment, is compared with the complete encrypted feature code of the circulating mechanism; if the comparison is consistent, the interactive execution unit of the circulating mechanism generates a chain regeneration instruction to drive the core chain of the adhesion chain to reconstruct the bidirectional binding link based on the original encrypted feature code; after the adhesion chain is regenerated, the automatic recovery activation state is restored, the circulating mechanism and the data train reestablish real-time data interaction, and the combination is completed; at this time, the temporary virtual transmission tunnel is automatically destroyed due to the combination instruction triggering.

[0045] Specifically, the automatic updating of the temporary parking space capacity is implemented by the following steps: during initialization, the temporary parking garage is set with the same number of temporary parking spaces as the monitoring sensors, and each parking space is uniquely mapped with the circulating mechanism of the corresponding sensor, and the mapping is realized through the sensor ID and the cycle number in the circulating mechanism, so that the data train can be correctly parked even after multiple lane changes; during the transmission of the data train, the circulating mechanism sends the current data size of the data train to the corresponding parking space manager in real time, and the parking space manager automatically adjusts the available capacity according to the data size and reserves buffer space for different transmission stages; if the data train changes in data size due to the delay data integration related to the carbon emissions of green buildings during operation, the circulating mechanism sends the new data size to the parking space manager, and the parking space capacity is updated synchronously, so as to avoid data overflow or space waste when the data train arrives at the parking space; whether all data trains are in place is determined by comparing the total number of monitoring sensors with the number of parked parking spaces; when all parking spaces have data trains temporarily stored, the data packaging process is triggered.

[0046] In the embodiment, the automatic updating of the temporary parking space capacity ensures that the parking space capacity matches the data size of the data train, avoiding overflow or space waste caused by fixed buffers in the prior art; in addition, the parking space is quickly located through the mapping relationship, and the capacity is updated in time, ensuring the packaging efficiency and data integrity of the data train after it arrives.

[0047] Specifically, the carbon emission intelligent monitoring of green building operation is realized by using the carbon emission monitoring data package by the following steps: extracting the original data of each monitoring sensor in the same monitoring period from the carbon emission monitoring data package, including the energy consumption data of building energy consumption equipment, indoor environmental parameter data and building material carbon emission factor; using the influence weight of the carbon emission monitoring demand related features of each data train to match the contribution of each original data to carbon emission evaluation, for example, the weight of carbon dioxide concentration change and energy consumption in carbon emission accounting in unit time is higher, and the weight of temperature and humidity data is relatively low; according to the existing carbon emission accounting standard, such as emission factor method, energy consumption conversion coefficient method, etc., the carbon emission of the building in the period is calculated; at the same time, according to the data package of historical period, the carbon emission intensity, unit area carbon emission and other indexes are calculated, the influence of different time periods and different equipment operation on carbon emission is analyzed; using statistical analysis or machine learning algorithm to analyze the trend of historical period monitoring data package, identify the change rule of building operation carbon emission, such as holiday and working day difference, seasonal change, equipment maintenance influence; generate carbon emission analysis report, carbon emission analysis report includes emission amount, main emission source, time sequence trend and emission reduction suggestion, provide decision support for building managers, compare with preset standard according to real-time monitoring result, alarm or trigger energy saving control strategy in time.

[0048] In the embodiment, the analysis of carbon emission monitoring data package can process multiple source heterogeneous data at one time, avoid the error caused by single data, provide comprehensive carbon emission evaluation result, combine with historical data trend analysis, help building managers to find out abnormal situation in time and formulate effective low-carbon operation strategy.

[0049] Please refer to Figure 3The application discloses a green building operation carbon emission intelligent monitoring system, and applies the green building operation carbon emission intelligent monitoring method, and the system comprises the following modules: a data receiving and defining module, which is used for receiving periodic data of monitoring sensors related to green building operation carbon emission, defining the data collected by each monitoring sensor in each period as a data train, and providing a patrol mechanism for each data train based on a bonding chain; a channel allocation module, which is used for allocating the data trains to high-speed, medium-speed or low-speed channels for transmission based on the carbon emission monitoring demand related features of the data trains; a lane changing processing module, which is used for identifying delayed data of green building operation carbon emission generated by the same monitoring sensor in the same period in the data train transmission process by using the patrol mechanism, updating the composition of the data train in combination with the delayed data of green building operation carbon emission, and performing a lane changing operation by using the patrol mechanism based on the features of the updated data train; and a parking lot management and monitoring module, which is used for automatically updating the capacity of temporary parking spaces by using the mapping between the patrol mechanism and the temporary parking spaces, packing the data of all the data trains into a carbon emission monitoring data packet when all the data trains arrive at the corresponding temporary parking spaces, and performing intelligent monitoring on the carbon emission of the green building by using the carbon emission monitoring data packet.

[0050] In summary, the application has at least the following effects:

[0051] The periodic data of the monitoring sensors related to green building operation carbon emission is defined as a data train and provided with a patrol mechanism, so that fine management is realized; the transmission channels are allocated according to features, so that the transmission efficiency is optimized, and the key data for evaluating carbon emission is ensured to be delivered in time; the delayed data of green building operation carbon emission is processed by using the patrol mechanism in the transmission process, so that the integrity is ensured, and the lane can be dynamically changed to adapt to network changes; the capacity is automatically updated by using the mapping between the patrol and the temporary parking spaces, so that the resource utilization rate is improved; when the data train is in place, the data is automatically packed into a monitoring packet for intelligent monitoring, so that the manual intervention is reduced, the error rate is reduced, and the carbon emission monitoring of the green building is more scientific, efficient, economic and feasible.

[0052] Those skilled in the art will understand that the embodiments of the application can be provided as methods, systems. Therefore, the application can adopt a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the application can adopt the form of a computer program product implemented on one or more computer usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer usable program codes.

[0053] The application is described with reference to the figures of the drawings in connection with methods, systems of the application. It will be understood that each flow and associated block in the figures and combinations of flows and blocks in the figures can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flow Figure 1 The flow and associated block in the figures and combinations of flows and blocks in the figures can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flow Figure 1 The flow and associated block in the figures and combinations of flows and blocks in the figures can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flow The flow and associated block in the figures and combinations of flows and blocks in the figures can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flow

[0054] The flow and associated block in the figures and combinations of flows and blocks in the figures can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flow Figure 1 The flow and associated block in the figures and combinations of flows and blocks in the figures can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flow Figure 1 The flow and associated block in the figures and combinations of flows and blocks in the figures can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flow The flow and associated block in the figures and combinations of flows and blocks in the figures can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flow

[0055] The flow and associated block in the figures and combinations of flows and blocks in the figures can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flow Figure 1 The flow and associated block in the figures and combinations of flows and blocks in the figures can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flow Figure 1 The flow and associated block in the figures and combinations of flows and blocks in the figures can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flow The flow and associated block in the figures and combinations of flows and blocks in the figures can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flow

[0056] Although preferred embodiments of the application have been described herein, it will be apparent to those skilled in the art that various modifications can be made within the scope of the application. Accordingly, it is intended that all such modifications come within the scope of the application as defined by the claims and their equivalents.

[0057] Obviously, numerous modifications and variations of the present application are possible in light of the above teachings. It is therefore to be understood that within the scope of the appended claims and their equivalents, the application can be practiced otherwise than as specifically described.

Claims

1. A green building operation carbon emission intelligent monitoring method, characterized in that, The method comprises the following steps: receiving periodic data of monitoring sensors related to carbon emissions of green building operation, defining the data collected by each monitoring sensor in each period as a data train, and assigning a patrol mechanism to each data train based on a sticky chain; based on the carbon emission monitoring demand related features of each data train, the data train is assigned to a high-speed, medium-speed or low-speed channel for transmission; during the transmission of the data train, the patrol mechanism is used to identify the delay data generated by the same monitoring sensor in the same period, the data train is updated based on the delay data related to the carbon emissions of the green building operation, and the patrol mechanism performs a lane change operation based on the updated data train features; using the mapping between the patrol mechanism and the temporary parking space, the capacity of the temporary parking space is automatically updated, and when all data trains are identified to arrive at the corresponding temporary parking space, the data of all data trains is packaged as a carbon emission monitoring data packet, and the carbon emission monitoring data packet is used to monitor the carbon emissions of the green building operation.

2. The green building operation carbon emission intelligent monitoring method according to claim 1, characterized in that, The patrol mechanism comprises an identification storage unit, a feature perception unit, an association matching unit, a decision control unit and an interactive execution unit; The patrol mechanism is specifically used for: pre-writing the unique identifier of the data train in the identification storage unit, and the unique identifier information includes the monitoring sensor ID and the data generation period number; the feature perception unit is used to capture the feature vector of the data train in the transmission process in real time, and the feature vector is fed back to the decision control unit, and the feature vector includes data volume, carbon emission data type identifier and real-time transmission speed priority; the association matching unit is used to compare the delay data with the unique identifier of the data train to determine the ownership relationship, and the interactive execution unit is used to drive the delay data to integrate into the target data train; the decision control unit is used to match the target channel and determine the lane change position based on the updated features, and the interactive execution unit is used to control the patrol mechanism to separate from the data train, and a temporary virtual transmission tunnel is created; the interactive execution unit is used to transmit the patrol mechanism carrying the condensed features to the target channel through the temporary virtual transmission tunnel, and the data train is recombined after the data train arrives, and the temporary virtual transmission tunnel is destroyed; the association matching unit is used to map the temporary parking space through the unique identifier.

3. The green building operation carbon emission intelligent monitoring method according to claim 1, characterized in that, The specific analysis of assigning the data train to the high-speed, medium-speed or low-speed channel for transmission is as follows: the patrol mechanism is used to extract the carbon emission monitoring demand related features of each data train, the carbon emission monitoring demand related features include data real-time demand, data size and data influence weight on carbon emission evaluation, and the transmission adaptation conditions of the high-speed channel, the medium-speed channel and the low-speed channel are set based on the carbon emission monitoring demand related features, and each data train is transmitted to the matched transmission channel.

4. The green building operation carbon emission intelligent monitoring method according to claim 1, characterized in that, The specific analysis of performing a lane change operation by the patrol mechanism is as follows: the data train is updated using the delay data related to the carbon emissions of the green building operation, and the updated data train features are extracted, the updated data train features include updated data size, data real-time demand change and influence weight adjustment; The updated data train feature is compared with the transmission adaptation condition of the current channel and the transmission adaptation conditions of other channels, and a target channel is matched; The updated data train is predicted to switch from the original channel to the target channel by using a patrol mechanism to predict the predicted lane change position; The condensed feature of the updated data train is extracted, and the condensed feature is written into the patrol mechanism, and then the patrol mechanism carrying the condensed feature is separated from the updated data train by automatically triggering the breaking of the adhesive chain, and the condensed feature includes data train identification, target channel information and lane change position information; The separated patrol mechanism is transmitted to a position where the target channel and the lane change position are consistent in transmission space distance, and a temporary virtual transmission tunnel is established at the position, and the patrol mechanism carrying the condensed feature is transmitted to the target channel for waiting by using the virtual transmission tunnel, and the temporary virtual transmission tunnel connects the target channel and the original channel; When the updated data train passes through the temporary virtual transmission tunnel, the updated data train is transmitted to the target channel through the temporary virtual transmission tunnel, and the patrol mechanism in the target channel is matched through the condensed feature, and the patrol mechanism is recombined with the updated data train through adhesive chain regeneration; When the patrol mechanism and the updated data train are recombined, the temporary virtual transmission tunnel is automatically destroyed.

5. The green building operation carbon emission intelligent monitoring method according to claim 4, characterized in that, The specific analysis of updating the data train with the delay data related to the carbon emission of green building operation is as follows: After the data train has entered the transmission channel, it is identified whether new data is generated in the same cycle of the monitoring sensor, and the new data is marked as delay data of the data train, and the delay data carries the monitoring sensor ID and the data generation cycle number; The delay data related to the carbon emission of green building operation outside the transmission channel is scanned in real time by using the patrol mechanism, and the target data train belonging to the same monitoring sensor in the same cycle is identified by comparing the monitoring sensor ID and the data generation cycle number of the delay data related to the carbon emission of green building operation; The target data train association instruction is sent to the delay data by the patrol mechanism, and the delay data is transmitted to the corresponding target data train.

6. The green building operation carbon emission intelligent monitoring method according to claim 4, characterized in that, The specific prediction method of the predicted lane change position is as follows: based on the current position of the data train in the original channel, the transmission speed difference between the original channel and the target channel, and the predetermined arrival synchronization requirement, the patrol mechanism is used to determine the predicted lane change position of the data train.

7. The green building operation carbon emission intelligent monitoring method according to claim 2, characterized in that, The specific analysis of automatically updating the capacity of the temporary parking space is as follows: The same number of temporary parking spaces as the number of monitoring sensors is set for the temporary data train parking garage, and each temporary parking space has a unique mapping relationship with the patrol mechanism of the data train of the corresponding monitoring sensor in a specific cycle, and the mapping relationship is associated by the monitoring sensor ID and the data generation cycle number in the patrol mechanism; The data amount of the data train is obtained in real time by using the patrol mechanism during the transmission of the data train, and the data amount is transmitted to the corresponding temporary parking space; The capacity of the temporary parking space is automatically adjusted according to the received data amount, and data buffer space is reserved in each temporary parking space. When the data train is updated and reorganized, the updated data size is sent to the temporary parking space by using the cruising mechanism, and the parking space capacity is adjusted again according to the updated data size.

8. The green building operation carbon emission intelligent monitoring method according to claim 3, characterized in that, The specific analysis of the carbon emission intelligent monitoring of the green building operation by using the carbon emission monitoring data packet is as follows: the original data collected by each monitoring sensor in the same period is extracted by using the carbon emission monitoring data packet, the original data includes energy consumption data of building energy consumption equipment, indoor environmental parameter data and building material carbon emission factor related data, the influence weight of each original data on carbon emission evaluation is matched by using the carbon emission monitoring demand related features of each data train, the carbon emission status of the green building operation in the period is identified in combination with the influence weight, and the carbon emission change trend of the green building operation is identified based on the carbon emission monitoring data packet of the historical period.

9. A green building operation carbon emission intelligent monitoring system, applying the green building operation carbon emission intelligent monitoring method of any one of claims 1-8, characterized in that, Comprise: A data receiving and defining module is used for receiving periodic data of monitoring sensors related to carbon emission of green building operation, defining the data collected by each monitoring sensor in each period as a data train, and providing each data train with a cruising mechanism based on a sticking chain; A channel allocation module is used for allocating the data train to a high-speed, medium-speed or low-speed channel for transmission based on the carbon emission monitoring demand related features of each data train; A lane changing processing module is used for identifying the delayed data related to carbon emission of green building operation generated by the same monitoring sensor in the same period during the transmission of the data train by using the cruising mechanism, updating the organization of the data train in combination with the delayed data related to carbon emission of green building operation, and performing lane changing operation by using the cruising mechanism based on the updated features of the data train; A parking garage management and monitoring module is used for automatically updating the temporary parking space capacity by using the mapping between the cruising mechanism and the temporary parking space, identifying that all data trains arrive at the corresponding temporary parking space, packing the data of all data trains into a carbon emission monitoring data packet, and performing carbon emission intelligent monitoring of the green building operation by using the carbon emission monitoring data packet.

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