Control method based on zero-carbon laboratory
By generating a mapping data table and randomly combining eight-bit binary numbers, the energy consumption and management risks of key encryption methods in zero-carbon laboratories are solved, achieving low-carbon and secure data transmission and reducing hardware requirements and carbon emissions.
Patent Information
- Application Number
- CN202511579722.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-10-31
- Publication Date
- 2026-02-24
AI Technical Summary
Existing technologies in zero-carbon laboratories present significant energy consumption problems with key encryption methods, high key management risks, and impact carbon emission control targets. Furthermore, traditional improvement methods can only partially reduce energy consumption and cannot fundamentally eliminate the dependence on keys.
By generating a mapping data table, the object monitoring data is converted into a binary data stream, and multiple types of eight-bit binary numbers are generated by random combination. This avoids the key generation, storage, and distribution stages, and uses the mapping data table for data transmission, thereby achieving data security and low-carbon goals.
It effectively reduces energy consumption and carbon emissions, improves data transmission security, reduces hardware investment and operation and maintenance costs, and ensures the stable operation of the zero-carbon laboratory.
Smart Images
Figure CN121559922A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of zero-carbon technology, specifically a control method based on a zero-carbon laboratory. Background Technology
[0002] As the core carrier of green transformation in scientific research, zero-carbon laboratories need to achieve the goal of "near-zero carbon emissions throughout the entire life cycle." Their stable operation is highly dependent on the real-time and reliability of monitoring data. This monitoring data covers key information such as energy consumption, carbon emissions, environmental parameters, and equipment operation data. As the scale of laboratories continues to expand, the single local management model can no longer meet the needs of collaborative management and control of multiple laboratories, remote operation and maintenance, and long-term data storage. Therefore, it is necessary to transmit the monitoring data to the cloud platform. Through the cloud, centralized storage, multi-terminal sharing, big data analysis, and remote control of data can be achieved. This cloud management model can not only break geographical limitations and support managers to obtain the operating status of multiple zero-carbon laboratories in real time from different locations, but also achieve remote control of laboratory equipment through cloud commands. At the same time, the large-capacity storage capacity of the cloud can meet the long-term archiving needs of monitoring data and provide data support for subsequent zero-carbon operation optimization analysis. Therefore, cloud data transmission and cloud control have become a necessary mode for the management of zero-carbon laboratories.
[0003] In existing technologies, zero-carbon laboratories typically collect monitoring data of objects periodically through hardware modules such as sensors and data acquisition devices. Since the raw data collected is mostly analog signals (such as current signals and voltage signals output by sensors) or decimal digital signals, while cloud transmission and processing require digital and standardized data formats, it is necessary to convert the raw object monitoring data into binary data streams. This data stream has the advantages of fast transmission rate, strong anti-interference ability and compatibility with cloud data interfaces, and is a necessary prerequisite for realizing cloud data transmission.
[0004] To ensure the security of binary data streams during cloud transmission and prevent data theft, tampering, or forgery, existing technologies generally employ key encryption methods to process the data streams. Commonly used encryption algorithms include symmetric encryption algorithms (AES) and asymmetric encryption algorithms (RSA). However, these encryption methods have significant energy consumption issues: the key generation stage requires complex mathematical calculations using dedicated encryption chips or processors, consuming a large amount of electrical energy. In scenarios with concurrent transmission across multiple laboratories, energy consumption increases linearly with the amount of data. The key storage stage requires dedicated secure storage hardware (such as a hardware security module, HSM), which requires continuous power to maintain the encrypted state. Its production and maintenance also generate additional carbon emissions. The key distribution stage requires transmitting the key to the cloud platform and local decryption unit through a secure channel. The multiple authentication and data verification processes during distribution not only increase transmission latency but also generate additional energy consumption. The key periodic update stage requires repeating the "generation-storage-distribution" process, further exacerbating energy accumulation. This will seriously affect the carbon emission control targets of zero-carbon laboratories.
[0005] In addition to energy consumption issues, traditional key encryption also suffers from key management risks, which can indirectly increase energy consumption: if a key is leaked during storage or distribution, a full-system key reset must be performed immediately. During the reset process, data transmission and cloud control must be suspended, and the laboratory must temporarily switch to a local emergency operation mode. However, the energy efficiency of equipment in the local emergency mode is usually lower than that in the cloud-optimized control mode, resulting in additional energy waste. If a key is lost or damaged, all keys must be regenerated and distributed, which not only prolongs the data transmission interruption time but also requires more hardware resources for key recovery, further increasing energy consumption and maintenance costs.
[0006] To address the aforementioned issues, the industry has undertaken some improvement attempts, such as using lightweight encryption algorithms (e.g., SM4) to reduce the computational energy consumption of key generation, or using key pool technology to reduce the frequency of key updates. However, these improvements can only reduce energy consumption locally and cannot fundamentally eliminate the dependence on keys. Lightweight algorithms still need to complete key generation, storage, and distribution, only with a slight reduction in energy consumption. Although key pool technology reduces the number of key updates, it still needs to bear the basic energy consumption of key management in the long run, and the maintenance of key pools also requires additional hardware support.
[0007] To address the above problems, this invention proposes a solution. Summary of the Invention
[0008] The purpose of this invention is to provide a control method based on a zero-carbon laboratory in order to solve the problems mentioned in the background art.
[0009] This invention provides a control method based on a zero-carbon laboratory, comprising:
[0010] Step 1: The information acquisition module periodically collects the object monitoring data of the target laboratory and transmits it to the first processing unit in real time. The object monitoring data contains monitoring data of several target objects.
[0011] Step 2: After receiving the periodically transmitted object monitoring data, the first processing unit converts it into a binary data stream and generates a mapping data table of the target laboratory in real time according to the preset generation steps.
[0012] Step 3: After generating the mapping data table, the first processing unit maps the binary data stream according to the preset mapping rules to obtain the first processed data of the periodic target laboratory and transmits it to the second processing unit.
[0013] Step 4: After receiving the periodically transmitted first processed data, the second processing unit compresses it to obtain the periodically transmitted target laboratory second processed data, and transmits the second processed data to the cloud control platform.
[0014] Furthermore, the steps for generating the mapping data table for the target laboratory are as follows:
[0015] S11: Create a 4-row, 4-column spreadsheet using pre-selected software. Fill each cell of the spreadsheet with the 16 bases of the four-bit binary number as the fill source according to a preset fill order. The fill order is based on the decimal values of the 16 bases of the binary number, which are filled into each cell of the spreadsheet in ascending order.
[0016] S12: Label the 16 base codes as A0, A1, ..., A15 in the order they are filled into the cells;
[0017] S13: Determine the four-neighbor list B0 and the row and column list C0 of the cell containing the base code A0 in the spreadsheet, respectively:
[0018] S14: Perform the first update on row and column list C0. The update content is as follows: In row and column list C0, remove all base codes that are simultaneously contained in row and column list C0 and four neighboring lists B0 to complete the first update of row and column list C0.
[0019] S15: Determine the four neighbor lists B1, B2, ..., B15 and the row and column lists C1, C2, ..., C15 in sequence according to S13, and complete the first update of the row and column lists C1, C2, ..., C15 according to S14;
[0020] S16: Extract all elements contained in the row and column list C0, C1, ..., C15 and remove duplicates. Construct a set C_all based on all remaining elements after deduplication. After construction, assign an allocation status to each element in the set C_all. There are two allocation statuses: allocated and unallocated. The default allocation status is unallocated when assigning an allocation status.
[0021] S17: Assign priority based on the number of elements in the row and column lists of the base A0, A1, ..., A15, with priority starting from 1 and proceeding sequentially. The lower the priority, the fewer the number of elements in the row and column lists of the corresponding base.
[0022] S18: Remove several elements from the row and column lists C0, C1, ..., C15 according to the preset removal steps to complete the second update of the row and column lists C0, C1, ..., C15;
[0023] S19: Create a data table with three fields: base code, neighbor list, and row / column. Based on the 16 base ...
[0024] Furthermore, in S11, the filling order is to fill each cell in the spreadsheet in ascending order of the decimal values of the 16 base codes. The 16 base codes of the four-bit binary numbers are 0000, 0001, 0010, 0011, 0100, 0101, 0110, 0111, 1000, 1001, 1010, 1011, 1100, 1101, 1110, and 1111.
[0025] Furthermore, in S13, the contents of the four-neighbor list B0 of the base A0 are determined as follows:
[0026] S21: Create an empty list of base A0, and locate the coordinates (X1, Y1) of the cell in the spreadsheet to be filled with base A0, where the x and y coordinates are the row and column of the cell in the spreadsheet, respectively.
[0027] S22: Identify all cells that are adjacent to the cell in the spreadsheet. For each cell identified, obtain the base code filled in the cell and add the base code to the list. After identifying and adding all base codes, mark the list as the four-neighbor list of base code A0, labeled as B0. The adjacent relationship includes top adjacent, bottom adjacent, left adjacent and right adjacent.
[0028] Furthermore, in S22, the cells that are adjacent to the cell above are located in row X1-1 and column Y1 of the spreadsheet; the cells that are adjacent to the cell below are located in row X1+1 and column Y1 of the spreadsheet; the cells that are adjacent to the cell ...
[0029] Furthermore, in S13, the contents of the row and column list C0 of the base A0 are determined as follows:
[0030] Create an empty list of base A0. In the spreadsheet, identify all cells that are in the same row or column as the cell. For each cell identified, obtain the base code filled in the cell and add the base code to the list. After identifying and adding all base codes, mark the list as the row and column list of base A0 and label it as C0.
[0031] In this context, "row" and "column" refer to cells in the spreadsheet that are in the same row and column as the cell filled with the base A0, respectively.
[0032] Furthermore, in S18, the removal steps are as follows:
[0033] S31: Perform a selection operation several times. Each time a selection operation is performed, a set of operations is obtained. Each set of operations contains one element randomly selected from the row and column lists of 16 base-based ...
[0034] S32: Mark all operation sets sequentially according to the index sum of the operation sets in ascending order, labeled as D1, D2, ..., Dd, where d≥1; where the index sum of any operation set is the sum of the indices of all elements in the operation set in the corresponding row and column lists before selection; if there are several operation sets with the same index sum, then extract the index of the element selected from the row and column lists corresponding to the base code of the corresponding priority from these operation sets in ascending order of priority, with the smaller the index, the earlier it is marked;
[0035] S33: Select the first set of operations that satisfies the constraints from the set of operations D1, D2, ..., Dd according to the preset selection steps, and use it as the constraint set;
[0036] S34: Based on each element contained in the constraint combination, remove all elements other than the selected element from the row and column list to complete the second update of the corresponding row and column list.
[0037] Furthermore, in step S33, the first set of operations that satisfies the constraints is selected from the operation sets D1, D2, ..., Dd as the constraint set. The selection steps are as follows:
[0038] S331: Determine the check list of operation set D1 based on base A0, A1, ..., A15;
[0039] S332: Use 256 unsigned 8-bit binary numbers to determine whether the operation set D1 satisfies the constraints. The content is as follows:
[0040] Based on each of the 256 unsigned octet binary numbers, the octet binary number is split into a sequence consisting of the first four characters, denoted as sequence X, and a sequence consisting of the last four characters, denoted as sequence Y.
[0041] If, in base A0, A1, ..., A15, exactly one base has a four-neighbor list containing sequence X and a check list containing sequence Y, then operation set D1 is determined to satisfy the constraint, and operation set D1 is selected as the constraint set; otherwise, operation set D1 is determined not to satisfy the constraint, and operation sets D2, D3, ..., Dd are determined in the order of operation sets D1, D2, ..., Dd to satisfy the constraint, until the first operation set that satisfies the constraint appears, and that operation set is selected as the constraint set.
[0042] Furthermore, the mapping rules for the first processed data of the periodic target laboratory are as follows:
[0043] S41: Divide the characters in the binary data stream into groups of four, from left to right. Each group corresponds to a mapping array. According to the order of these mapping arrays in the binary data stream, they are labeled as E1, E2, ..., Ee from left to right, where e is the total number of groups.
[0044] S42: Obtain the four neighbor list and row and column list corresponding to the same base as the original code of the mapping array E1 from the original code field of the mapping data table, randomly select an element from the four neighbor list as the first element of the mapping array E1, and extract the element from the row and column list as the second element of the mapping array E1.
[0045] The first element and the second element are concatenated to obtain the encrypted sequence of the mapping array E1. During the concatenation process, the first element is at the leftmost end of the encrypted sequence.
[0046] S43: Obtain the encryption sequences of mapping arrays E2, E3, ..., Ee in sequence according to S41 to S42. Then, concatenate the encryption sequences of mapping arrays E1, E2, ..., Ee in the order of mapping arrays E1, E2, ..., Ee to obtain the first processed data of the periodic target laboratory.
[0047] Furthermore, after completing step four, the following steps also need to be completed:
[0048] After receiving the second processing data of the periodic target laboratory, the cloud control platform restores it to obtain the object monitoring data of the periodic target laboratory. The object monitoring data is stored and displayed to the management personnel, who then analyze it to determine whether it is necessary to control several target objects in the target laboratory to ensure that the preset operating indicators of the zero-carbon laboratory are met.
[0049] Compared with existing technologies, it has the following advantages:
[0050] This invention periodically collects monitoring data of objects in a zero-carbon laboratory through an information acquisition module. Upon receiving the monitoring data, the first processing unit converts it into a binary data stream and instantly generates a mapping data table. This table maps each mapping array obtained from the binary data stream. The mapping data table stores the four-neighbor lists and row / column lists corresponding to each of the 16 base codes. Randomly combining the list elements of any base code generates several 8-bit binary numbers corresponding to that base code. A total of 256 8-bit binary numbers are generated from the 16 base codes. This process eliminates the need for complex mathematical operations for key generation, dedicated hardware for key storage, secure channel key distribution, and the periodic repetition of the "generate-store-distribute" process. It directly eliminates the entire key management process, fundamentally avoiding the energy consumption associated with these steps, and effectively reducing the total energy consumption and carbon emissions of the zero-carbon laboratory.
[0051] This invention avoids key management risks by randomly combining and generating multiple types of eight-bit binary numbers, greatly improving the randomness and concealment of the data mapping process. Compared with encryption logic with fixed keys, the dynamic mapping relationship formed by random combination is difficult to crack and does not rely on fixed keys, fundamentally eliminating the risk of key leakage and loss. It avoids the extra energy waste caused by cloud transmission interruption and laboratory switching to inefficient local emergency mode due to key problems, while reducing the hardware investment and operation and maintenance costs required for key recovery, and ensuring the security of core monitoring data of the zero-carbon laboratory in cloud transmission and processing.
[0052] This invention eliminates the dependence on keys and achieves security and low-carbon goals through simplified mapping. It eliminates the need to bear the basic energy consumption of key management and the need to configure additional hardware for maintaining the key pool. While improving data security, it further improves the energy efficiency ratio of the overall system and reduces the investment in hardware equipment required for key management. Attached Figure Description
[0053] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation
[0054] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0055] Please see Figure 1This application provides a control method based on a zero-carbon laboratory. The method is executed by a control system based on a zero-carbon laboratory, which includes an information acquisition module, an information processing module, and a cloud control platform.
[0056] The information acquisition module is used to periodically collect the object monitoring data of the target laboratory and transmit it to the information processing module in real time. The object monitoring data includes the monitoring data of several target objects. The target objects are determined by the management personnel according to the core management needs of the target laboratory, including but not limited to energy consumption dimensions (such as electricity consumption, renewable energy power generation, water consumption, etc.), carbon emission dimensions (such as fossil energy carbon emission data, indirect carbon emission accounting data, etc.), environmental control dimensions (such as environmental parameters such as temperature and humidity, clean area pressure difference, gas concentration, etc., and control system operation data), and experimental equipment dimensions (such as the operating status, process parameters, and energy consumption data of precision analytical instruments, pilot plants, etc.).
[0057] Core management requirements include, but are not limited to, achieving zero-carbon targets, optimizing energy consumption, controlling environmental stability, ensuring equipment operation and maintenance, and complying with regulations.
[0058] In this application, the target laboratory refers to a zero-carbon laboratory;
[0059] The information processing module is used to encrypt and compress the periodically received object monitoring data of the target laboratory. The information processing module includes a first processing unit and a second processing unit.
[0060] After receiving the periodically transmitted object monitoring data of the target laboratory, the information processing module transmits it to the first processing unit.
[0061] After receiving the periodically transmitted object monitoring data of the target laboratory, the first processing unit first converts the object monitoring data into a binary data stream. It should be noted that the object monitoring data is converted into a binary data stream because whether it is text, file, audio and video or sensor data, it will eventually be converted into a binary data stream composed of 0s and 1s and then transmitted through the network link.
[0062] Simultaneously, a mapping data table for the target laboratory is generated in real time. The generation steps are as follows:
[0063] S11: Create a 4-row, 4-column spreadsheet using pre-selected software. Fill each cell of the spreadsheet with the 16 bases of the four-bit binary number as the fill source according to a preset fill order. The fill order is based on the decimal values of the 16 bases of the binary number, which are filled into each cell of the spreadsheet in ascending order. Here, a cell is the basic unit that constitutes the spreadsheet.
[0064] In this application, the 16 base-based base-based original codes of the four-bit binary number are arranged in ascending order of their corresponding decimal values as follows: 0000, 0001, 0010, 0011, 0100, 0101, 0110, 0111, 1000, 1001, 1010, 1011, 1100, 1101, 1110, 1111;
[0065] In this application, the pre-selected software is Excel.
[0066] In this application, the 16 base numbers are used as the data source to fill the spreadsheet using a row-first principle. Starting with the first cell of the first row, all cells in the first row are filled from left to right. Then, starting with the first cell of the second row, the process continues until all rows are filled. It should be noted that during the filling process, each cell in the matrix table is filled with only one base number. The first row of the spreadsheet refers to the first row counted from top to bottom. Furthermore, each base number is filled only once.
[0067] S12: Label the 16 base codes as A0, A1, ..., A15 in the order they are filled into the cells;
[0068] S13: Determine the four-neighbor list B0 and the row and column list C0 of the base A0 based on the position of the cell filled with the base A0 in the spreadsheet:
[0069] The contents of the four neighbor list B0 of the base A0 are determined as follows:
[0070] S21: Use the list() function to create an empty list of base A0, and locate the coordinates (X1, Y1) of the cell to be filled with base A0 in the spreadsheet, where the horizontal and vertical coordinates are the row and column of the cell in the spreadsheet, respectively. In this application, the coordinates of the cell to be filled with base A0 are (1, 1).
[0071] S22: In the spreadsheet, identify all cells that are adjacent to the cell. For each cell identified, obtain the base code filled in the cell and add the base code to the list. After identifying and adding all base codes, mark the list as the four-neighbor list of base code A0 and label it as B0.
[0072] The adjacent relationships include top adjacent, bottom adjacent, left adjacent, and right adjacent. Specifically: the cell that is top adjacent to the cell is located in row X1-1 and column Y1 of the spreadsheet; the cell that is bottom adjacent to the cell is located in row X1+1 and column Y1 of the spreadsheet; the cell that is left adjacent to the cell is located in row X1 and column Y1-1 of the spreadsheet; and the cell that is right adjacent to the cell is located in row X1 and column Y1+1 of the spreadsheet.
[0073] It should be noted that there are no cells that are adjacent to the cell above or to the cell to the left in the spreadsheet. Therefore, the four-adjacent list B0 only stores the base codes filled in the cells that are adjacent to the cell to the right and to the cell below.
[0074] The contents of the row and column list C0 for the base A0 are determined as follows:
[0075] Create an empty list of base A0 using the list() function again. Identify all cells in the spreadsheet that are in the same row or column as the cell. For each cell identified, obtain the base code filled in the cell and add the base code to the list. After identifying and adding all base codes, mark the list as the row and column list of base A0 and label it C0.
[0076] In this context, "row-to-row" refers to a cell in the spreadsheet that is in the same row as the cell filled with the base A0, and "column-to-column" refers to a cell in the spreadsheet that is in the same column as the cell filled with the base A0. Specifically:
[0077] All cells that are in the same row as the cell filled with base A0 are located in row X1 of the spreadsheet, and all cells that are in the same column as the cell filled with base A0 are located in column Y1 of the spreadsheet.
[0078] It should be noted that the steps of determining the four neighbor list B0 and the row and column list C0 can be performed simultaneously. The description here of executing the row and column list C0 after the four neighbor list B0 is to reduce redundant descriptions.
[0079] It should be noted that neither the four-neighbor list B0 nor the row and column list C0 contains the base code A0.
[0080] S14: Perform the first update on row and column list C0. The update content is as follows: In row and column list C0, remove all base codes that are simultaneously contained in row and column list C0 and four neighboring lists B0 to complete the first update of row and column list C0.
[0081] S15: Determine the four neighbor lists B1, B2, ..., B15 and the row and column lists C1, C2, ..., C15 in sequence according to S13, and complete the first update of the row and column lists C1, C2, ..., C15 according to S14;
[0082] S16: Assign priorities based on the number of elements in the row and column lists of the base-based primitives A0, A1, ..., A15, with priorities starting from 1 and proceeding sequentially. A lower priority indicates fewer elements in the row and column lists of the corresponding base-based primitives. In this application, priorities 0, 1, ..., 15 correspond to base-based primitives A0, A5, A6, A1, A2, A7, A9, A10, A11, A13, A3, A4, A14, A12, A12, A15, and A8, respectively.
[0083] It should be noted here that for several base codes with the same number of elements, the values are assigned in ascending order of priority according to their marking subscripts.
[0084] S17: Following the preset removal steps, remove several elements from the row and column lists C0, C1, ..., C15 respectively to complete the second update of the row and column lists C0, C1, ..., C15. The removal steps are as follows:
[0085] S31: Perform a selection operation several times. Each time a selection operation is performed, a set of operations is obtained. Each set of operations contains one element randomly selected from the row and column lists of 16 base-based ...
[0086] S32: Mark all operation sets sequentially according to their index sums in ascending order, labeled as D1, D2, ..., Dd, where d≥1; the sum of the indices of any operation set is the sum of the indices of all elements in the operation set before they are selected in the corresponding row and column lists. If several operation sets have the same index sum, then extract the indices of the elements selected from the row and column lists corresponding to the base codes of the corresponding priorities in ascending order of priority. The smaller the index, the earlier it is marked, i.e., the index of the element selected from the row and column lists corresponding to the base codes of priority 0 is marked first.
[0087] S33: Select the first set of operations that satisfies the constraints from the operation sets D1, D2, ..., Dd according to the preset selection steps. The selection steps are as follows:
[0088] S331: Determine the verification list of operation set D1 based on base codes A0, A1, ..., A15, and determine the following: Based on each element in operation set D1, remove all elements except the selected element from the row and column list, and determine the row and column list after removal as the verification list of operation set D1 based on the base code corresponding to the row and column list.
[0089] S332: Use 256 unsigned 8-bit binary numbers to determine whether the operation set D1 satisfies the constraints. The content is as follows:
[0090] Based on each of the 256 unsigned octet binary numbers, the octet binary number is split into a sequence of the first four characters, denoted as sequence X, and a sequence of the last four characters, denoted as sequence Y. In this application, the first four characters refer to the first four characters from left to right, and the last four characters refer to the first four characters from right to left.
[0091] If there is exactly one radix A0, A1, ..., A15 whose four-neighbor list contains sequence X and whose check list contains sequence Y, then the operation set D1 is determined to satisfy the constraint, and the operation set D1 is selected as the constraint set. That is, for any unsigned 8-bit binary number, its sequences x and Y have exactly one radix A0, A1, ..., A15 whose four-neighbor list contains sequence X and whose check list contains sequence Y.
[0092] Conversely, if the operation set D1 does not meet the constraint, the operation sets D2, D3, ..., Dd are sequentially evaluated to determine whether they meet the constraint, until the first operation set that meets the constraint is found. This operation set is then selected as the constraint set. If the first operation set that meets the constraint is found, the evaluation of the remaining operation sets is stopped.
[0093] The unsigned eight-bit binary number ranges from 00000000 to 11111111, corresponding to a decimal range of 0 to 255. The calculation method is: 2^8 = 256, that is, there are 256 possibilities, with a minimum value of 0 and a maximum value of 255.
[0094] S34: Based on each element contained in the constraint combination, remove all elements except the selected element from the row and column list to complete the second update of the corresponding row and column list;
[0095] S19: Create a data table, and set up three fields in the data table: primitive code, four neighbors, and row and column. According to the primitive code of 16 bases and its four neighbors list and the row and column list after the second update, fill the primitive code field of the data table with the primitive code of 16 bases respectively. Fill the four neighbors and row and column fields with the four neighbors list and row and column list of the corresponding base primitive code respectively. After filling, mark the data table as the mapping data table of the target laboratory.
[0096] After generating the mapping data table, the first processing unit maps the binary data stream according to a preset mapping rule to obtain the first processed data of the periodic target laboratory and transmits it to the second processing unit. The mapping rule is as follows:
[0097] S41: Divide the characters in the binary data stream into groups of four, from left to right. Each group corresponds to a mapping array. According to the order of these mapping arrays in the binary data stream, they are labeled as E1, E2, ..., Ee from left to right, where e is the total number of complete groups. If the number of remaining characters in the binary data stream after division is less than four, the remaining characters are directly used as the reserved array of the binary data stream and do not participate in the group mapping.
[0098] S42: Obtain the four neighbor list and row and column list corresponding to the same base as the original code of the mapping array E1 from the original code field of the mapping data table, randomly select an element from the four neighbor list as the first element of the mapping array E1, and extract the element from the row and column list as the second element of the mapping array E1.
[0099] The first element and the second element are concatenated to obtain the encrypted sequence of the mapping array E1. During the concatenation process, the first element is at the leftmost end of the encrypted sequence. This operation can make several encrypted sequences corresponding to the same mapping array. This method can increase the difficulty of cracking the encrypted sequence and increase the complexity of the encrypted sequence.
[0100] S43: Obtain the encryption sequences of mapping arrays E2, E3, ..., Ee in sequence according to S41 to S42. Concatenate the encryption sequences of mapping arrays E1, E2, ..., Ee in the order of mapping arrays E1, E2, ..., Ee to obtain the first processed data of the periodic target laboratory. If there is a reserved array, concatenate the reserved array at the rightmost end of the first processed data.
[0101] The first processing unit transmits the first processing data of the periodic target laboratory to the second processing unit;
[0102] After receiving the first processed data of the periodic target laboratory, the second processing unit compresses the binary data stream using a pre-selected compression algorithm to obtain the second processed data of the periodic target laboratory. The second processed data is then transmitted to the cloud control platform. In this application, the pre-selected compression algorithm is the Deflate algorithm. The Deflate algorithm is a widely used lossless compression algorithm that combines the LZ77 algorithm and Huffman coding. First, the LZ77 algorithm is used to replace the repeated strings in the data with shorter symbols to generate a "text (original byte / offset + length)" sequence. Then, Huffman coding is performed on this sequence to replace the high-frequency parts with shorter forms, finally obtaining a binary data stream without gaps. Compression methods such as Zlib and Gzip are usually based on the Deflate algorithm.
[0103] The cloud-based control platform is used to restore the periodic target laboratory's object monitoring data after receiving the second-processed data. The restoration steps are as follows:
[0104] After receiving the second processed data, it is first decompressed and restored to obtain the corresponding first processed data;
[0105] Then, the same generation steps are followed to generate the mapping data table for the target laboratory;
[0106] The cutting step size is specified as 8 characters. The first processed data is cut and restored in order from left to right to obtain several encrypted sequences. Then, based on each encrypted sequence obtained by restoration, the mapping array is found according to the mapping data table. The mapping array contains elements that are consistent with the first four characters and the last four characters of the encrypted sequence in the four adjacent fields and the row and column fields, respectively.
[0107] By concatenating and restoring all the obtained mapping arrays, we can obtain the object monitoring data of the periodic target laboratory.
[0108] The monitoring data of the objects is stored and displayed to the management personnel, who then analyze it to determine whether it is necessary to control several target objects within the target laboratory to ensure that the preset operating indicators of the zero-carbon laboratory are met. The preset operating indicators include, but are not limited to, energy consumption indicators, carbon emission-related indicators, resource recycling indicators, operating efficiency indicators, and environmental compatibility indicators.
[0109] Some of the data in the above formulas are numerical calculations with dimensions removed, and the contents not described in detail in this specification are all prior art known to those skilled in the art.
[0110] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.
Claims
1. A control method based on a zero-carbon laboratory, characterized in that, Includes the following steps: Step 1: The information acquisition module periodically collects the object monitoring data of the target laboratory and transmits it to the first processing unit in real time. The object monitoring data contains monitoring data of several target objects. Step 2: After receiving the periodically transmitted object monitoring data, the first processing unit converts it into a binary data stream and generates a mapping data table of the target laboratory in real time according to the preset generation steps. Step 3: After generating the mapping data table, the first processing unit maps the binary data stream according to the preset mapping rules to obtain the first processed data of the periodic target laboratory and transmits it to the second processing unit. Step 4: After receiving the periodically transmitted first processed data, the second processing unit compresses it to obtain the periodically transmitted target laboratory second processed data, and transmits the second processed data to the cloud control platform.
2. The control method based on a zero-carbon laboratory according to claim 1, characterized in that, The steps to generate the mapping data table for the target laboratory are as follows: S11: Create a 4-row, 4-column spreadsheet using pre-selected software. Fill each cell of the spreadsheet with the 16 bases of the four-bit binary number as the fill source according to a preset fill order. The fill order is based on the decimal values of the 16 bases of the binary number, which are filled into each cell of the spreadsheet in ascending order. S12: Label the 16 base codes as A0, A1, ..., A15 in the order they are filled into the cells; S13: Determine the four-neighbor list B0 and the row and column list C0 of the cell containing the base code A0 in the spreadsheet, respectively: S14: Perform the first update on row and column list C0. The update content is as follows: In row and column list C0, remove all base codes that are simultaneously contained in row and column list C0 and four neighboring lists B0 to complete the first update of row and column list C0. S15: Determine the four neighbor lists B1, B2, ..., B15 and the row and column lists C1, C2, ..., C15 in sequence according to S13, and complete the first update of the row and column lists C1, C2, ..., C15 according to S14; S16: Extract all elements contained in the row and column list C0, C1, ..., C15 and remove duplicates. Construct a set C_all based on all remaining elements after deduplication. After construction, assign an allocation status to each element in the set C_all. There are two allocation statuses: allocated and unallocated. The default allocation status is unallocated when assigning an allocation status. S17: Assign priority based on the number of elements in the row and column lists of the base A0, A1, ..., A15, with priority starting from 1 and proceeding sequentially. The lower the priority, the fewer the number of elements in the row and column lists of the corresponding base. S18: Remove several elements from the row and column lists C0, C1, ..., C15 according to the preset removal steps to complete the second update of the row and column lists C0, C1, ..., C15; S19: Create a data table with three fields: base code, neighbor list, and row / column. Based on the 16 base ...
3. The control method based on a zero-carbon laboratory according to claim 2, characterized in that, In S11, the filling order is to fill each cell of the spreadsheet in ascending order of the decimal values of the 16 base codes. The 16 base codes of the four-bit binary numbers are 0000, 0001, 0010, 0011, 0100, 0101, 0110, 0111, 1000, 1001, 1010, 1011, 1100, 1101, 1110, and 1111.
4. The control method based on a zero-carbon laboratory according to claim 2, characterized in that, S13, determine the contents of the four neighbor list B0 of base A0 as follows: S21: Create an empty list of base A0, and locate the coordinates (X1, Y1) of the cell in the spreadsheet to be filled with base A0, where the x and y coordinates are the row and column of the cell in the spreadsheet, respectively. S22: Identify all cells that are adjacent to the cell in the spreadsheet. For each cell identified, obtain the base code filled in the cell and add the base code to the list. After identifying and adding all base codes, mark the list as the four-neighbor list of base code A0, labeled as B0. The adjacent relationship includes top adjacent, bottom adjacent, left adjacent and right adjacent.
5. The control method based on a zero-carbon laboratory according to claim 4, characterized in that, In S22, the cells that are adjacent to the cell above are located in row X1-1 and column Y1 of the spreadsheet; the cells that are adjacent to the cell below are located in row X1+1 and column Y1 of the spreadsheet; the cells that are adjacent to the cell ...
6. The control method based on a zero-carbon laboratory according to claim 2, characterized in that, S13, determine the contents of the row and column list C0 of the base A0 as follows: Create an empty list of base A0. In the spreadsheet, identify all cells that are in the same row or column as the cell. For each cell identified, obtain the base code filled in the cell and add the base code to the list. After identifying and adding all base codes, mark the list as the row and column list of base A0 and label it as C0. In this context, "row" and "column" refer to cells in the spreadsheet that are in the same row and column as the cell filled with the base A0, respectively.
7. The control method based on a zero-carbon laboratory according to claim 2, characterized in that, S18, the removal steps are as follows: S31: Perform a selection operation several times. Each time a selection operation is performed, a set of operations is obtained. Each set of operations contains one element randomly selected from the row and column lists of 16 base-based ... S32: Mark all operation sets sequentially according to the index sum of the operation sets in ascending order, labeled as D1, D2, ..., Dd, where d≥1; where the index sum of any operation set is the sum of the indices of all elements in the operation set in the corresponding row and column lists before selection; if there are several operation sets with the same index sum, then extract the index of the element selected from the row and column lists corresponding to the base code of the corresponding priority from these operation sets in ascending order of priority, with the smaller the index, the earlier it is marked; S33: Select the first set of operations that satisfies the constraints from the set of operations D1, D2, ..., Dd according to the preset selection steps, and use it as the constraint set; S34: Based on each element contained in the constraint combination, remove all elements other than the selected element from the row and column list to complete the second update of the corresponding row and column list.
8. The control method based on a zero-carbon laboratory according to claim 7, characterized in that, S33, Select the first set of operations that satisfies the constraints from the operation sets D1, D2, ..., Dd as the constraint set. The selection steps are as follows: S331: Determine the check list of operation set D1 based on base A0, A1, ..., A15; S332: Use 256 unsigned 8-bit binary numbers to determine whether the operation set D1 satisfies the constraints. The content is as follows: Based on each of the 256 unsigned octet binary numbers, the octet binary number is split into a sequence consisting of the first four characters, denoted as sequence X, and a sequence consisting of the last four characters, denoted as sequence Y. If, in base A0, A1, ..., A15, exactly one base has a four-neighbor list containing sequence X and a check list containing sequence Y, then operation set D1 is determined to satisfy the constraint, and operation set D1 is selected as the constraint set; otherwise, operation set D1 is determined not to satisfy the constraint, and operation sets D2, D3, ..., Dd are determined in the order of operation sets D1, D2, ..., Dd to satisfy the constraint, until the first operation set that satisfies the constraint appears, and that operation set is selected as the constraint set.
9. The control method based on a zero-carbon laboratory according to claim 1, characterized in that, The mapping rules for obtaining the first processed data of the periodic target laboratory are as follows: S41: Divide the characters in the binary data stream into groups of four, from left to right. Each group corresponds to a mapping array. According to the order of these mapping arrays in the binary data stream, they are labeled as E1, E2, ..., Ee from left to right, where e is the total number of groups. S42: Obtain the four neighbor list and row and column list corresponding to the same base as the original code of the mapping array E1 from the original code field of the mapping data table, randomly select an element from the four neighbor list as the first element of the mapping array E1, and extract the element from the row and column list as the second element of the mapping array E1. The first element and the second element are concatenated to obtain the encrypted sequence of the mapping array E1. During the concatenation process, the first element is at the leftmost end of the encrypted sequence. S43: Obtain the encryption sequences of mapping arrays E2, E3, ..., Ee in sequence according to S41 to S42. Then, concatenate the encryption sequences of mapping arrays E1, E2, ..., Ee in the order of mapping arrays E1, E2, ..., Ee to obtain the first processed data of the periodic target laboratory.
10. The control method based on a zero-carbon laboratory according to claim 1, characterized in that, After completing step four, the following steps also need to be completed: After receiving the second processing data of the periodic target laboratory, the cloud control platform restores it to obtain the object monitoring data of the periodic target laboratory. The object monitoring data is stored and displayed to the management personnel, who then analyze it to determine whether it is necessary to control several target objects in the target laboratory to ensure that the preset operating indicators of the zero-carbon laboratory are met.