A method and system for monitoring carbon emissions from long foundation pit projects based on the Internet of Things

Abstract

This invention provides a method and system for monitoring carbon emissions from long foundation pit projects based on the Internet of Things (IoT), relating to the field of carbon emission monitoring technology. The method includes: acquiring geological exploration data at various preset locations of the target foundation pit; acquiring real-time carbon emissions at each preset location of the target foundation pit at multiple times during a monitoring period; determining a construction difficulty coefficient based on the geological exploration data; acquiring foundation pit environmental data at each preset location of the target foundation pit; determining a foundation pit environmental impact coefficient based on the construction difficulty coefficient and the foundation pit environmental data; acquiring the expected completed construction volume at each preset location of the target foundation pit; determining the expected carbon emissions based on the foundation pit environmental impact coefficient and the expected completed construction volume; and generating a monitoring report based on the expected carbon emissions and the real-time carbon emissions. According to this invention, the accuracy of carbon emission monitoring for long foundation pit projects can be improved.

Description

Technical Field

[0001] This invention relates to the field of carbon emission monitoring technology, and in particular to a method and system for monitoring carbon emissions from long foundation pit projects based on the Internet of Things. Background Technology

[0002] In related technologies, carbon emissions from long foundation pits can be monitored by collecting relevant data through sensors and combining it with manual monitoring by professionals. In other words, it mainly relies on human factors. Over-reliance on human factors may make it difficult to guarantee the accuracy of carbon emission monitoring, and it is impossible to conduct zoned monitoring of different areas of long foundation pits.

[0003] The information disclosed in the background section of this application is intended only to enhance the understanding of the general background of this application and should not be construed as an admission or in any way implying that the information constitutes prior art known to those skilled in the art. Summary of the Invention

[0004] This invention provides a method and system for monitoring carbon emissions in long foundation pit projects based on the Internet of Things, which can solve the technical problems that related technologies cannot guarantee the accuracy of carbon emission monitoring and cannot perform zoned monitoring of different areas of long foundation pits.

[0005] According to a first aspect of the present invention, a method for monitoring carbon emissions from long foundation pit projects based on the Internet of Things is provided, comprising: acquiring geological exploration data at various preset locations of the target foundation pit; acquiring real-time carbon emissions at various preset locations of the target foundation pit at multiple times during a monitoring period; determining a construction difficulty coefficient based on the geological exploration data; acquiring foundation pit environmental data at various preset locations of the target foundation pit, wherein the foundation pit environmental data includes: foundation pit rainfall data and foundation pit wind speed data; determining a foundation pit environmental impact coefficient based on the construction difficulty coefficient and the foundation pit environmental data; acquiring the expected completed construction volume at various preset locations of the target foundation pit; determining the expected carbon emissions based on the foundation pit environmental impact coefficient and the expected completed construction volume; and generating a monitoring report based on the expected carbon emissions and the real-time carbon emissions.

[0006] According to the present invention, determining the construction difficulty coefficient based on the geological exploration data includes: determining the uniaxial compressive strength, standard penetration test blow count, and rock quality index based on the geological exploration data; determining the soft soil identification result, hard soil identification result, and extremely hard soil identification result based on the standard penetration test blow count; determining the soil layer strength identification result based on the soft soil identification result, the hard soil identification result, and the extremely hard soil identification result; and determining the construction difficulty coefficient based on the uniaxial compressive strength, the rock quality index, and the soil layer strength identification result.

[0007] According to the present invention, determining the soft soil identification result, hard soil identification result, and extremely hard soil identification result based on the standard penetration test blow count includes: if the standard penetration test blow count is less than a first preset test blow count threshold, the soft soil identification result is 1; if the standard penetration test blow count is greater than or equal to the first preset test blow count threshold and less than or equal to a second preset test blow count threshold, the hard soil identification result is 2; if the standard penetration test blow count is greater than the second preset test blow count threshold, the extremely hard soil identification result is 3.

[0008] According to the present invention, the construction difficulty coefficient is determined based on the uniaxial compressive strength, the rock quality index, and the soil layer strength identification result, including: according to the formula: Determine the construction difficulty coefficient at the i-th preset location of the target foundation pit. ,in, The soil strength identification result at the i-th preset location of the target foundation pit. Let be the uniaxial compressive strength at the i-th preset location of the target foundation pit. To preset the uniaxial compressive strength threshold, Let be the rock quality index at the i-th preset location of the target foundation pit. This is a preset threshold for rock quality indicators.

[0009] According to the present invention, determining the environmental impact coefficient of a foundation pit based on the construction difficulty coefficient and the foundation pit environmental data includes: acquiring historical geological exploration data, historical foundation pit environmental data, historical carbon emissions, and historical construction records at various historical preset locations during multiple historical construction cycles, wherein the historical foundation pit environmental data includes historical foundation pit rainfall data and historical foundation pit wind speed data; determining the historical construction volume based on the historical construction records; determining the historical construction difficulty coefficient based on the historical geological exploration data; determining a first relational function based on the historical construction difficulty coefficient, the historical foundation pit environmental data, the historical carbon emissions, and the historical construction volume; and determining the environmental impact coefficient of the foundation pit based on the construction difficulty coefficient, the first relational function, and the foundation pit environmental data.

[0010] According to the present invention, determining the historical construction volume based on the historical construction records includes: establishing a historical 3D information model of the historical target foundation pit in multiple historical construction cycles; establishing a historical 4D information model based on the historical 3D information model and the historical construction records; determining the historical construction process based on the historical 4D information model; and determining the historical construction volume based on the historical construction process.

[0011] According to the present invention, a first relational function is determined based on the historical construction difficulty coefficient, the historical foundation pit environmental data, the historical carbon emissions, and the historical construction volume, including: according to the formula: Determine the equation to be fitted for the first relational function, where, This represents the historical carbon emissions at the j-th historical preset location during the k-th historical construction cycle. To preset carbon emission thresholds, This represents the historical construction volume at the j-th historical preset location during the k-th historical construction cycle. This refers to the historical rainfall data of the foundation pit at the j-th historical preset location during the k-th historical construction cycle. To preset the rainfall data threshold, This refers to the historical wind speed data of the foundation pit at the j-th historical preset location during the k-th historical construction cycle. To preset the wind speed data threshold, The historical construction difficulty coefficient is the historical construction location at the j-th historical preset position in the k-th historical construction cycle. , , , , , and The coefficients to be fitted are: Based on the historical foundation pit environmental data, the historical carbon emissions, and the historical construction volume, the solution values ​​of the coefficients to be fitted are obtained; Based on the solution values ​​of the coefficients to be fitted and the equation to be fitted, the first relationship function is obtained.

[0012] According to a second aspect of the present invention, an Internet of Things-based carbon emission monitoring system for long foundation pit projects is provided, comprising: a geological data system for acquiring geological exploration data at various preset locations of the target foundation pit; a real-time data system for acquiring real-time carbon emissions at various preset locations of the target foundation pit at multiple times during a monitoring period; a difficulty coefficient system for determining a construction difficulty coefficient based on the geological exploration data; an environmental data system for acquiring foundation pit environmental data at various preset locations of the target foundation pit, wherein the foundation pit environmental data includes: foundation pit rainfall data and foundation pit wind speed data; an impact coefficient system for determining a foundation pit environmental impact coefficient based on the construction difficulty coefficient and the foundation pit environmental data; an expected construction system for acquiring the expected completed construction volume at various preset locations of the target foundation pit; an expected emission system for determining the expected carbon emissions based on the foundation pit environmental impact coefficient and the expected completed construction volume; and a monitoring report system for generating a monitoring report based on the expected carbon emissions and the real-time carbon emissions.

[0013] Technical Effects: According to this invention, based on geological exploration data, the construction difficulty is accurately analyzed, and the construction difficulty coefficient is determined. Furthermore, based on the construction difficulty coefficients, pit environmental data, and expected construction volume at each preset location of the target foundation pit, the expected carbon emissions at each preset location can be determined, enabling zoned monitoring of carbon emissions at each preset location and improving the accuracy of carbon emission monitoring for long foundation pit projects. When determining the construction difficulty coefficient, it can be determined based on uniaxial compressive strength, rock quality indicators, and soil strength identification results. During the calculation process, the construction difficulty can be assessed from three aspects: soil strength, rock hardness, and rock integrity, thus determining the construction difficulty coefficient and providing comprehensiveness and accuracy. When determining the first relationship function, it can be determined based on historical construction difficulty coefficients, historical foundation pit environmental data, historical carbon emissions, and historical construction volume, accurately describing the impact of construction difficulty and the foundation pit environment on the historical carbon emissions per unit of construction volume, improving the accuracy and objectivity of the first relationship function.

[0014] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only, and are not intended to limit the invention. Other features and aspects of the invention will become clearer from the following detailed description of exemplary embodiments with reference to the accompanying drawings. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other embodiments can be obtained based on these drawings without creative effort.

[0016] Figure 1 An exemplary flowchart illustrates a method for monitoring carbon emissions from long foundation pit projects based on the Internet of Things, according to an embodiment of the present invention.

[0017] Figure 2 An exemplary schematic diagram illustrating the determination of the construction difficulty coefficient according to an embodiment of the present invention is shown;

[0018] Figure 3 An exemplary schematic diagram illustrating the determination of the environmental impact coefficient of a foundation pit according to an embodiment of the present invention is shown;

[0019] Figure 4 A block diagram of an Internet of Things-based carbon emission monitoring system for long foundation pit projects according to an embodiment of the present invention is shown as an example. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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.

[0021] The technical solution of the present invention will be described in detail below with reference to specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0022] Figure 1 An exemplary flowchart illustrates a method for monitoring carbon emissions from long foundation pit projects based on the Internet of Things (IoT) according to an embodiment of the present invention. The method includes: Step S1, acquiring geological exploration data at various preset locations of the target foundation pit; Step S2, acquiring real-time carbon emissions at various preset locations of the target foundation pit at multiple times during a monitoring period; Step S3, determining a construction difficulty coefficient based on the geological exploration data; Step S4, acquiring foundation pit environmental data at various preset locations of the target foundation pit, wherein the foundation pit environmental data includes: foundation pit rainfall data and foundation pit wind speed data; Step S5, determining a foundation pit environmental impact coefficient based on the construction difficulty coefficient and the foundation pit environmental data; Step S6, acquiring the expected completed construction volume at various preset locations of the target foundation pit; Step S7, determining the expected carbon emissions based on the foundation pit environmental impact coefficient and the expected completed construction volume; Step S8, generating a monitoring report based on the expected carbon emissions and the real-time carbon emissions.

[0023] According to an embodiment of the present invention, the Internet of Things-based carbon emission monitoring method for long foundation pit projects can accurately analyze the construction difficulty based on geological exploration data, determine the construction difficulty coefficient, and further, formulate the expected carbon emission of each preset location based on the construction difficulty coefficient of each preset location of the target foundation pit, foundation pit environmental data, and expected construction volume, thereby realizing zoned monitoring of carbon emissions at each preset location and improving the accuracy of carbon emission monitoring for long foundation pit projects.

[0024] According to one embodiment of the present invention, in step S1, geological exploration data at each preset location of the target foundation pit is obtained.

[0025] For example, the target foundation pit is divided into multiple areas, and a sampling point is set in each area, i.e., a preset location, to obtain geological exploration data at the preset location, such as the uniaxial compressive strength of the rock, the standard penetration test blow count, and the rock quality index.

[0026] According to one embodiment of the present invention, in step S2, the real-time carbon emissions at each preset location of the target foundation pit are obtained at multiple moments during the monitoring period.

[0027] For example, the real-time carbon emissions at each preset location of the target foundation pit are the real-time carbon emissions of each area of ​​the target foundation pit. The equipment used and the electricity used in each area are determined. Based on the emission factor model, the carbon emissions of each type of equipment are calculated. That is, the carbon emissions of the equipment are determined by multiplying the fuel consumption of the equipment by the emission factor. The emission factor of electricity is 0.96 kg per kilowatt-hour. The carbon emissions of the electricity used in each area are calculated based on the emission factor of the electricity. The carbon emissions of the equipment and the carbon emissions of the electricity used are summed to obtain the real-time carbon emissions at each preset location of the target foundation pit.

[0028] According to one embodiment of the present invention, in step S3, the construction difficulty coefficient is determined based on the geological exploration data.

[0029] Figure 2 An exemplary schematic diagram illustrating the determination of the construction difficulty coefficient according to an embodiment of the present invention is shown.

[0030] According to an embodiment of the present invention, step S3 includes: step S31, determining the uniaxial compressive strength, standard penetration test blow count, and rock quality index based on the geological exploration data; step S32, determining the soft soil identification result, hard soil identification result, and extremely hard soil identification result based on the standard penetration test blow count; step S33, determining the soil layer strength identification result based on the soft soil identification result, the hard soil identification result, and the extremely hard soil identification result; and step S34, determining the construction difficulty coefficient based on the uniaxial compressive strength, the rock quality index, and the soil layer strength identification result.

[0031] For example, complete rock core samples from various predetermined locations in the target foundation pit are tested in the laboratory using a pressure machine to obtain uniaxial compressive strength. A standard penetrator (SPT) is driven 30 cm into the soil by a free-falling hammer of a certain mass from a certain height to obtain the number of blows required. The ratio of the total length of complete rock core segments longer than 10 cm to the drilling depth of that run is expressed as a percentage to obtain the rock quality index. The higher the rock quality index, the higher the rock mass strength. Based on the SPT blow count, the soil density and strength of the target area are determined, identifying soft soil, hard soil, and extremely hard soil. The soil strength identification result is determined by summing the soft soil, hard soil, and extremely hard soil identification results. The higher the soil strength identification result, the greater the soil density and strength at the predetermined location, and the higher the construction difficulty. Based on the uniaxial compressive strength, rock quality index, and soil strength identification results, the overall construction difficulty at each predetermined location is assessed, and the construction difficulty coefficient is determined.

[0032] According to an embodiment of the present invention, step S32 includes: step S321, if the standard penetration test blow count is less than a first preset test blow count threshold, the soft soil identification result is 1; step S322, if the standard penetration test blow count is greater than or equal to the first preset test blow count threshold and less than or equal to a second preset test blow count threshold, the hard soil identification result is 2; step S323, if the standard penetration test blow count is greater than the second preset test blow count threshold, the extremely hard soil identification result is 3.

[0033] For example, if the standard penetration test (SPT) blow count is less than the first preset test blow count threshold (which can be set to 4 blows), it means that the penetrometer can be easily driven into the soil layer at the preset location after hammering, and the soil layer is soft soil (e.g., clay, silt). The soft soil identification result is 1. If it is not less than the first preset test blow count threshold, the soft soil identification result is 0. If the SPT blow count is greater than or equal to the first preset test blow count threshold and less than or equal to the second preset test blow count threshold (which can be set to 50 blows), it means that the soil layer at the preset location is hard soil (e.g., dense sand, stiff plastic clay). The hard soil identification result is 2. If the SPT blow count is not within the above range, the hard soil identification result is 0. If the SPT blow count is greater than the second preset test blow count threshold, it means that the soil layer at the preset location is soft rock or extremely hard soil. The extremely hard soil identification result is 3. If the SPT blow count is not within the above range, the extremely hard soil identification result is 0.

[0034] According to an embodiment of the present invention, step S34 includes: determining the construction difficulty coefficient at the i-th preset location of the target foundation pit according to formula (1). ,

[0035] (1)

[0036] in, The soil strength identification result at the i-th preset location of the target foundation pit. Let be the uniaxial compressive strength at the i-th preset location of the target foundation pit. To preset the uniaxial compressive strength threshold, Let be the rock quality index at the i-th preset location of the target foundation pit. This is a preset threshold for rock quality indicators.

[0037] According to one embodiment of the present invention, The soil strength identification result at the i-th preset location of the target foundation pit is the soil layer strength identification result. The larger the soil layer strength identification result, the greater the soil density and strength at the preset location, and the greater the construction difficulty. This is the relative difference between the uniaxial compressive strength at the i-th preset location of the target foundation pit and a preset uniaxial compressive strength threshold. The larger this ratio, the greater the uniaxial compressive strength at the i-th preset location of the target foundation pit. The uniaxial compressive strength of soft rock is generally between 5 MPa and 30 MPa (e.g., strongly weathered rock, mudstone), while that of moderately weathered or slightly weathered granite, limestone, is generally greater than 30 MPa. The greater the uniaxial compressive strength, the harder the rock and the greater the construction difficulty. It can be set to 30MPa; The ratio is the relative difference between the rock quality index at the i-th preset location of the target foundation pit and the preset rock quality index threshold. The larger the ratio, the larger the rock quality index at the i-th preset location of the target foundation pit. The larger the rock quality index, the more intact the rock mass and the greater the construction difficulty. The preset rock quality index threshold can be set to 50%.

[0038] According to one embodiment of the present invention, The construction difficulty coefficient is determined based on three aspects: soil strength, rock hardness, and rock integrity.

[0039] In this way, the construction difficulty coefficient can be determined based on the identification results of uniaxial compressive strength, rock quality indicators, and soil strength. During the calculation process, the construction difficulty can be assessed from three aspects: soil strength, rock hardness, and rock integrity, thus determining the construction difficulty coefficient and providing comprehensiveness and accuracy of the construction difficulty coefficient.

[0040] According to an embodiment of the present invention, in step S4, environmental data of the foundation pit at each preset location of the target foundation pit is obtained, wherein the environmental data of the foundation pit includes: foundation pit rainfall data and foundation pit wind speed data.

[0041] For example, rainfall and wind speed data of the foundation pit can be obtained by setting rainfall sensors and wind speed sensors at various preset locations in the target foundation pit.

[0042] According to one embodiment of the present invention, in step S5, the environmental impact coefficient of the foundation pit is determined based on the construction difficulty coefficient and the foundation pit environmental data.

[0043] Figure 3 An exemplary schematic diagram illustrating the determination of the environmental impact coefficient of a foundation pit according to an embodiment of the present invention is shown.

[0044] According to an embodiment of the present invention, step S5 includes: step S51, acquiring historical geological exploration data, historical foundation pit environmental data, historical carbon emissions, and historical construction records for each historical preset location in multiple historical construction cycles, wherein the historical foundation pit environmental data includes historical foundation pit rainfall data and historical foundation pit wind speed data; step S52, determining the historical construction volume based on the historical construction records; step S53, determining the historical construction difficulty coefficient based on the historical geological exploration data; step S54, determining a first relationship function based on the historical construction difficulty coefficient, the historical foundation pit environmental data, the historical carbon emissions, and the historical construction volume; and step S55, determining the foundation pit environmental impact coefficient based on the construction difficulty coefficient, the first relationship function, and the foundation pit environmental data.

[0045] For example, acquire historical geological exploration data, historical foundation pit environmental data, historical carbon emissions, and historical construction records for each historical preset location of other long foundation pits that have been completed (i.e., historical target foundation pits) during the historical construction cycle; based on the historical construction records, determine the historical construction volume for each historical preset location of other long foundation pits during each historical construction cycle; based on the historical geological exploration data, determine the historical construction difficulty coefficient, which is determined in a similar way to the construction difficulty coefficient and will not be elaborated here; carbon emissions are related to construction difficulty, foundation pit environment, and construction volume to a certain extent. For example, the larger the construction volume, the larger the carbon emissions. Based on the correlation of the above data, determine the first relationship function between the historical construction difficulty coefficient, historical foundation pit environmental data, historical carbon emissions, and historical construction volume; substitute the construction difficulty coefficient and foundation pit environmental data into the first relationship function to determine the carbon emissions per unit of construction volume, i.e., the foundation pit environmental impact coefficient. The larger the foundation pit environmental impact coefficient, the greater the carbon emissions consumed to complete a unit of construction volume.

[0046] According to an embodiment of the present invention, step S52 includes: step S521, establishing a historical 3D information model of the historical target foundation pit in multiple historical construction cycles; step S522, establishing a historical 4D information model based on the historical 3D information model and the historical construction records; step S523, determining the historical construction progress based on the historical 4D information model; and step S524, determining the historical construction volume based on the historical construction progress.

[0047] For example, based on the construction drawings of the historical target foundation pit, a BIM model of the historical target foundation pit is established, i.e., a historical 3D information model; based on historical construction records, the historical construction schedule is determined, and the historical 3D information model and the historical construction schedule are linked to establish a historical 4D information model. In the historical 4D information model, the completion progress of each construction project can be intuitively obtained, such as the volume of excavated earth. Based on the historical 4D information model, the historical construction process is determined, such as obtaining the volume of excavated earth at each historical preset location in each historical construction cycle; based on the historical construction process, the historical construction volume is determined, such as determining the earth volume ratio based on the ratio of the volume of excavated earth to the preset earth volume threshold, and determining the historical construction volume at each historical preset location in each historical construction cycle based on the earth volume ratio, where the preset earth volume threshold is 1 cubic meter.

[0048] According to an embodiment of the present invention, step S54 includes: determining the equation to be fitted for the first relational function according to formula (2).

[0049] (2)

[0050] in, This represents the historical carbon emissions at the j-th historical preset location during the k-th historical construction cycle. To preset carbon emission thresholds, This represents the historical construction volume at the j-th historical preset location during the k-th historical construction cycle. This refers to the historical rainfall data of the foundation pit at the j-th historical preset location during the k-th historical construction cycle. To preset the rainfall data threshold, This refers to the historical wind speed data of the foundation pit at the j-th historical preset location during the k-th historical construction cycle. To preset the wind speed data threshold, The historical construction difficulty coefficient is the historical construction location at the j-th historical preset position in the k-th historical construction cycle. , , , , , and The coefficients to be fitted are: Based on the historical foundation pit environmental data, the historical carbon emissions, and the historical construction volume, the solution values ​​of the coefficients to be fitted are obtained; Based on the solution values ​​of the coefficients to be fitted and the equation to be fitted, the first relationship function is obtained.

[0051] According to one embodiment of the present invention, This is the ratio of the historical carbon emissions at the j-th historical preset location during the k-th historical construction cycle to the preset carbon emission threshold. The preset carbon emission threshold can be set to 1 kg. This represents dimensionless historical carbon emission data. This is the ratio of historical carbon emission data to the historical construction volume at the j-th historical preset position in the k-th historical construction cycle (the historical construction volume is also dimensionless data), representing the historical carbon emission per unit of construction volume. This is the ratio of the historical rainfall data of the foundation pit at the j-th historical preset location during the k-th historical construction cycle to the preset rainfall data threshold. The preset rainfall data threshold can be set to 1 mm. This represents dimensionless historical rainfall data for foundation pits. This indicates a positive correlation between historical carbon emissions per unit of construction work and historical rainfall data related to the foundation pit. For example, the greater the rainfall, the more rainwater flows into the foundation pit. To remove this water and prevent flooding, additional drainage pumps need to be started and the operating time of existing dewatering pumps extended. This leads to a sharp increase in the total power consumption of the foundation pit, resulting in a significant increase in carbon emissions during that period. The higher the historical carbon emissions per unit of construction work, the greater the carbon emissions. This is the ratio of the historical wind speed data of the foundation pit at the j-th historical preset location during the k-th historical construction cycle to the preset wind speed data threshold. The preset wind speed data threshold can be set to 1 m / s. This is dimensionless historical wind speed data for foundation pits. This indicates a positive correlation between historical carbon emissions per unit of construction work and historical wind speed data for foundation pits. For example, higher wind speeds make bare soil and material piles more prone to dust generation. To meet environmental protection requirements, construction companies must increase the intensity and frequency of water spraying and mist cannon spraying. Spraying systems and mist cannons are energy-consuming equipment, and their operating time is positively correlated with wind speed; the higher the historical carbon emissions per unit of construction work, the greater the carbon emissions. This indicates a positive correlation between the historical carbon emissions per unit of construction volume and the historical construction difficulty coefficient. For example, the higher the historical construction difficulty coefficient, the greater the amount of fuel consumed to excavate the same unit of earthwork, and the greater the historical carbon emissions per unit of construction volume. Based on the above relationship, the equation to be fitted for the first relationship function can be obtained.

[0052] According to one embodiment of the present invention, fitting can be performed based on multiple parameters involved in the above-mentioned equation to be fitted, that is, fitting is performed based on historical construction difficulty coefficients, historical foundation pit environmental data, historical carbon emissions, and historical construction volume to solve for the above-mentioned multiple coefficients to be fitted. There are 7 coefficients to be fitted, namely, , , , , , and Based on the historical construction difficulty coefficient, historical foundation pit environmental data, historical carbon emissions, and historical construction volume in at least seven historical construction cycles, the above seven fitting coefficients are solved to obtain the solution values ​​of the above seven fitting coefficients. The solution values ​​of the above seven fitting coefficients are then substituted into the fitting equation to determine the first relationship function.

[0053] In this way, the first relationship function can be determined based on historical construction difficulty coefficients, historical foundation pit environmental data, historical carbon emissions, and historical construction volume. This accurately describes the impact of construction difficulty and foundation pit environment on the historical carbon emissions per unit of construction volume, thus improving the accuracy and objectivity of the first relationship function.

[0054] According to one embodiment of the present invention, in step S6, the expected amount of construction work to be completed at each preset location of the target foundation pit is obtained.

[0055] For example, according to the construction plan, the expected completed construction volume at each preset location of the target foundation pit is obtained. For instance, if the expected completed construction volume at the first preset location in the current monitoring cycle is 200 cubic meters of earthwork excavation, then referring to the method for determining historical construction volume, the expected completed construction volume at the first preset location in the current construction cycle is 200.

[0056] According to one embodiment of the present invention, in step S7, the expected carbon emissions are determined based on the environmental impact coefficient of the foundation pit and the expected amount of construction to be completed.

[0057] For example, the expected carbon emissions can be determined by multiplying the environmental impact coefficient of the foundation pit by the expected amount of construction work to be completed.

[0058] According to one embodiment of the present invention, in step S8, a monitoring report is generated based on the expected carbon emissions and the real-time carbon emissions.

[0059] For example, if the real-time carbon emissions exceed the expected carbon emissions, it indicates that the real-time carbon emissions are exceeding the standard, prompting staff to check whether there is any waste of resources.

[0060] According to an embodiment of the present invention, the method for monitoring carbon emissions from long foundation pit projects based on the Internet of Things accurately analyzes the construction difficulty based on geological exploration data, determines the construction difficulty coefficient, and further, formulates the expected carbon emissions for each preset location based on the construction difficulty coefficient, foundation pit environmental data, and expected completed construction volume, thereby achieving zoned monitoring of carbon emissions at each preset location and improving the accuracy of carbon emission monitoring for long foundation pit projects. When determining the construction difficulty coefficient, it can be determined based on uniaxial compressive strength, rock quality indicators, and soil strength identification results. During the calculation process, the construction difficulty can be assessed through three aspects: soil strength, rock hardness, and rock integrity, providing comprehensiveness and accuracy for determining the construction difficulty coefficient. When determining the first relationship function, it can be determined based on historical construction difficulty coefficients, historical foundation pit environmental data, historical carbon emissions, and historical construction volume, accurately describing the impact of construction difficulty and foundation pit environment on the historical carbon emissions per unit of construction volume, thus improving the accuracy and objectivity of the first relationship function.

[0061] Figure 4 An exemplary block diagram of a long foundation pit carbon emission monitoring system based on the Internet of Things (IoT) according to an embodiment of the present invention is shown. The system includes: a geological data system for acquiring geological exploration data at various preset locations of the target foundation pit; a real-time data system for acquiring real-time carbon emissions at various preset locations of the target foundation pit at multiple times during a monitoring period; a difficulty coefficient system for determining a construction difficulty coefficient based on the geological exploration data; an environmental data system for acquiring foundation pit environmental data at various preset locations of the target foundation pit, wherein the foundation pit environmental data includes: foundation pit rainfall data and foundation pit wind speed data; an impact coefficient system for determining a foundation pit environmental impact coefficient based on the construction difficulty coefficient and the foundation pit environmental data; an expected construction system for acquiring the expected completed construction volume at various preset locations of the target foundation pit; an expected emission system for determining the expected carbon emissions based on the foundation pit environmental impact coefficient and the expected completed construction volume; and a monitoring report system for generating a monitoring report based on the expected carbon emissions and the real-time carbon emissions.

[0062] This invention can be a method, apparatus, system, and / or computer program product. The computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for performing various aspects of the invention.

[0063] Those skilled in the art should understand that the embodiments of the present invention described above and shown in the accompanying drawings are merely examples and do not limit the present invention. The objectives of the present invention have been fully and effectively achieved. The functions and structural principles of the present invention have been demonstrated and explained in the embodiments, and any variations or modifications may be made to the implementation of the present invention without departing from the stated principles.

Claims

1. A long and large foundation pit engineering carbon emission monitoring method based on Internet of Things, characterized by, The method comprises: obtaining geological exploration data at each preset position of a target foundation pit; at multiple time points in a monitoring period, obtaining real-time carbon emissions at each preset position of the target foundation pit; determining a construction difficulty coefficient according to the geological exploration data; obtaining foundation pit environment data at each preset position of a target foundation pit, wherein the foundation pit environment data comprises: foundation pit rainfall data and foundation pit wind speed data; determining a foundation pit environment influence coefficient according to the construction difficulty coefficient and the foundation pit environment data; obtaining an expected completed construction amount at each preset position of the target foundation pit; determining an expected carbon emission amount according to the foundation pit environment influence coefficient and the expected completed construction amount; generating a monitoring report according to the expected carbon emission amount and the real-time carbon emission amount; determining a construction difficulty coefficient according to the geological exploration data, comprising: determining uniaxial compressive strength, standard penetration test blow counts and rock mass index according to the geological exploration data; determining soft soil identification results, hard soil identification results and extremely hard soil identification results according to the standard penetration test blow counts; determining soil layer strength identification results according to the soft soil identification results, the hard soil identification results and the extremely hard soil identification results; determining a construction difficulty coefficient according to the uniaxial compressive strength, the rock mass index and the soil layer strength identification results; determining a foundation pit environment influence coefficient according to the construction difficulty coefficient and the foundation pit environment data, comprising: obtaining historical geological exploration data, historical foundation pit environment data, historical carbon emission amounts and historical construction records at each historical preset position in a plurality of historical construction periods, wherein the historical foundation pit environment data comprises: historical foundation pit rainfall data and historical foundation pit wind speed data; determining historical construction amounts according to the historical construction records; determining historical construction difficulty coefficients according to the historical geological exploration data; determining a first relationship function according to the historical construction difficulty coefficients, the historical foundation pit environment data, the historical carbon emission amounts and the historical construction amounts; determining a foundation pit environment influence coefficient according to the construction difficulty coefficient, the first relationship function and the foundation pit environment data; determining a first relationship function according to the historical construction difficulty coefficients, the historical foundation pit environment data, the historical carbon emission amounts and the historical construction amounts, comprising: determining a fitting equation of the first relationship function according to the formula: determining a fitting equation of the first relationship function, is a historical carbon emission amount at a jth historical preset position of a kth historical construction period, is a preset carbon emission amount threshold, is a historical construction amount at a jth historical preset position of a kth historical construction period, the historical construction amount being determined according to a ratio of a volume of excavated earthwork to a preset earthwork volume threshold, is historical foundation pit rainfall data at a jth historical preset position of a kth historical construction period, is a preset rainfall data threshold, is historical foundation pit wind speed data at a jth historical preset position of a kth historical construction period, is a preset wind speed data threshold, a historical construction difficulty coefficient at a jth historical preset position in a kth historical construction period, 、 、 、 、 、 and is a to-be-fitted coefficient; a solution value of the to-be-fitted coefficient is obtained according to the historical foundation pit environment data, the historical carbon emission and the historical construction amount; a first relationship function is obtained according to the solution value of the to-be-fitted coefficient and the to-be-fitted equation. 2.The Internet of Things based long and large foundation pit engineering carbon emission monitoring method according to claim 1, characterized in that, determining a soft soil identification result, a hard soil identification result, and an extremely hard soil identification result according to the standard penetration test blows, including: if the standard penetration test blows are less than a first preset test blow threshold, the soft soil identification result is 1; if the standard penetration test blows are greater than or equal to the first preset test blow threshold and less than or equal to a second preset test blow threshold, the hard soil identification result is 2; if the standard penetration test blows are greater than the second preset test blow threshold, the extremely hard soil identification result is 3. 3.The Internet of Things based long and large foundation pit engineering carbon emission monitoring method according to claim 1, characterized in that, According to the uniaxial compressive strength, the rock mass index and the soil layer strength identification result, a construction difficulty coefficient is determined, including: according to the formula: determining the construction difficulty coefficient at the ith preset position of the target foundation pit , wherein, is the soil layer strength identification result at the ith preset position of the target foundation pit, is the uniaxial compressive strength at the ith preset position of the target foundation pit, is a preset uniaxial compressive strength threshold, is the rock mass index at the ith preset position of the target foundation pit, is a preset rock mass index threshold. 4.The Internet of Things based long and large foundation pit engineering carbon emission monitoring method according to claim 1, characterized in that, determining a historical construction amount according to the historical construction records, including: establishing a historical 3D information model of the historical target foundation pit in multiple historical construction periods; establishing a historical 4D information model according to the historical 3D information model and the historical construction records; determining a historical construction progress according to the historical 4D information model; determining a historical construction amount according to the historical construction progress.

5. A long and large foundation pit engineering carbon emission monitoring system based on Internet of Things, used for executing the method of any one of claims 1-4, characterized in that, The method comprises: a geological data system for obtaining geological exploration data at each preset position of a target foundation pit; a real-time data system for obtaining real-time carbon emissions at each preset position of the target foundation pit at multiple time points in a monitoring period; a difficulty coefficient system for determining a construction difficulty coefficient according to the geological exploration data; an environmental data system for obtaining foundation pit environmental data at each preset position of the target foundation pit, wherein the foundation pit environmental data includes foundation pit rainfall data and foundation pit wind speed data; an influence coefficient system for determining a foundation pit environmental influence coefficient according to the construction difficulty coefficient and the foundation pit environmental data; an expected construction system for obtaining an expected completed construction amount at each preset position of the target foundation pit; an expected emission system for determining an expected carbon emission amount according to the foundation pit environmental influence coefficient and the expected completed construction amount; a monitoring report system for generating a monitoring report according to the expected carbon emission amount and the real-time carbon emission amount.

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