AU2021102807A4 - A device and method to improve the efficiency of construction sites using iot enabled digital twins - Google Patents
A device and method to improve the efficiency of construction sites using iot enabled digital twins Download PDFInfo
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Abstract
TITLE: "A DEVICE AND METHOD TO IMPROVE THE EFFICIENCY
OF CONSTRUCTION SITES USING IOT ENABLED DIGITAL TWINS"
5 7. ABSTRACT
A digital twin system to improve the efficiency of a construction site is disclosed.
The system includes an application for twinning of construction sites, a Field
Programmable Gate Array (FPGA) based internet of things (IoT) sensor interface
called nodules. The nodules include a plurality of sensor modules and
10 communication equipment, pluggable to any system with a need for minimum
interfacing. The nodules are interfaced directly with a signal filtering unit, combines
with an ADC unit along with an ALU to process the sensed data. The unit comprises
of multiplexers used to combine data from different sensors into a single
multiplexed channel, wherein the FPGA device sends relevant signals to these
15 devices in order to get the final values from the ADC wherein the values are
processed to generate actuation signals. The said signals are used to modify the
display data, control the connected actuators.
Figure associated with Abstract is Fig.1
20
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Description
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Title of the Invention
Technical Field of the Invention
[001] Present invention relates to a computer implemented method and a system for data collection in industrial environments. More particularly, to a method and system leveraging collected data for monitoring, remote control, autonomous action, and the like activities in industrial environments.
Background of the Invention
[002] From the early history of development, there has been a requirement for exhaustive data backing of the development measures. Notwithstanding the information trade innovation, which has changed since the beginning, engineers have strived for the most organized and organized undertaking documentation conceivable. As of not long ago, the emphasis was basically on tending to the innovative difficulties of plan, like how to most efficiently gather and present information before the "primary digging tool", particularly considering the streamlining of the development cycle. These endeavors are, obviously, supported and still important, however inventors of the present invention, concentrated on the cycles that follow the actual development.
[003] Inventors are tending to innovative inquiries as well as featuring difficulties confronting the development business from an entire other point of view, that is, the biological and financial effects of development works, particularly as far as the Circular Economy (CE) worldview. Development, Digitalisation, CE, and SRM. Shutting material circles through reusing constantly materials in asset concentrated ventures is getting increasingly more significant even with progressively severe ecological prerequisites and the requirement for environmental change moderation by and large.
[004] Correspondingly, the European Union is progressively perceiving qualities that harmonize with the change from direct plans of action to CE. Albeit broad endeavors to advance the advantages of CE, just as authoritative and monetary recreations, are being set up, the measure of material being reused a lot as SRM is a long way from ideal. This is particularly obvious in customarily more traditionalist areas, like the development business. The fundamental deterrents for execution are, regulative, social, sectoral, and monetary-driven basically by the bounty and ease of virgin materials.
[005] Shockingly, this harmonizes with the way that the development business is perhaps the biggest buyer of raw materials. That being said, CE models can be helpful, particularly for structural designing undertakings, where a monstrous measure of material is required. In Europe, an aggregate of 6,265,212 km of streets existed in 2016. The complete expenses of the whole street network were equivalent to around 184 billion EUR in 2016 with speculation expenses of ca. 145.5 billion EUR and operational and upkeep expenses of 38.3 billion EUR. This is assessed to be 1.2% of the yearly GDP in the EU. 226.8 million tons of black-top was delivered in 2016 for street development and recovery and around 0.6 billion tons of total.
[006] Taking into account that 12% of all total is presently being reused constantly and that up to 100% of black-top could be recovered in the EU, which practically speaking is significant, these numbers show that there is an enormous potential for diminishing ecological and financial effects of street development and structural designing works overall by utilizing SRM and consequently forestalling the consumption of regular materials and shortening transport distances by utilizing locally accessible SRM-based materials. In light of everything, the need to utilize SRM is expanding, and correspondingly, the drawn out checking of the fabricated climate is getting increasingly pertinent. The colossal yet undiscovered potential for setting round business cases in the development business is by and large seriously researched inside the EU-established undertaking named CINDERELA. SRM based development items created in the CINDERELA project effectively supplant virgin materials and lessening natural effects. Reused total, i.e., secondary total from reused development and destroying waste, is a fantastic material for base and subbase courses, while certain fabricated totals, for example, reused Electric Arc Furnace (EAF) slag and recovered black-top, are brilliant for surface course black top layers. Moreover, there are a few other notable SRM-based materials for street development and support that can be utilized, (1) either in the surface course as totals (e.g., made total from reused foundry sand, reused glass, scoop slag, and reused scrap elastic) or as a cover (e.g., elective bitumen from natural waste) or both (i.e., recovered black-top); (2) street base (e.g., reused and produced total from various waste, recovered black-top), normally compound or mechanical adjustment is expected to accomplish the necessary burden bearing limit; and (3) subbase or potentially dikes (e.g., geotechnical composites).
[007] Utilizing SRM in lower street structure layers is especially fascinating as they are normally the biggest as far as material volume, yet this doesn't overlook their utilizations in other street layers with higher required burden bearing limits. The exertion of the CINDERELA venture to build up a long-term economic plan of action dependent on applying SRM-based materials is just one piece of the riddle. It is similarly essential to demonstrate that such less-traditional development materials and constructions are protected both earth and primarily. Understand that additional difficult issues when utilizing SRM are less knowledge of such materials by engineers, particularly thinking about their drawn-out conduct. Therefore, considering this, it is much more imperative to deliberately gather information on the reaction of SRM-based development materials once introduced in a genuine climate. In the broadest and least difficult setting, DTs can be characterized as a digital actual coordination of resources, cycles, or framework for virtual reproductions, benchmarking, and checks.
[008] DTs go about as a spanning component between the genuine and virtual climate in which ongoing element information is gathered. They are such a relic; a gathering point or an interface that lives between an "inward" climate, the substance and association of the actual antiquity, and an "external" climate, the environmental factors where it works. All the more explicitly, to fit the necessities of CE standards in AEC, DTs can be viewed as the idea of giving steady admittance to the advanced portrayal of actual resources, whereby computerized information is produced progressively by sensors that supplement the benchmark BIM with persistent checking of the actual climate. The basic elements of information in which a data set characterizing the genuine climate can be described as a DT can't be obviously characterized. The model incorporates organized mathematical and property information (material information, compound and mineralogical structure, strength, and so forth) just as unstructured help information as constant material qualities sensor readings. When observing development with SRM, where we don't have the foggiest idea about the specific reaction to outer impacts, it is critical to screen potential changes in the calculation (i.e., distortions and removals), just as supporting data (e.g., temperature, pressing factor, or outside impacts, checking of ecological effects through draining likely harmful components, molecule, and gas emanations). This data is significant, essentially to guarantee mechanical security, wellbeing, economy, and natural effects and to look for additional chances for enhancements in street development materials and streets. In the structural designing area, much is in progress and still being developed with respect to the commonsense convenience of DTs as frameworks of help for specialized dynamic cycles.
[009] On one hand, the current variant 4.2 of the most regularly utilized exchangeable BIM design, specifically, the IFC, actually comes up short on specific highlights and functionalities for street development components contrasted with structures overall. Thusly, the demonstrating stage actually requires a great deal of exertion, regularly including different programming items just as a ton of manual PC work.
[010] Additionally, traversing controls of model creation and later upkeep, DTs request starting close collaboration of both of these subject matters. Besides, polite designing tasks incorporate in fact altogether different elements, which all must be inside associated (adjusted) to give truly important data on the vehicle network level (or its more modest portions). This availability not exclusively is restricted to the arrangement of individual computerized models inside a typical facilitate outline yet in addition includes the foundation of methodological advances that will characterize pertinent boundaries for the vehicle network all in all. For any digitized framework to be valuable for arranging future exercises, one likewise needs to accomplish a serious level of information dividing among various data sets. This in itself addresses a major test. There is an extra advance that convolutes the situation: the DTs, by definition, should contain modern data on the present status of the street being referred to. This must be accomplished by including information from various observing sensors (see Section 4). How this sensor information is refined down to the BIM and its parts is as yet an open inquiry, particularly on the grounds that considerable measures of sensor information might be included, some with high information obtaining rates.
[011] There are two potential approaches to incorporate sensor information areas per the following: (i) To add separate sensor information components to the generally existing BIM; and (ii) To dole out sensors results to relating BIM component properties In the two cases, the underlying advance would include preprocessing the sensor information stream and assessing crucial estimation boundaries to stay away from oversaturating the BIM.
[012] The inventors found dire need to design a digital twin which can be used for multiple construction sites; to monitor the performance of existing sites and improve efficiency of monitoring and provide effective control via this digital twin infrastructure.
Brief Summary of the Invention
[013] As of late, data innovation (IT) support has been acquiring energy, even in more traditionalist businesses. Confronting ever higher solicitations to assemble greater, higher, quicker and all the more proficiently and with less ecological effect, Architectural, Engineering and Construction (AEC) specialists endeavor to discover various intends to handle the difficulties that emerge with automatization of development works'plan, development, use, and remaking or destruction.
[014] Correspondingly, it is very much reported that the AEC business is going through a critical move away from utilizing 2D and 3D CAD models toward a more advanced computerized information structure as a Building Information Model (BIM). This is a reasonable change, as the end result of configuration is turning into a semantically characterized item. Following this approach, it is feasible to make an advanced model of an office in which both mathematical data and nongeometric properties of the multitude of components are incorporated. The need for overseeing data in computerized conditions along the structure lifecycle was first perceived by private financial backers, trailed by the European Union Public Procurement Directive, empowering the European Member States to require the utilization of BIM for openly subsidized development and building projects. Normalization bodies, like building SMART, have put forth extraordinary attempts to shape the information structures into opensource record designs, like Industry Foundation Classes (IFC), since the normalization is pivotal to accomplishing interoperability among exceptionally particular apparatuses that specialists use for different investigations.
[015] Scientists go connected at the hip with programming suppliers to meet the shared objective to make a sheer virtual portrayal as well as reenactment of the actual resources of the assembled climate. Consequently, its long-standing inclination research in AEC to think of a total virtual reproduction of development projects in the plan stage before the beginning of the development works is being epitomized. As ever higher rates of financial backers, including government bodies, project workers, and administrators, understand its advantages upheld development, it is protected to say that BIM is getting more perceived as the business standard. Notwithstanding, we should not overestimate that the utilization of IT has arrived at its maximum capacity exclusively by more extensive selection of BIM.
[016] Our fundamental writing audit demonstrates that in the event that we split AEC-related exercises into two subcategories of structures and structural designing ventures (i.e., streets, rail lines burrows, dikes, and so on), the last will in general get more unobtrusive IT support. This is particularly valid for exercises that follow the plan stage (e.g., progress observing, quality control during development, and checking during the activity stage). In addition, structural designing activities need consistent observing and upkeep because of different burdens and high security prerequisites regarding maturing issues.
[017] It is an object of the present invention to provide to design a digital twin which can be used for multiple construction sites.
[018] It is another object of the present invention to use the digital twin to monitor the performance of existing sites.
[019] It is another object of the present invention to use the digital and improve efficiency of monitoring and provide effective control via this digital twin infrastructure.
[020] According to an aspect of the present invention, a digital twin system to improve the efficiency of a construction site is disclosed. The system includes an application for twinning of construction sites, a Field Programmable Gate Array (FPGA) based internet of things (IoT) sensor interface.
[021] In accordance with the aspect of the present invention, the IoT sensor interfaces (nodules) includes a plurality of sensor modules and communication equipment, pluggable to any system with a need for minimum interfacing.
[022] In accordance with the aspect of the present invention, the nodules are interfaced directly with a signal filtering unit, combined with an ADC unit along with an ALU to process the sensed data. The unit comprises of multiplexers used to combine data from different sensors into a single multiplexed channel.
[023] In accordance with the aspect of the present invention, the FPGA device sends relevant signals to these devices in order to get the final values from the ADC wherein the values are processed to generate actuation signals.
[024] In accordance with the aspect of the present invention, the said signals are used to modify the display data, control the connected actuators.
[025] In accordance with the aspect of the present invention, the FPGA hardware uses an internal soft-core processor like NIOS 2 to send these signals to the soft core unit.
[026] In accordance with the aspect of the present invention, the soft-core unit uses the signals, performs signal processing operations like clustering, thresholding, and others to find out patterns from the input data which are used for intelligent processing.
[027] In accordance with the aspect of the present invention, the patterns are sent through a wireless communication channel which can be Zigbee, GSM, WiFi or the like application specific channel.
[028] In accordance with the aspect of the present invention, the data is received at the receiving side, and control signals are generated at a receiver; the receiver sends these signals back to a transmitter based on the signals; and the transmission device changes the actuation signals, and control the devices accordingly.
[029] In accordance with the aspect of the present invention, the input construction related data fed to the system includes dry density, angle of friction, surcharges, retaining wall height, coefficient of resting earth pressure, coefficient of active earth pressure, coefficient of passive earth pressure, earth pressure per unit width due to soil pressure, earth pressure per unit due to surcharge pressure, and resultant active earth pressure.
[030] According to the aspect of the present invention, a method for twinning the construction sites is disclosed. In accordance with the aspect of the present invention, the method involves a step of entering a plurality of site parameters to the system, and based on pre-set simulation parameters, an analysis is done.
[031] In accordance with the aspect of the present invention, the method involves another step of deciding the site quality based on the analysis, and thereby steps are taken in order to improve existing sites.
[032] In accordance with the aspect of the present invention, the said twinning of the construction sites, includes study of different construction components along with their effects on various parameters.
[033] In accordance with the aspect of the present invention, the said twinning of the construction sites, includes design of a digital twin system that can be used for multiple construction sites.
[034] In accordance with the aspect of the present invention, the twin will take site parameters as input, and conditions like wind direction, soil type, cement quality, etc. and decide upon the site's performance, wherein the performance is monitored using machine learning models, and is improved using neural networks.
[035] In accordance with the aspect of the present invention, the said evaluating parameters are measurements of temperature, heating, and loads.
[036] Operational advantages on using the IoT enabled system and method: Reduced cost of analysis Reduced delay in analysis / Addition of hardware for real-time analysis / oT interface for anywhere access of the site information / Reduced energy consumption due to use of FPGA / Optimization possible due to machine learning / Iterative error reduction can be done / Reduced cost of end product / Better directives for employees for managing site / Can be modelled on open-source technologies to reduce cost of deployment / Simple to understand, so even non-experienced people can use it / Reduced complexity of analysis via modularization / Ability to add multiple metrics for analysis / Flexibility to add large number of parameters for accurate analysis
[037] Working advantages with the IoT enabled system and method: / Design using free source tools like Python to reduce cost / Use of high-performance FPGA for monitoring and high-speed decision making / Ability to analyze a large number of parameters via machine learning / Flexible system due to incorporation of IoT and its monitoring with
actuation / Reduced delay due to high-speed analysis / High accuracy due to machine learning modelling
Safe to test due to digital twinning Unlimited application to other construction sites / Ability to learn from one site and transfer knowledge to other sites / Flexibility to integrate multiple sites for effective analysis / Increased speed of analysis via high performance computing / Performance can be tuned via machine learning models
Brief description of drawings
[038] The above and other objects, features and advantages of the invention will become apparent from a consideration of the following detailed description presented in connection with the accompanying drawings in which:
FIG.a illustrates a flow chart of the IoT enabled digital twin method, according to an exemplary embodiment of the present invention;
FIG.lb illustrates a block diagram of the IoT enabled digital twin device, according to an exemplary embodiment of the present invention;
FIG.2 illustrates overall zone temperature for the entire construction site, according to an exemplary embodiment of the present invention;
FIG.3 illustrates a graph showing zone temperature for the basement, according to an exemplary embodiment of the present invention;
FIG.4 illustrates a graph showing zone temperature for ground floor, according to an exemplary embodiment of the present invention;
FIG.5 illustrates a graph showing zone temperature for floor 1, according to an exemplary embodiment of the present invention;
FIG.6 illustrates a graph showing zone temperature for floor 2, according to an exemplary embodiment of the present invention;
FIG.7 illustrates a graph showing zone temperature for internal offices of each zone, according to an exemplary embodiment of the present invention;
FIG.8 illustrates a graph showing simulated heating predicted for each floor of the construction site, according to an exemplary embodiment of the present invention;
FIG.9 illustrates a graph showing simulated v/s measured values of heating, according to an exemplary embodiment of the present invention;
FIG.10 illustrates a graph showing simulated data v/s retrofit values for each construction component across different time durations, according to an exemplary embodiment of the present invention;
FIG.11 illustrates a graph showing comparison of overall performance for different methods, according to an exemplary embodiment of the present invention;
FIG.12 illustrates a graph showing energy consumption of the IoT enabled digital twin device when compared with other non-nodule and without machine learning models, according to an exemplary embodiment of the present invention;
FIG.13 illustrates a graph showing delay needed for analysis v/s number of sensors used in different conditions, according to an exemplary embodiment of the present invention.
Detailed description of the invention
[039] It is to be understood that the present disclosure is not limited in its application to the details of construction and the arrangement of components set forth in the following description. The present disclosure is capable of other embodiments and of being practiced or of being carried out in many ways. Also, it is to be understood that the phraseology and terminology used herein is for description and should not be regarded as limiting.
[040] On the contrary, it is intended to cover alternatives, modifications and equivalents. Various modifications to the present invention will be clear to a person skilled in the art, and can be made to the present invention within the spirit and scope of the invention.
[041] According to an exemplary embodiment of the present invention, a digital twin system to improve the efficiency of a construction site is disclosed. The system includes an application for twinning of construction sites, a Field Programmable Gate Array (FPGA) based internet of things (IoT) sensor interface.
[042] In accordance with the exemplary embodiment of the present invention, the IoT sensor interfaces (nodules) includes a plurality of sensor modules and communication equipment, pluggable to any system with a need for minimum interfacing.
[043] In accordance with the exemplary embodiment of the present invention, the nodules are interfaced directly with a signal filtering unit, combined with an ADC unit along with an ALU to process the sensed data. The unit comprises of multiplexers used to combine data from different sensors into a single multiplexed channel.
[044] In accordance with the exemplary embodiment of the present invention, the FPGA device sends relevant signals to these devices in order to get the final values from the ADC wherein the values are processed to generate actuation signals.
[045] In accordance with the exemplary embodiment of the present invention, the said signals are used to modify the display data, control the connected actuators.
[046] In accordance with the exemplary embodiment of the present invention, the FPGA hardware uses an internal soft-core processor like NIOS 2 to send these signals to the soft-core unit.
[047] In accordance with the exemplary embodiment of the present invention, the soft-core unit uses the signals, performs signal processing operations like clustering, thresholding, and others to find out patterns from the input data which are used for intelligent processing.
[048] In accordance with the exemplary embodiment of the present invention, the patterns are sent through a wireless communication channel which can be Zigbee, GSM, WiFi or the like application specific channel.
[049] In accordance with the exemplary embodiment of the present invention, the data is received at the receiving side, and control signals are generated at a receiver; the receiver sends these signals back to a transmitter based on the signals; and the transmission device changes the actuation signals, and control the devices accordingly.
[050] In accordance with the exemplary embodiment of the present invention, the input construction related data fed to the system includes dry density, angle of friction, surcharges, retaining wall height, coefficient of resting earth pressure, coefficient of active earth pressure, coefficient of passive earth pressure, earth pressure per unit width due to soil pressure, earth pressure per unit due to surcharge pressure, and resultant active earth pressure.
[051] According to the exemplary embodiment of the present invention, a method for twinning the construction sites is disclosed. In accordance with the exemplary embodiment of the present invention, the method involves a step of entering a plurality of site parameters to the system, and based on pre-set simulation parameters, an analysis is done.
[052] In accordance with the exemplary embodiment of the present invention, the method involves another step of deciding the site quality based on the analysis, and thereby steps are taken in order to improve existing sites.
[053] In accordance with the exemplary embodiment of the present invention, the said twinning of the construction sites, includes study of different construction components along with their effects on various parameters.
[054] In accordance with the exemplary embodiment of the present invention, the said twinning of the construction sites, includes design of a digital twin system that can be used for multiple construction sites.
[055] In accordance with the exemplary embodiment of the present invention, the twin will take site parameters as input, and conditions like wind direction, soil type, cement quality, etc. and decide upon the site's performance, wherein the performance is monitored using machine learning models, and is improved using neural networks.
[056] In accordance with the exemplary embodiment of the present invention, the said evaluating parameters are measurements of temperature, heating, and loads.
[057] Reference will now be made to the drawings in which the various elements of the present invention will be given numeral designations and in which the invention will be discussed so as to enable one skilled in the art to make and use the invention. It is to be understood that the following description is only exemplary of the principles of the present invention, and should not be viewed as narrowing the pending claims.
[058] Additionally, it should be appreciated that the components of the individual embodiments discussed may be selectively combined in accordance with the teachings of the present disclosure. Furthermore, it should be appreciated that various embodiments will accomplish different objects of the invention, and that some embodiments falling within the scope of the invention may not accomplish all of the advantages or objects which other embodiments may achieve.
[059] Referring to FIG.la, a flow chart of the IoT enabled digital twin method, according to an exemplary embodiment of the present invention is disclosed.
[060] Due to high modelling costs, testing construction quality and validating it requires a large infrastructure, which adds to project development cost. In order to reduce this cost, the proposed work describes a model which can be used for twinning any construction site. The site parameters are inserted to the model, and based on pre-set simulation parameters, its analysis is done. Based on this analysis, site quality is decided and thereby steps can be taken in order to improve existing sites.
[061] Methodology The following process is followed for the given research, • Study of different construction components along with their effects on various parameters. • Design of a digital twin system that can be used for multiple construction sites. • The twin will be able to take site parameters as input, and conditions like wind direction, soil type, cement quality, etc. and decide upon the site's performance. • This performance will be monitored using machine learning models, and will be improved using neural networks.
• In case of performance gaps, the system will be able to reduce errors and optimize the digital twin performance for better results.
[062] Based on this process, the following model observed from figure 1 for digital twin development is used. In this process, the following steps are taken for improving site quality via the use of digital twin adoption, • All construction related data like dry density, angle of friction, surcharges, retaining wall height, coefficient of resting Earth pressure, coefficient of active Earth pressure, coefficient of passive Earth pressure, Earth pressure per unit width due to soil pressure, Earth pressure per unit due to surcharge pressure, resultant Active Earth pressure, etc. are input to the system.
[063] Figure la - Flow of the proposed model • These parameters are evaluated, and their effects on the site development performance is studied. This effect includes load on the site, construction time needed based on these parameters, etc. • Using this evaluation, measurements of temperature, heating, loads, etc. and their effects on site quality are studied. These effects are then applied on the site, and their performance is compared from real-time sites. • Integration of these effects on the site is done, and site's performance is simulated. • The simulated performance is compared with real-time performance of actual sites, and based on error values, performance tuning is done. • Performance is tuned, until there is minimum error of evaluation, and the trained model is used for newer site inputs for improve efficiency.
[064] The model is evaluated for different kinds of simulation environments, and results of temperature variation, heating variation, etc. are compared with existing models. To further facilitate the performance of the underlying system, the proposed model is integrated with field programmable gate array (FPGA) based internet of things (IoT) sensor interface. These IoT sensor interfaces are called as nodules. A nodule is basically a combination of sensor modules and communication equipment, which can be pluggable to any system with the need of minimum interfacing. The following figure showcases the design of our proposed IoT nodule,
[065] Referring to FIG.lb, a block diagram of the IoT enabled digital twin device, according to an exemplary embodiment of the present invention is disclosed.
[066] From the design, the working of the proposed system can be described as follows, " The sensors are interfaced directly with the signal filtering unit • These sensors have their data in analog format, and might need some pre processing before actual data recording * The Signal filtering unit combines an ADC unit along with an ALU to process the sensed data * This unit also consists of multiplexers that can be used to combine data from different sensors into a single multiplexed channel * The FPGA device then sends relevant signals to these devices in order to get the final values from the ADC * These values are then processed on the FPGA device directly, and actuation
signals are generated • These signals are used to modify the display data • These signals are also used to control the connected actuators (if needed) • The FPGA hardware uses an internal soft-core processor like NIOS 2 to send these signals to the soft-core unit * The soft-core unit uses these signals, performs signal processing operations like clustering, thresholding, and others * These operations are performed in order to find out patterns from the input data which can be used for intelligent processing
* These patterns are sent through a wireless communication channel which can be Zigbee, GSM, WiFi or any other application specific channel * The data is received at the receiving side, and control signals are generated at the receiver * The receiver will send these signals back to the transmitter
* Based on these signals, the transmission device can change the actuation signals, and control the devices accordingly
[067] In our proposed system, the sensors used are LM35 for temperature sensing, YL69 for moisture sensing, EC sensor, pH sensor, and SY230 humidity sensor. These sensors are interfaced with and PMOD AD2 ADC for conversion into digital values. The multiplexing is done with the help of 4051 Mux device. All these devices are connected to a Nexys 2 FPGA board which is powered by the Spartan 3E processor module. The processor is also interfaced with a HD4470 16x2 LCD module for display of data. While the LM293D device is used for actuating the motor based on the data obtained from these sensors. The soft-core processor is connected to the GSM module, which allows the system to consume lower power, and have high efficiency of wireless data trans-communication. Due to the interface of GSM module with the soft-core processor, there is a possibility of adding multiple application-level interfaces to the system. In this work, a simple data communication interface is developed in C language, which takes data from the FPGA and communicates it over the GSM medium. The communicated data is displayed on the operator's mobile device, for on-the-go analysis of sensed data. A detailed performance evaluation can be observed from the next section.
[068] In order to evaluate performance of the system, various material studies are performed. These studies are performed on each floor level of the building construction site, and parameters like temperature, load consumption, heating, zone temperature, etc. are evaluated. These parameters are compared for both real-time values and simulated values, and results are evaluated. Hourly values of Zone temperatures for a 2-floor building with basement were evaluated, these values can be observed from the following figures.
[069] FIG.2 illustrates overall zone temperature for the entire construction site, according to an exemplary embodiment of the present invention.
[070] The predicted zone temperature for the entire construction site is observed via the purple line, which indicates that the zone temperature is evaluated with high accuracy. Similar measurement is done for the basement and showcased in figure 3, wherein the blue line is an indicative of the predicted basement zone temperature. It can be observed that the predicted value closely matches with actual values of temperature for the system. This indicates that the proposed model is able to identify values with high accuracy, for basement temperature. Similar observations are made for Ground floor, Floor 1, and Floor 2. These observations can be observed from figure 4, 5 and 6, wherein blue line is used for showcasing predicted zone temperature values for the construction site. Similar analysis is done for measured indoor temperature for different offices on each floor. These temperatures are plotted in figure 7, wherein it is observed that the predicted values (blue line) have high accuracy, and match with the original values for actual temperature in the offices. This indicates the high precision of simulation of the proposed tool, and its applicability to real-time construction sites.
[071] FIG.3 illustrates a graph showing zone temperature for the basement, according to an exemplary embodiment of the present invention.
[072] FIG.4 illustrates a graph showing zone temperature for ground floor, according to an exemplary embodiment of the present invention.
[073] FIG.5 illustrates a graph showing zone temperature for floor 1, according to an exemplary embodiment of the present invention.
[074] FIG.6 illustrates a graph showing zone temperature for floor 2, according to an exemplary embodiment of the present invention.
[075] FIG.7 illustrates a graph showing zone temperature for internal offices of each zone, according to an exemplary embodiment of the present invention.
[076] Simulated heating data as shown in figure 8 was given to the system, this data is an approximation of heating needed for each floor space in order to provide optimum load utilization. This simulated data is used for predicting future measured values for the heating system. It is observed that the proposed model is able to capture these values with over 80% accuracy, which makes the proposed model highly accurate and applicable for real-time usage on construction sites.
[077] FIG.8 illustrates a graph showing simulated heating predicted for each floor of the construction site, according to an exemplary embodiment of the present invention.
[078] FIG.9 illustrates a graph showing simulated v/s measured values of heating, according to an exemplary embodiment of the present invention.
[079] The simulated temperature measured data for the following components is analyzed, and compared with actual retrofit values, Retrofit data for windows on the construction site / All Retrofit data for plasters on the construction site / Retrofit data for aerogel used on the construction site / All Retrofit data for ceilings used on the construction site / Retrofit data for air tightness high levels on the construction site / Overall retrofitting data on the site
[080] All these analyzed values are compared with simulated values, and the results are plotted in figure 10, wherein it is observed that the simulated data is nearly 90% accurate and matching with the original measured values.
[081] FIG.10 illustrates a graph showing simulated data v/s retrofit values for each construction component across different time durations, according to an exemplary embodiment of the present invention.
[082] The overall predictions are evaluated for the work, and is compared with the proposed model, their performance is plotted in Fig.11 illustrating a graph showing comparison of overall performance for different methods, according to an exemplary embodiment of the present invention.
[083] Using these evaluations, accuracy of the proposed model is compared with existing models described in [3] and [5]. The accuracy is measured for evaluating temperatures, loads, material quality, material quantity, wind pressure, solar radiation effects and external load effects on the quality of construction. These results are tabulated as follows:
Condition evaluated Accuracy Accuracy Accuracy (%) (%) (%) (Prior (Prior art) art) Effect of temperature on construction 80 83 90 quality Effect of internal loads on life of 70 65 85 construction Effect of material quality on life of 55 70 83 construction
Effect of material quantity availability 90 95 95 on life of construction Effect of wind pressure on construction 75 82 96 quality Effect of solar radiation on construction 83 84 91 quality Effect of human load on construction 90 91 96 quality Effect of construction machinery load on 80 90 93 construction quality Effect of wear and tear on construction 65 75 90 quality
Table 1. Comparison of different types of loads on the overall construction quality prediction by the system
[084] Using this analysis, it can be observed that the proposed model is able to reduce errors during simulation, and improve accuracy with which digital twin material can be evaluated. The accuracy improvement is over 15% when compared to state-of-the art methods, which makes the proposed model applicable for real time usage. Due to incorporation of hardware nodule, the system's delay and energy consumption are also reduced when compared with a non-hardware nodule integrated system. These results can be observed from figure 12 and 13, where in performance evaluation is done for energy consumption and delay of operation for the system with and without nodules. The formula for energy consumption is shown via equation 1, Ec = Esim + Esensing + Eact -- (1)
[085] Where, Ec is energy consumption of the model, Esim is energy needed for performing simulation analysis, Esensing is energy needed for sensing data via IoT
hardware, and Eact is energy consumed for actuating the information via IoT devices. Similarly, delay is also evaluated using the same equation, which indicates that both energy and delay can be optimized via optimization of the internal simulation, sensing and actuating activities.
[086] FIG.12 illustrates a graph showing energy consumption of the IoT enabled digital twin device when compared with other non-nodule and without machine learning models, according to an exemplary embodiment of the present invention.
[087] Similar comparison is done for delay, and can be observed from Fig.13 illustrating a graph showing delay needed for analysis v/s number of sensors used in different conditions, according to an exemplary embodiment of the present invention., wherein number of sensors are varied for delay evaluation.
[088] From the results it can be observed that the proposed model is highly effective, and can be used for efficiently predicting zone temperatures, heating effects, inter-component behavior, effects of internal & external loads with high accuracy. The model is compared with some of the state-of-the-art models, and accuracy improvement of 10% for temperature effect incorporation, 20% for internal load consideration, 28% for material quality consideration, 5% for material quantity consideration, 21% for wind pressure consideration, 8% for solar radiation consideration, 6% for human load consideration, 13% for machine load consideration and, 25% for wear and tear considerations is achieved. This accuracy is a measure of the closeness with which digital twin is modelled for construction sites, and thus is able to reduce overall human effort for testing and validation of the system. This reduces testing & validation costs, thereby reducing overall construction site costs. The model also reduces delay needed in building the sites, thereby increasing overall speed at which safe and quality construction can take place.
Claims (1)
- 5. CLAIMS I/We Claim: 1. A digital twin system to improve the efficiency of a construction site, wherein the system includes: an application for twinning of construction sites; a Field Programmable Gate Array (FPGA) based internet of things (IoT) sensor interface; wherein the IoT sensor interfaces (nodules) includes a plurality of sensor modules and communication equipment, pluggable to any system with a need for minimum interfacing; wherein the nodules are interfaced directly with a signal filtering unit, combines with an ADC unit along with an ALU to process the sensed data; the unit comprises of multiplexers used to combine data from different sensors into a single multiplexed channel; wherein the FPGA device sends relevant signals to these devices in order to get the final values from the ADC wherein the values are processed to generate actuation signals; the said signals are used to modify the display data, control the connected actuators; the FPGA hardware uses an internal soft-core processor like NIOS 2 to send these signals to the soft-core unit; the soft-core unit uses the signals, performs signal processing operations like clustering, thresholding, and others to find out patterns from the input data which are used for intelligent processing; the patterns are sent through a wireless communication channel which can be Zigbee, GSM, WiFi or the like application specific channel; the data is received at the receiving side, and control signals are generated at a receiver; the receiver sends these signals back to a transmitter based on the signals; the transmission device changes the actuation signals, and control the devices accordingly.2. The digital twin system as claimed in claim 1, wherein the input construction related data fed to the system includes dry density, angle of friction, surcharges, retaining wall height, coefficient of resting earth pressure, coefficient of active earth pressure, coefficient of passive earth pressure, earth pressure per unit width due to soil pressure, earth pressure per unit due to surcharge pressure, and resultant active earth pressure.3. A method of twinning the construction sites, wherein the method involves steps of: entering a plurality of site parameters to the system, and based on pre-set simulation parameters, an analysis is done; deciding the site quality based on the analysis, and thereby steps are taken in order to improve existing sites; the said twinning of the construction sites, includes: study of different construction components along with their effects on various parameters; design of a digital twin system that can be used for multiple construction sites; and the twin will take site parameters as input, and conditions like wind direction, soil type, cement quality, etc. and decide upon the site's performance, wherein the performance is monitored using machine learning models, and is improved using neural networks.4. The method as claimed in claim 1, the said evaluating parameters are measurements of temperature, heating, and loads.Input different Evaluate the effect Measure temperature, construction site of these parameters heating, loads, etc., and parameters on site development study their effects 1/12Integrate these effects Tune the parameters in order to evaluate in order to improve site performance construction qualityFIG. 1ATemp Humidity Pressure Other sensor sensor sensor sensorsSignal filtering unit (ADC and filters)Hardware interface code for sensors and actuators 2/12Display and actuator devices Soft core processor FPGA deviceWireless communication device for sending sensed data and receiving actuating informationFIG. 1B27.525.022.520.017.5 3/1215.012.510.07.5 7 14 21 28 04 11 18 25 04 11FIG. 22218 4/1216 14 1207 14 21 28 04 11 18 25 04 11FIG. 323 22 21 5/1219 18 10 11 12 13 14FIG. 424 2218 6/1216 14 1207 14 21 28 04 11 18 25 04 11FIG. 5227/1218161407 14 21 28 04 11 18 25 04 11FIG. 626 24 22 20 8/1218Zone Temperature ( 0C) 16 007 14 21 28 04 11 18 25 04 11 Measured Indoor TemperatureFIG. 7
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113655423A (en) * | 2021-08-27 | 2021-11-16 | 康达洲际医疗器械有限公司 | High real-time magnetic resonance spectrometer system and management method |
| CN115086202A (en) * | 2022-04-14 | 2022-09-20 | 安世亚太科技股份有限公司 | Time delay analysis method and system based on network digital twin |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113655423A (en) * | 2021-08-27 | 2021-11-16 | 康达洲际医疗器械有限公司 | High real-time magnetic resonance spectrometer system and management method |
| CN113655423B (en) * | 2021-08-27 | 2024-05-28 | 康达洲际医疗器械有限公司 | High-instantaneity magnetic resonance spectrometer system and management method |
| CN115086202A (en) * | 2022-04-14 | 2022-09-20 | 安世亚太科技股份有限公司 | Time delay analysis method and system based on network digital twin |
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