Equipment data-based activity recognition of construction machinery

Fischer, Anne; Bedrikow, Alexandre Beiderwellen; Keßler, Sylvia; Fottner, Johannes

doi:10.1109/ice/itmc52061.2021.9570272

Cited by 4 publications

(2 citation statements)

References 14 publications

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“…The research algorithm is compared with the ENN, BP neural network [29], LSTM algorithm [30], and the model algorithm proposed by Li et al (2023) in terms of tting effect, root mean squared error (RMSE), and determination coe cient (R 2 ) in order to assess the performance of the model built in this paper.…”

Section: Simulation Experiments Evaluationmentioning

confidence: 99%

Intelligent Building Construction Cost Prediction Based on BIM and Elman Neural Network

Zhang,

2023

Preprint

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This paper aims to predict the construction cost more accurately to promote the digital and visual development of the design and construction process in the construction field. In this paper, an intelligent building construction cost prediction model based on BIM and Elman neural network (ENN) is constructed. In this model, firstly, BIM technology is introduced, and the BIM intelligent building model is established, including the digitalization and visualization of the information of building structure, electromechanical and pipeline. Then the data information in BIM intelligent building model is imported into ENN as input data, and the construction cost of intelligent building is predicted by optimizing the parameters of neural network. Finally, the model is evaluated experimentally. The results show that the predicted value of the construction cost of the intelligent building is highly fitted with the original information price, the root mean squared error (RMSE) is less than 75. The determination coefficient is greater than 0.95, which is clearly superior to the single ENN. The algorithm of the intelligent building construction cost prediction model has thus been found through this paper to have high accuracy and reliability, and can successfully predict the construction cost, providing strong decision support for the digital and intelligent development of construction enterprises.

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Section: Simulation Experiments Evaluationmentioning

confidence: 99%

Intelligent Building Construction Cost Prediction Based on BIM and Elman Neural Network

Zhang,

2023

Preprint

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“…Through this approach, specific sub-processes are examined, measured, and analysed, and the processes with major emissions are detected. Examples of this very detailed approach are shown by [20,21].…”

Section: Bottom-up Approach and Lean Constructionmentioning

confidence: 99%

Process-specific digital recording of construction site LCA-inventory to identify decarbonisation pathways

Wagner¹,

Ott²

2022

IOP Conf. Ser.: Earth Environ. Sci.

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In building life cycle assessment, construction site processes are currently hardly accounted for in detail. If considered, the emission values are determined by globally capturing effort values and by allocating them to individual work steps, equipment, or materials. To identify improvement potential to decarbonize construction activities, detailed process data must be captured for specific processes to determine the carbon dioxide emissions of single processes. The results can then be aggregated to larger process units e.g. to components or trades. To fully implement this approach, a recording of process-specific data at construction site is necessary. Therefore, the basic framework to record specific processes at construction site is developed in this article and LCA methodology to systematically link them to emissions is explained. Further, the method of computer vision for automated recording of construction site activities is being presented.

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Investigation of Data Transmission Between Construction Machines and Attachment Tools via OPC UA Technology

Land,

Vogel-Heuser,

Krüger

et al. 2023

Lecture Notes in Civil Engineering

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Equipment data-based activity recognition of construction machinery

Cited by 4 publications

References 14 publications

Intelligent Building Construction Cost Prediction Based on BIM and Elman Neural Network

Intelligent Building Construction Cost Prediction Based on BIM and Elman Neural Network

Process-specific digital recording of construction site LCA-inventory to identify decarbonisation pathways

Investigation of Data Transmission Between Construction Machines and Attachment Tools via OPC UA Technology

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