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Construction Industry

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Prediction of Equipment Effectiveness using Hybrid Moving Average-Adaptive Neuro Fuzzy Inference System (MA-ANFIS) for decision support in Bus Body Building Industry.

Anais da Academia Brasileira de Ciencias
Managers are driven to accomplish significantly higher levels of operational performance due to the difficulty of today's dynamic production environment. Typically, the precision of production facilities and the efficiency of manufacturing systems ar...

Exploring the Application of BIM Technology in the Whole Process of Construction Cost Management with Computational Intelligence.

Computational intelligence and neuroscience
The construction industry is a labor-intensive industry in China. In recent years, as people's living standards have risen, so have their requirements for the functionality, appearance, and comfort of buildings. The amount of information attached to ...

Real-time construction demolition waste detection using state-of-the-art deep learning methods; single-stage vs two-stage detectors.

Waste management (New York, N.Y.)
Central to the development of a successful waste sorting robot lies an accurate and fast object detection system. This study assesses the performance of the most representative deep-learning models for the real-time localisation and classification of...

Unmanned Aerial Systems and Deep Learning for Safety and Health Activity Monitoring on Construction Sites.

Sensors (Basel, Switzerland)
Construction is a highly hazardous industry typified by several complex features in dynamic work environments that have the possibility of causing harm or ill health to construction workers. The constant monitoring of workers' unsafe behaviors and wo...

Real-time monitoring unsafe behaviors of portable multi-position ladder worker using deep learning based on vision data.

Journal of safety research
INTRODUCTION: Fatal fall from height accidents, especially on construction sites, persist, underscoring the importance of monitoring and managing worker behaviors to enhance safety. Deep learning showed the possibility of substituting the manual work...

A Bibliometric Analysis of Neuroscience Tools Use in Construction Health and Safety Management.

Sensors (Basel, Switzerland)
Despite longstanding traditional construction health and safety management (CHSM) methods, the construction industry continues to face persistent challenges in this field. Neuroscience tools offer potential advantages in addressing these safety and h...

Deep learning-based models for environmental management: Recognizing construction, renovation, and demolition waste in-the-wild.

Journal of environmental management
The construction industry generates a substantial volume of solid waste, often destinated for landfills, causing significant environmental pollution. Waste recycling is decisive in managing waste yet challenging due to labor-intensive sorting process...

Enhancing safety of construction workers in Korea: an integrated text mining and machine learning framework for predicting accident types.

International journal of injury control and safety promotion
Construction workers face a high risk of various occupational accidents, many of which can result in fatalities. This study aims to develop a prediction model for nine prevalent types of construction accidents, utilizing construction tasks, activitie...

Research on helmet wearing detection method based on deep learning.

Scientific reports
The vigorous development of the construction industry has also brought unprecedented safety risks. The wearing of safety helmets at the construction site can effectively reduce casualties. As a result, this paper suggests employing a deep learning-ba...

A new multi-criteria decision making method for the selection of construction contractors using interval valued fuzzy set.

BMC research notes
OBJECTIVE: This article introduces a novel approach called Digital Weighted Multi Criteria Decision Making (DWMCDM) that employs interval valued fuzzy sets to select the best contractor for building projects. The contractor is chosen based on the pre...