Prediction and Enhancing Construction Processes Through Machine Learning and Recent Optimization Techniques

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Author(s): M. Veerapathran (Department of Civil Engineering, Dr. N.G.P. Institute of Technology, Coimbatore, India), Somu Chinnusamy (Department of Research and Development, RSP Science Hub, Coimbatore, India), Himanshu Singh (Department of Civil Engineering, Uttranchal University, Dehradun, India), Amit Chawla (School of Emerging Media and Creator Economy, K.R. Mangalam University, Gurugram, India)and Harkirat Kaur (Department of Civil Engineering, Gautam Buddha University, Greater Noida, India)
Copyright: 2026
Pages: 26
Source title: Mitigating Unsustainable Practices in Construction and Architecture
Source Author(s)/Editor(s): Roberto Alonso González-Lezcano (Universidad CEU San Pablo, Spain)and Sunil Kumar Sansaniwal (NITI Aayog, India)
DOI: 10.4018/979-8-3373-2555-2.ch006

Keywords: Engineering Science / Engineering Science Reference / Environment & Agriculture / Sustainable Development

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Abstract

This chapter explores artificial intelligence (AI) and machine learning (ML)-driven processes in transactions that detect optimization, emphasizing forecast analysis, auto tomatoes, and data-based decisions. It investigates how AI/ML models increase the accuracy of planning, resource allocation, reducing risk and real-time monitoring of construction activities. By integrating history with intelligent algorithms, construction workflow can be trimmed for more efficiency, cost-effectiveness and durability. Case studies and emerging technologies highlight AI's transformative prospects in eliminating industry challenges such as delays, budget overruns, and safety risks. The chapter outlines practical structures and future directions for the implementation of AI and ML to optimize the construction project exhibition from the end to end.

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Prediction and Enhancing Construction Processes Through Machine Learning and Recent Optimization Techniques

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