AI-Powered Solutions for Sustainable Waste Management in Construction Projects

Year : 2025 | Volume : 15 | Issue : 02 | Page : 1 5
    By

    Deshvena Y.N.,

Abstract

The construction industry is a significant contributor to global waste, posing challenges to sustainability and environmental health. This research explores AI-powered solutions for sustainable waste management in construction projects, focusing on optimizing waste reduction, recycling, and resource efficiency. By integrating machine learning algorithms and IoT-enabled sensors, real-time monitoring of waste generation and segregation can be achieved. Predictive analytics and AI-driven decision-making tools are employed to enhance material reuse and minimize landfill contributions. The study also examines the role of AI in automating waste classification, tracking, and recovery processes. These solutions aim to reduce environmental impact, improve cost efficiency, and support sustainable construction practices. The findings will contribute to advancing eco-friendly approaches in the construction industry through intelligent waste management systems. The construction industry is a leading contributor to global waste, accounting for significant environmental and resource challenges. This research explores AI-powered solutions to promote sustainable waste management in construction projects, aiming to reduce waste generation, enhance recycling, and optimize resource efficiency. By leveraging advanced technologies such as machine learning, IoT, and computer vision, AI-driven systems enable real-time monitoring of waste at construction sites. IoT sensors and data analytics provide insights into waste patterns, while machine learning models predict future trends and material requirements, helping to minimize excess and prevent over-ordering. AI-based automation in waste classification and segregation enhances recycling efficiency by identifying recyclable materials with high precision, reducing landfill dependency. Decision-making tools supported by AI offer project-specific strategies to improve material reuse, cost efficiency, and environmental sustainability. Furthermore, predictive analytics play a vital role in identifying opportunities for material recovery and reuse, supporting circular economy principles. This study also examines the challenges of implementing AI solutions, including data availability, system scalability, and collaboration among stakeholders. By addressing these barriers, AI can transform waste management practices in the construction industry, enabling a shift toward sustainable development and aligning with global environmental goals. The findings provide actionable insights into integrating AI-driven systems for eco-friendly construction waste management.

 

Keywords: Sustainable construction, waste management, artificial intelligence (AI), Machine learning, IoT sensors, recycling optimization, resource efficiency, circular economy, predictive analytics, waste classification

[This article belongs to Recent Trends in Civil Engineering & Technology ]

How to cite this article:
Deshvena Y.N.. AI-Powered Solutions for Sustainable Waste Management in Construction Projects. Recent Trends in Civil Engineering & Technology. 2025; 15(02):1-5.
How to cite this URL:
Deshvena Y.N.. AI-Powered Solutions for Sustainable Waste Management in Construction Projects. Recent Trends in Civil Engineering & Technology. 2025; 15(02):1-5. Available from: https://journals.stmjournals.com/rtcet/article=2025/view=232902


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Regular Issue Subscription Original Research
Volume 15
Issue 02
Received 21/03/2025
Accepted 25/04/2025
Published 30/04/2025
Publication Time 40 Days
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