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INTERNATIONAL JOURNAL OF RECENT TRENDS IN TECHNOLOGY AND ENGINEERING (IJRTTE)

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AI-Driven Prediction and Optimization of Concrete Curing Conditions for Enhanced Performance

J Raja
Associate Professor, Department of Computer Science and Engineering, School of Computing, Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology , India.

Keywords: AI-supported optimization, concrete curing, machine learning, real-time monitoring, concrete strength, durability, resource efficiency, cost savings, sustainable building, predictive modelling, dynamic adaptation, construction efficiency, concrete mixture, environmental conditions, data-driven process.

Abstract

Optimization of the curing systems is vital to improve the quality, durability, and performance of the concrete structures. In this paper, an AI-based method introduced to predict and optimize concrete curing parameters, applying machine learning models for better strength and consistency of concrete. Using real-time data and environmental conditions, the developed model is capable of adapting curing settings dynamically thus minimizing variations and material waste. The data-driven approach ultimately aims to optimise the resource efficiency, reduce cost, and sustainability practices in construction. The ability to control and adapt curing regimes in the field becomes possible, this allowing improved quality of concrete in every aspect, strength, durability and long-term performance. In addition, the scalability, and robust of the learned AI model makes it suitable for a various type of concretes and the curing conditions for flexible, cost-effective, and environment-friendly construction. The use of AI not only provides higher quality of concrete, but also can save time in the process allowing for quicker project completion and stronger structural formations. Finally, this study emphasizes the applicability of AI in the field of concrete curing; ultimately presenting a more effective, economical, and environmentally conscious alternative to traditional construction methods.
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Details
Published
2024-06-26
Pages
1-12
Issue
Vol. 3 No. 2 (2024): IJRTTE - 03 - 02
Section
Articles

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