Intelligent Material Tracking and Management in Large-Scale Construction Projects
-
DOI:
https://doi.org/10.67228/30715725/IJIARE-2018PII2H7LPublished 07-02-2018
Intelligent Material Management, Construction Technology, Real-Time Tracking, RFID, IoT in Construction, BIM Integration, Supply Chain Management, Construction Automation, GPS Tracking, Smart Construction Sites Issue
Section
ArticlesHow to Cite
[1]C. Wei, “Intelligent Material Tracking and Management in Large-Scale Construction Projects ”, IJIARE, vol. 1, no. 2, pp. 01–09, Jul. 2018, doi: 10.67228/30715725/IJIARE-2018PII2H7L.Abstract
Efficient material tracking and management are critical to the success of large-scale construction projects, where delays, losses, and mismanagement can significantly impact timelines and budgets. Traditional systems often lack the responsiveness and integration needed for modern project demands. This paper explores the adoption of intelligent technologies—such as RFID, IoT, AI, GPS, and BIM—for real-time, automated tracking and management of construction materials. It presents an overview of current technologies, outlines a proposed system architecture, and analyzes implementation through a case study scenario. The paper also discusses the challenges involved and highlights future trends like AI forecasting and blockchain integration. By embracing intelligent material management systems, the construction industry can achieve improved accuracy, efficiency, and sustainability in project execution.
References
[1] Azhar, S., Hein, M., & Sketo, B. (2008). Building Information Modeling (BIM): Benefits, Risks and Challenges. Proceedings of the 44th ASC Annual Conference.
[2] Cheng, J. C. P., & Teizer, J. (2013). Real-time resource location data collection and visualization technology for construction safety and activity monitoring applications. Automation in Construction, 41, 96–105.
[3] Eastman, C., Teicholz, P., Sacks, R., & Liston, K. (2011). BIM Handbook: A Guide to Building Information Modeling for Owners, Managers, Designers, Engineers and Contractors. Wiley.
[4] Goh, Y. M., & Abdul-Rahman, H. (2015). Use of RFID technology for materials management in construction projects. International Journal of Construction Management, 15(1), 1–14.
[5] Irizarry, J., & Karan, E. P. (2012). Integrating UAV-based photogrammetry and BIM for construction monitoring. Journal of Automation in Construction, 28, 123-131.
[6] Li, H., & Lu, W. (2018). Application of artificial intelligence in construction materials management: A review. Automation in Construction, 96, 88-98.
[7] Peña-Mora, F., & Han, S. (2001). Real-time project control: Integrating construction project management and scheduling with wireless communications. Journal of Construction Engineering and Management, 127(6), 414-425.
[8] Teizer, J., & Cheng, T. (2011). Locating and tracking of construction resources using GPS and RFID: A review. Automation in Construction, 20(1), 91-98.
[9] Wang, L., & Shen, Q. (2013). Real-time monitoring of materials delivery using RFID technology in construction projects. Journal of Computing in Civil Engineering, 27(6), 609-619.
[10] Zhang, X., & Hu, Z. (2017). Integration of BIM and IoT for real-time construction site monitoring. Journal of Construction Engineering and Management, 143(7).
Downloads
How to Cite
[1]C. Wei, “Intelligent Material Tracking and Management in Large-Scale Construction Projects ”, IJIARE, vol. 1, no. 2, pp. 01–09, Jul. 2018, doi: 10.67228/30715725/IJIARE-2018PII2H7L.
Most read articles by the same author(s)
- Dr. Chen Wei, Dr. Liu Fang, Real-Time Path Correction for Assembly Line Robots Using Sensor Fusion , International Journal of Intelligent Automation & Robotics Engineering: Vol. 2 No. 1 (2019)
Similar Articles
- Dr. Anita Verma, Hybrid Control Strategies for High-Accuracy Robotic Manipulators , International Journal of Intelligent Automation & Robotics Engineering: Vol. 2 No. 2 (2019)
- Dr. Pooja Agarwal, Dr. Rakesh Chandra, Design of Autonomous Inspection Robots for Infrastructure Monitoring , International Journal of Intelligent Automation & Robotics Engineering: Vol. 3 No. 2 (2020)
- Dr. Chen Wei, Dr. Liu Fang, Real-Time Path Correction for Assembly Line Robots Using Sensor Fusion , International Journal of Intelligent Automation & Robotics Engineering: Vol. 2 No. 1 (2019)
- Dr. Rajesh Kumar Sharma, Dr. Priya Natarajan, AI-Driven Adaptive Control Systems for Industrial Automation , International Journal of Intelligent Automation & Robotics Engineering: Vol. 3 No. 1 (2020)
- Mr. Jose Fernandez, Ms. Marta Silva, Autonomous Decision Support Systems for Intelligent Factory Operations , International Journal of Intelligent Automation & Robotics Engineering: Vol. 8 No. 1 (2025)
- Dr. Venkatesh Iyer, Dr. Nandhini Ravi, Development of Smart Robotic Grippers Using Tactile Sensors , International Journal of Intelligent Automation & Robotics Engineering: Vol. 3 No. 2 (2020)
- Dr. Linda Martinez, Dr. Mark Richardson, Digital Twin-Based Performance Optimization of Industrial Robots , International Journal of Intelligent Automation & Robotics Engineering: Vol. 4 No. 2 (2021)
- P. K. Iyengar, Smart Manufacturing Analytics Using Industrial Internet of Things , International Journal of Intelligent Automation & Robotics Engineering: Vol. 5 No. 2 (2022)
- Narendra Karmarkar, P. K. Iyengar, Industry 5.0-Oriented Human-Centric Robotic Manufacturing Systems , International Journal of Intelligent Automation & Robotics Engineering: Vol. 7 No. 1 (2024)
- Alexey Lyapunov, AI-Based Dynamic Task Allocation in Multi-Robot Systems , International Journal of Intelligent Automation & Robotics Engineering: Vol. 8 No. 1 (2025)
You may also start an advanced similarity search for this article.