Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
@article{199733,
author = {Siva Sankar M and Keerthanalakshmi J and Moorthi G and Nandhini M},
title = {REAL-TIME MONITORING OF THERMAL BEHAVIOR IN TRUSSES USING IOT AND ANSYS SIMULATION},
journal = {International Journal of Innovative Research in Technology},
year = {2026},
volume = {12},
number = {12},
pages = {396-403},
issn = {2349-6002},
url = {https://ijirt.org/article?manuscript=199733},
abstract = {The strength, stability, and long-term safety of truss structures are significantly affected by temperature variations, which can lead to thermal stress, deformation, and potential structural failure over time. Changes in temperature cause expansion and contraction of structural members, creating additional stresses that may not be easily detected through visual inspection alone. This study presents an integrated approach that combines IoT technologies with advanced numerical simulation to monitor and analyse the real-time thermal behaviour of truss structures. A network of temperature and strain sensors is installed on a physical truss to continuously collect real-time data under changing environmental conditions. These smart sensors, enabled through IoT technologies, transmit the collected data wirelessly to a central monitoring system. The received data is processed and visualized to provide immediate insights into temperature distribution and strain response across the structure. In parallel, a detailed Thermal Analysis is performed using ANSYS software. The live sensor data is used as input for the simulation model, allowing accurate prediction of temperature-induced stress and deformation in the truss members. This combined experimental and numerical approach enables realistic assessment of structural performance under thermal loading. By integrating real-time IoT-based monitoring with ANSYS thermal and structural simulations, the proposed method improves prediction accuracy and enables early identification of heat-related stress issues. This approach supports timely maintenance decisions, reduces the risk of structural damage, and contributes to the development of smarter, safer, and more resilient truss structures.},
keywords = {- GGBS, Flyash, Basalt fibre, Sodium silicate, Sodium hydroxide and oven curing},
month = {May},
}
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