Evaluation of a Swarm Intelligence Approach for Assessing Civil Infrastructure Condition

Authors

  • Hemal Thakker Department of ISME, ATLAS SkillTech University, Mumbai, Maharashtra, India
  • Daljeet Pal Singh Maharishi University of Information Technology, Lucknow, India
  • Raja Praveen K. N. JAIN (Deemed-to-be University), Karnataka, India
  • Tannmay Gupta Chitkara University, Rajpura, Punjab, India
  • Ravi Kant Pareek Vivekananda Global University, Jaipur

Keywords:

Civil infrastructure, condition monitoring, structural health, Swarm-Intelligent Aquila Optimization (SIAO)

Abstract

It is crucial to evaluate the state of civil infrastructure to maintain the durability of these essential systems and ensure public safety. Physical assessments, which are time-consuming, laborious, and prone to human error, are frequently used in traditional methods for evaluating infrastructure status. This study introduces a new Swarm-Intelligent Aquila Optimisation (SIAO) method for assessing the state of civil infrastructure to get beyond these restrictions. The SIAO approach intelligently examines and evaluates the present condition of buildings by examining many characteristics, including structural health, by simulating a swarm's well-organized motion and decisions. Concrete image datasets are gathered to explore the proposed SIAO approach's performance in monitoring the structures' status. The outcomes showed that the SIAO technique performs better than conventional methods in effectiveness, accuracy, and dependability. This strategy could revolutionize the building engineering discipline and support the proactive control and upkeep of vital infrastructure facilities..

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Published

24.03.2024

How to Cite

Thakker, H. ., Singh, D. P. ., K. N., R. P. ., Gupta, T. ., & Pareek, R. K. . (2024). Evaluation of a Swarm Intelligence Approach for Assessing Civil Infrastructure Condition. International Journal of Intelligent Systems and Applications in Engineering, 12(19s), 733–738. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/5203

Issue

Vol. 12 No. 19s (2024)

Section

Research Article

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