Applying Artificial Intelligence and the Internet of Things to the Building Sector to Improve Security and Disaster Prediction
The Intelligent Infrastructure Monitoring System (IIMS) is a data-driven approach that uses Artificial Intelligence (AI) and the Internet of Things (IoT) to enhance civil engineering Disaster Management (DM). To predict future disasters, the system uses a Multi-Tiered Model (MTM) to integrate real-time data from IoT sensors, such as stress, vibration, temperature, humidity, and corrosion levels. The Temporal Graph Convolutional Network Model (TGCNM) processes this data to capture spatial and temporal dependencies across structural components, enabling proactive maintenance and risk mitigation. The TGCNM outperforms baseline models by a significant margin, and hyperparameter sensitivity analysis identifies the optimal configuration for enhanced performance. This data-driven approach is vital for monitoring and securing key infrastructure and enhancing civil engineering DM with AI and IoT.
Authors
- Sampathirao Suneetha
- N Nanthini
- Swati Saxena (ORCID: https://orcid.org/0000-0003-0797-7095)
- V. Sabaresan
- S.B. Prakalya
- A. T.
Institutions
- St. Joseph's Institute of Technology (IN)
- Sathyabama Institute of Science and Technology (IN)
- Saveetha University (IN)
- Koneru Lakshmaiah Education Foundation (IN)
Publication Details
- Journal
- Journal of Machine and Computing
- Published
- 2025-04-05
- DOI
- https://doi.org/10.53759/7669/jmc202505087
- Primary Topic
- Traffic Prediction and Management Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00