Smart Technologies in Construction and Transportation Infrastructure: A Review of AI, IoT, and Data-Driven Innovations
While the field of civil engineering has traditionally been dominated by hands-on and experience-based techniques, the advent of Artificial Intelligence (AI), Internet of Things (IoT), and data analytics are transforming it. This paper provides a structured outcome-oriented narrative review of the applications of smart technology in two dominant areas: construction management and transportation infrastructure. It is based on 37 peer-reviewed journal articles, conference papers, and technical reports from 2015 to 2026 that were selected purposively, without using a registered systematic search. The evidence has been grouped into eight application themes: AI/ML in construction project management; IoT-enabled site and structural monitoring; AI-driven intelligent transportation systems; IoT-based smart pavement and road monitoring; machine-learning-based structural health monitoring; digital twins and blockchain; UAV and computer-vision monitoring; and cybersecurity in smart infrastructure. The reported outcomes represent distinct performance dimensions and are not directly compared: examples include a 0.12% cost variance for AI/ML project models, a concrete strength prediction error within 1–2 MPa alongside a maximum UWB worker positioning error of 1.44 m for an IoT-based system, a 98.6% traffic-monitoring performance for a machine-learning classification model, and a hardhat-detection precision of 93.1% for Faster R-CNN. Themes of AI and IoT integration are most frequently associated with improved prediction, monitoring, and decision support, while digital twins and blockchain are primarily associated with data trust, traceability, and operational latency reduction. Recurring barriers include data interoperability, data security, implementation costs, and metric heterogeneity across literature. This review concludes with a research agenda prioritizing interoperable data standards, edge-AI and federated learning, cybersecurity-by-design, and standardized outcome reporting.
Authors
- Vijay Lalwani
Institutions
- Parul University (IN)
Publication Details
- Journal
- International Journal of Applied Smart Interdisciplinary Technologies
- Published
- 2026-10-29
- DOI
- https://doi.org/10.68104/ijasit.v1.i4.53
- Primary Topic
- Infrastructure Maintenance and Monitoring
- Type
- article
- Field-Weighted Citation Impact
- 0.00