Applied Research and Innovation
AKCM is actively developing AI/ML-driven engineering solutions to transform infrastructure management and automate road safety processes. As part of its applied research and innovation initiatives, AKCM—in collaboration with Thapar Institute of Engineering & Technology (TIET)—has launched a flagship project titled “Real-Time Health Monitoring and Development of Maintenance Management System for Rigid Pavements using AI/ML.”
The project focuses on building an AI-based decision-support platform for real-time pavement health monitoring, performance evaluation, and predictive maintenance, leveraging AI/ML models, LiDAR and inertial profiling sensors, geo-tagged data capture, and cloud-based analytics.
AI-Enabled Frameworks
Importantly, this initiative also serves as a precursor and foundational module for AKCM’s AI-enabled Road Safety Automation framework. The platform is being developed to integrate road-safety-aligned functionalities such as:
- Automated chainage tracking and geo-referenced documentation.
- Geo-referenced visual documentation and annotation-based analysis.
- Corridor-level analytics for future deployment.
- AI-driven Road Safety Audit and Risk Assessment tools.
Roadmap to National Deployment
The project follows a structured multi-phase roadmap—from prototype and MVP development to field validation, industry engagement, and deployment ensuring that academic research translates into field-ready, scalable solutions for National Highways and large road networks.
- Prototype and MVP development for rapid field validation.
- Industry engagement and large-scale corridor analytics.
- Scalable deployment for National Highway networks.
