Matrix Geo Solutions Limited has secured a railway infrastructure project in collaboration with the Ajmer Division of Indian Railways to deploy digital twin technology, drone-based LiDAR mapping, and 3D geospatial modelling for a proposed broad gauge rail corridor between Taranga Hill and Abu Road via Ambaji.
The project marks a significant step towards the adoption of data-driven railway planning and digital engineering frameworks in India’s transport infrastructure sector. By integrating aerial surveying, geospatial analytics, and digital twin modelling, the initiative aims to improve planning accuracy, reduce design risks, and enhance long-term operational visibility.
At the core of the project is the use of drone-based LiDAR (Light Detection and Ranging) technology, which will capture high-resolution terrain and infrastructure data across the proposed corridor. These aerial surveys will generate topographic maps, elevation models, and orthophoto mosaics, creating a precise digital representation of the landscape for engineering analysis and route planning.
Matrix Geo will also develop a comprehensive 3D digital twin of the project environment, incorporating terrain features such as roads, vegetation, water bodies, utilities, and built infrastructure. This virtual replica will function as a dynamic planning and simulation environment, allowing teams to analyse alignment options, evaluate construction feasibility, and identify potential challenges before physical execution begins.
In addition, the company will create a separate 3D engineering model of the proposed railway corridor to Level of Development (LOD) 200 standards. The model will include structural and alignment components such as bridges, tunnels, station infrastructure, formation widths, and embankments, enabling greater precision during the design and coordination phases.
The initiative also incorporates aerial simulation and flythrough visualisation capabilities, which will support stakeholder communication, project reviews, and collaborative decision-making. These immersive digital outputs are expected to reduce rework during construction while improving coordination between engineering, planning, and execution teams.
According to Amit Sharma, digital twin technology enables infrastructure teams to test, validate, and refine designs in a virtual environment before deployment, creating a more reliable and efficient planning framework.
Beyond project execution, the digital twin models are expected to support future operations and maintenance workflows, reflecting a growing trend towards lifecycle-based infrastructure management where digital assets continue to provide value long after construction is complete.
Overall, the project highlights the increasing role of geospatial intelligence, drone analytics, and digital twin ecosystems in modern infrastructure development as transportation networks move towards more connected, predictive, and technology-driven planning models.