JNPA Advances AI-Powered Digital Twin for Smarter Port Operations

The Jawaharlal Nehru Port Authority (JNPA) is moving ahead with an AI/ML-enabled Digital Twin project aimed at creating a dynamic virtual representation of port operations. The initiative is designed to combine real-time operational data with AI to support predictive planning and data-driven decision-making. JNPA has appointed ATAI as an advisor to provide strategic and technical guidance for the project.
 

🖥️ More than a visual replica
 

The digital twin is intended to mirror key activities across the port and provide planners with a live operational picture.
 

JNPA says the initiative will support areas including sea-side and land-side operations, environmental management, safety and hinterland connectivity. It is also intended to bring stakeholders such as shipping lines, terminal operators, customs, transporters and container freight stations into a more synchronised, data-driven framework.
 

🚢 Simulating port operations
 

One of the key advantages of a digital twin is the ability to test operational scenarios virtually before implementing changes in the physical port.
 

For JNPA, this could support analysis of vessel movements, yard planning, equipment utilisation, congestion and hinterland connectivity. By modelling different scenarios, planners can identify potential bottlenecks and evaluate how operational changes could affect the wider port ecosystem.
 

The project is therefore moving the digital twin concept beyond simple visualisation toward simulation and decision support.
 

🤖 AI adds the predictive layer
 

The AI/ML component is particularly important.
 

JNPA describes the technology as enabling predictive planning and data-driven decision-making, allowing the port to anticipate operational requirements rather than relying only on historical or manually reported information.

This builds on JNPA's wider digitalisation programme. The port has already introduced a digital Harbour Management System integrating vessel scheduling, pilotage data, resource allocation, IoT inputs, safety monitoring and sustainability information. Its Pilot Thagaval app also digitally captures vessel-movement and pilotage data.

These connected data sources can provide an important foundation for a digital twin.

📊 From data to operational decisions

The potential workflow is straightforward:

Real-time port data → Digital twin → AI analysis → Scenario simulation → Predictive insight → Operational decision

For example, planners could potentially evaluate how changes in vessel arrivals, yard utilisation or landside movements might create congestion before the issue occurs.

This could help improve coordination between different parts of the port rather than optimising each operation independently.

🌐 Why this matters

JNPA handled a record 8.17 million TEUs in FY 2025-26, along with 102 million tonnes of overall throughput, according to the Ministry of Ports, Shipping and Waterways. At that scale, even relatively small improvements in planning and coordination can have significant operational implications.

The digital twin initiative also fits into JNPA's broader push toward technology-driven port management,
which includes its indigenous Harbour Management System, iVTS and AI-driven tools such as NIVIDA.

🔮 The bigger trend

Ports are increasingly moving from digitising individual processes to creating connected digital representations of the entire operation.

A traditional dashboard tells operators what is happening.

A digital twin can help them understand why it is happening, what could happen next and what may happen if they change something.

For JNPA, the ambition is to make port operations more predictive, coordinated and data-driven.

The digital twin is evolving from a virtual model of the port into a virtual environment for testing decisions before they impact the real port.