As India accelerates toward building smarter highways and future-ready transport infrastructure, Arya Omnitalk is positioning itself at the forefront of this transformation with cutting-edge tolling and traffic management solutions. At the heart of this shift is the adoption of Multi-Lane Free Flow (MLFF) technology, which promises to make boothless, seamless tolling a reality for millions of daily commuters. In an exclusive interaction with Machine Edge Global, Anuresh Sharma, COO of HTMS at Arya Omnitalk, shares insights into how the company is leveraging AI, predictive analytics, and intelligent transport systems to reimagine the future of mobility—while also preparing to take Indian innovation to global markets.
How is Arya Omnitalk reimagining the future of tolling in India through MLFF (Multi-Lane Free Flow) technology?
Arya Omnitalk envisions MLFF (Multi-Lane Free Flow) as the transformative next step in India’s tolling evolution. We do this by moving away from the current stop-and-go FASTag booths and moving toward MLFF, which enables seamless tolling as the vehicles no longer need to halt. Using RFID-based FASTag readers along with AI-powered Automatic Number Plate Recognition (ANPR) systems, vehicles are identified in motion, and the toll amount is debited from their linked account. This technology not only streamlines toll collection but lays the foundation for intelligent transport systems (ITS), where such real-time data can later be leveraged for speed enforcement, route planning, and traffic analytics.
How does MLFF differ from conventional tolling systems, and why is it the need of the hour for India’s growing network of expressways and high-traffic highways?
Unlike conventional tolling systems that rely on physical booths that force vehicles to slow down or stop, MLFF allows for uninterrupted vehicular movement at highway speeds. Vehicles are charged in real time through FASTag and ANPR validation, which reduces congestion and travel time caused by long queues at the tolling booths. As India rapidly expands its expressway infrastructure and traffic volumes continue to grow, MLFF emerges as a critical upgrade which offers speed, efficiency, and environmental benefits. Furthermore, it enhances user experience and supports the scalability required for future-ready infrastructure.
Could you elaborate on how AI and predictive analytics are integrated into Arya Omnitalk’s toll management systems? How do these tools support real-time decision-making and traffic optimization?
Arya Omnitalk has integrated AI and machine learning into multiple components of its toll and traffic management systems. Our Automatic Vehicle Classification (AVC) system uses infrared or laser sensors to create real-time vehicle profiles, which are then processed through AI/ML algorithms to determine the class of each vehicle with high precision in real time. Our in-house ANPR solution, powered by AI, ensures accurate vehicle recognition for tolling and enforcement. To add to this, we are also developing AI-driven Vehicle Incident Detection (VID) systems to monitor traffic anomalies and enhance safety on the road. Together, these technologies support real-time decision-making, enable dynamic traffic control, and improve operational efficiency across high-volume corridors.
India saw the wide adoption of FASTag in recent years. How has FASTag laid the foundation for MLFF, and what technological upgrades are necessary to complete this transition?
FASTag has played a pivotal role in digitizing tolling in India and building user familiarity with automated payment systems. Previously, the tolling system was completely cash-based, and now, people are used to maintaining a FASTag balance. But current systems are based on stop-and-go booth setups, the shift to MLFF retains FASTag as a core vehicle identifier but adds high-speed RFID reading and ANPR to ensure accuracy even in free-flow environments. This means the existing systems get a key upgrade, including high-resolution cameras, enhanced data processing units at toll zones, and robust integration between edge devices and central servers. Arya Omnitalk’s systems are already built to handle this transition seamlessly, and we look at the leap to MLFF as a natural evolution from FASTag’s existing ecosystem.
What are the main operational or technical challenges when shifting from booth-based tolling to MLFF systems—especially in terms of interoperability, connectivity, and enforcement?
One of the most pressing challenges is enforcement, vehicles with insufficient balance, no FASTag, or blacklisted tags may bypass tolls, and recovering those dues remains complex despite provisions for e-Challan. Infrastructure is another hurdle, as many toll plazas lack robust connectivity or power backup which is essential for the system to run efficiently.. Arya Omnitalk has recommended a cloud-based MLFF architecture to solve scalability and infrastructure constraints, but current mandates still emphasise on-premise solutions in our country. Interoperability with banks, acquirers, and enforcement agencies also requires secure data transmission protocols, which our platform fully adheres to using industry-grade encryption and communication standards.
What role do parking management and fleet management solutions play in Arya Omnitalk’s broader intelligent transportation ecosystem?
Arya Omnitalk’s vision extends beyond tolling to provide future-proof solutions for the entire mobility landscape. Our intelligent transport solutions include parking management systems that utilise ANPR and ticketless entry-exit models, enhancing urban traffic flow and reducing congestion and time waste. Similarly, our fleet management offerings enable logistics providers and government fleets to monitor vehicle health, driver behaviour, and route efficiency in real time. These components, when integrated with our tolling backbone, help create a unified, tech-driven mobility ecosystem. It becomes one that supports smarter cities, efficient logistics, and safer roadways.
Do you foresee a future where India’s tolling system becomes completely boothless? If yes, what’s the timeline and roadmap to achieving that?
Yes, we at Arya Omnitalk envision a future where tolling in India is completely boothless. The MLFF model is the immediate next step, but the ultimate goal is GNSS (Global Navigation Satellite System)-based tolling where users pay only for the exact distance travelled. While GNSS-based tolling is still three to four years away, India is already exploring its indigenous satellite navigation system, NAVIC, to power this transformation. With the right policy support, infrastructure upgrades, and phased tech deployment, India could begin piloting boothless, distance-based tolling within the next half-decade or so.
Finally, what are Arya Omnitalk’s expansion plans, particularly in emerging markets beyond India? Are you exploring global opportunities for your tolling and traffic management technologies?
Absolutely, we at Arya Omnitalk sees significant potential in emerging economies across Africa and South Asia where tolling infrastructure is still in its early stages. We have already exported our Automatic Vehicle Classification system to France-based Egis, and it has been successfully deployed in Uganda as well. We believe our scalable, modular toll and traffic management solutions are ideal for developing regions seeking robust, cost-effective ITS deployments. We are actively exploring opportunities in Bangladesh, Nepal, and Sri Lanka, and look forward to bringing Indian innovation to global mobility challenges.