TTD’s AI to redefine devotees’ experience of Tirumala darshan
TIRUPATI: Tirumala Tirupati Devasthanams (TTD) has announced plans to integrate Artificial Intelligence (AI) and advanced technologies to streamline management of darshan at the Sri Venkateswara Swamy Temple in Tirumala.
The initiative, currently in its planning phase, aims to significantly reduce waiting times of 20–30 hours to just 2–3 hours and improve crowd management, providing a seamless darshan for devotees.
The decision to integrate AI stems from the first board meeting chaired by TTD chairman B.R. Naidu. It has set rolling detailed studies and collaborations with experts in artificial intelligence and industry leaders to ensure robust implementation of artificial intelligence.
Leveraging state-of-the-art AI solutions, the Devasthanam plans to address challenges, such as managing high pilgrim footfalls, real-time crowd control and dynamic slot allocation.
TTD executive officer J. Syamala Rao told Deccan Chronicle: "Our primary focus is on leveraging accurate, real-time data to monitor the hourly inflow and outflow of devotees. This information will serve as a critical input for developing robust predictive models and enhancing operational efficiency."
In this regard, TTD has partnered with Jio Things to conduct an in-depth study using an AI-based system and cameras. These will identify hourly visitor counts and pinpoint peak and lean periods throughout the day. The overarching goal will be to minimise wait times in physical queue lines and compartments.
"Rather than subjecting devotees to physical waiting, the system will be designed to facilitate their arrival during pre-assigned time slots," EO Syamala Rao disclosed. This will involve advanced computational modelling and scientific analysis of variables, such as crowd density, flow rates and peak visitation patterns. The process is highly intricate, with leveraging of data-driven insights and predictive algorithms.
Experts say the AI-based framework will also comprise facial recognition systems, automating identity verification for ticketed pilgrims, expediting entry by eliminating manual checks. For dynamic slot allocation, AI algorithms will analyse real-time crowd density data to optimise schedules and reduce bottlenecks.
The system will include integration of pilgrims’ mobiles for enhanced communication. A centralised platform will notify pilgrims via SMS or mobile apps about their darshan slots, estimated waiting times, and directions to designated entry points.
The AI system will operate on a multi-layered architecture. At its core, the Data Layer will aggregate historical and real-time data from surveillance cameras, RFID trackers, and ticketing systems. Such data will provide a foundational understanding of crowd patterns and temple traffic flow.
The Processing Layer will employ advanced machine learning models to analyse patterns, predict potential surges, and recommend optimal scheduling strategies. This will ensure precise, data-driven decisions made in real time. Finally, the Output Layer will transform insights from the processing stage into actionable directives.
Prof. S. Ramesh, an AI expert, says: “Real-time crowd analytics and automation are game changers. They minimise human intervention, while ensuring efficiency and scalability, particularly during peak seasons.”
However, the AI initiative raises concerns about data privacy and cybersecurity. “Given the volume of personal and biometric data involved, TTD must implement strict encryption protocols and ensure compliance with privacy regulations,” said Dr. Priya Kulkarni, a data governance expert.
If successful, TTD’s model could serve as a benchmark for large-scale pilgrim management systems at other heritage sites worldwide. “By adopting AI, we aim to create a paradigm shift in temple management. This initiative aligns with our commitment to improving pilgrim experience without compromising the sanctity of darshan,” EO Syamala Rao affirmed.
