Abdul Wahab Khan
Panaji
Goa’s pristine beaches, misty hills of Shimla, Manali’s mountain landscapes and Jaipur’s heritage monuments are buckling under unprecedented tourist pressure, but an artificial intelligence (AI) system may offer a solution.
A team of six researchers from Indian institutions has developed a data-driven sustainable preservation approach that promises to transform how the nation manages its most vulnerable tourist destinations.
The research, published in the 2025 2nd International Conference on Multidisciplinary Research and Innovations in Engineering (MRIE), introduces SPEAR (Sustainable Preservation using Environmental Analytics and Regulation) algorithm, which has demonstrated precision in forecasting environmental stress zones.
The study examined “Shimla, Manali, Goa and Jaipur” – four high-pressure locations that the researchers describe as “confronting particular difficulties such as water scarcity, congestion, business development, environmental degradation and heritage erosion.”
The researchers started on the project after identifying that “Indian intellectual and policy research regarding over-tourism is limited”. Their work addresses tourism industry growth over the past two decades, “propelled by heightened internal travel, global interest in heritage and artistic tourism and governmental efforts like Incredible India and Dekho Apna Desh”.
However, the paper notes that “this rise has produced substantial economic advantages but has also resulted in over-tourism, especially in ecologically vulnerable, culturally affluent and infrastructurally constrained areas”.
The situation at these destinations has reached critical levels. According to the research, “locations such as Shimla, Manali, Goa and regions of Rajasthan and Northeast India are experiencing seasonal surges in tourist influx that exceed their storing capacities, resulting in ecological deterioration, strain on government facilities, movement of residents, commercialisation of culture, and escalating social tensions”.
The team conducted fieldwork, administering “structured surveys to over 400 participants, encompassing tourists, local residents and tourism-related enterprises across four case study locations”.
The primary research was complemented by in-depth conversations with government representatives, environmental activists and tourism industry professionals.
The SPEAR framework represents a breakthrough in environmental monitoring. As described in the paper, “The SPEAR method utilises IoT sensors and remotely sensed data for tracking environments in real time, employing convolutional LSTM networks for sophisticated spatial predictions.” The system’s innovation lies in its ability to calculate an Environmental Degradation Index whilst “using past and live data to forecast upcoming stress zones”.
The results proved exceptional. The researchers conclusively state: “Compared to every other approach tested in the study, the proposed SPEAR technique attained an overall accuracy of 93.2%. Among the methods that were tested, it showed the most reliability.”
When measured against traditional machine learning models, SPEAR’s performance metrics demonstrated a Mean Squared Error of just 0.010 and Root Mean Squared Error of 0.098, “indicating its capability for generating highly accurate and stable predictions”.
The findings paint a troubling picture of current conditions. “The findings indicate problems stemming from over-tourism and mismanagement, resulting in an imbalanced economic benefit, intellectual and cultural disruption, and severe environmental damage,” the paper states.
Contributing factors include “a lack of interaction among stakeholders, inadequate facility design and unchecked marketing of tourism”.
The study suggests using capacity-building estimates that are appropriate to each site, changing policies, promoting tourism within communities, and improving infrastructure.
The researchers advocate for what they describe as “an important change in Indian tourism strategy, transitioning from growth-centric to sustainability-driven, to prevent irrevocable destruction of India’s most recognisable landscapes and populations”.
The multi-institutional team comprised Dr Geetha Manoharan from SR University’s School of Business, Warangal, alongside Suresh N from SRM University Sikkim’s School of Hospitality and Tourism Studies, Dr Amar Prakash Dabral from Graphic Era Deemed University Dehradun, Avnish Sharma from GLA University Mathura, Auadhati Datta from Vignan’s Institute of Information Technology Duvvada and Mohit Tiwari from Bharati Vidyapeeth’s College of Engineering, Delhi.
