High Altitude Trek Prediction and Gear Renting Platform
Year: 2025
Type: article
Abstract: Trekking is a popular outdoor activity that offers both physical challenge and the opportunity to connect with nature. However, selecting the right trekking route that matches an individual's experience level, physical ability, and personal preferences can be a daunting task. This paper presents a comprehensive trekking recommendation system designed to assist outdoor enthusiasts in discovering suitable trekking routes and gear renting system. The system leverages a combination of user inputs, such as desired difficulty level, location, duration, along with data on existing trekking trails. Advanced algorithms and machine learning techniques are employed to analyze these inputs and provide personalized recommendations. The system also considers factors like health tracking which makes wonderful trekking experience. The aim of this project is to create an intelligent and user-friendly platform that not only encourages safe and enjoyable trekking experiences but also promotes eco-friendly tourism by recommending lesser-known trails, thereby reducing the impact on overcrowded popular routes. It also promotes a gear renting platform too.This paper details the development process, the challenges faced, and the potential impact of the system on the trekking community.
Authors: Dr. Devidas Thosar, Dr. Rachna Sable, D .Vaishali Baviskar, Sanyukta Yelnare, Neha Kakade, Harneet Kaur Arora
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6912409060
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