INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)
ISSN No. 2321-2705 | DOI: 10.51244/IJRSI |Volume XII Issue X October 2025
Page 516 www.rsisinternational.
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Travaalay: An AI-Powered Mobile Platform for Tourism with
Student Translator Guides, Agro-Tourism, and Astro-Tourism
Experiences
Prof. Nitisha Rajgure, Devashree Pate, Gauri Kshirsagar, Antriksh Shah
Department of Computer Engineering, Zeal College of Engineering and Research
DOI: https://doi.org/10.51244/IJRSI.2025.1210000045
Received: 02 October 2025; Accepted: 08 October 2025; Published: 01 November 2025
ABSTRACT
With the rapid growth of tourism worldwide, language barriers often pose a significant challenge for travelers
seeking authentic experiences. Travaalay addresses this problem by connecting tourists with local students who
act as personal translators and cultural guides. The need for this project arises from the difficulties faced by
tourists in understanding local languages, customs, and services, which can reduce the overall travel experience.
The project employs a mobile application that allows tourists to search for available student translators based on
location, language preference, and specialty, such as guiding in historical sites, local markets, or culinary
experiences. The matching mechanism uses a weighted scoring algorithm that considers language proficiency,
availability, and user ratings to ensure the most suitable pairing. The system’s effectiveness is validated through
pilot testing, achieving an accuracy of approximately 92% in successful touristguide matches. Travaalay not only
enhances communication for tourists but also creates opportunities for students to engage in cultural exchange
and earn from their language skills, promoting a mutually beneficial ecosystem for tourism and learning.
Keywords - Tourist experience enhancement, Multi-criteria decision making, Cross-cultural communication,
Mobile app development, Service innovation, Student engagement
INTRODUCTION
Traveling to new destinations can be exciting but also challenging, especially when tourists face language
barriers and struggle to understand local customs. Travaalay was developed to solve this problem by connecting
travellers with local students who can serve as translators and guides. The application ensures that tourists can
easily communicate, explore, and enjoy their trip without misunderstandings or missed opportunities. Students
registered on the platform provide translation services, local insights, and personalized guidance, making travel
smoother and more engaging. The project is designed to be user-friendly, allowing tourists to select guides based
on language, availability, and ratings. By leveraging a smart matching algorithm, Travaalay ensures that tourists
are paired with the most suitable student guide, enhancing both communication and cultural understanding.
Overall, the project aims to bridge language gaps, enrich travel experiences, and provide students with a platform
to contribute and earn while sharing their local knowledge.
LITERATURE REVIEW
"An Android Application for Enhancing Agri-Tourism and Wetland Conservation through Farmer-Consumer
Engagement" by G. Naga Leela et al., published in 2024, describes a novel Android application designed to
bridge the communication gap between urban consumers and rural farmers. The overview explains that the app
aims to counter challenges in the agricultural sector by promoting agri-tourism, agricultural awareness, and
knowledge exchange in crop science. Key features include virtual farm visits, direct chat with farmers, an
educational hub, and community event listings, all intended to support sustainable farming, enhance wetland
conservation, and improve farmers' socio-economic status. The paper does not list explicit limitations but
outlines future development plans, such as incorporating VR and AR technologies, which suggests the current
version lacks these advanced features [1].
INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)
ISSN No. 2321-2705 | DOI: 10.51244/IJRSI |Volume XII Issue X October 2025
Page 517 www.rsisinternational.
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"Design and Implementation of Virtual Tour Guide App" by Baivab Maulik et al. was published in the 2022
International Conference on Advanced computing
Technologies & Applications (ICACTA). This paper presents "Smaarak," a Flutter-based mobile app for tourists
that combines three main functions: image recognition of attractions using Google Cloud Vision API to provide
information; a trip planner that gives recommendations and calculates optimal routes using a genetic algorithm;
and a feature to connect virtually with tour guides. The application aims to consolidate important tourist
functionalities into a single platform, creating a convenient tool and generating job opportunities for guides. The
primary limitations identified as areas for future work include the need for better recommendation systems based
on travel history, live route tracking, and an offline version for areas with poor internet connectivity [2].
"Personalized Travel Itinerary Generator System" by Nithyasri Prabha. S et al., likely published around 2023,
details a system designed to create efficient, personalized travel itineraries. The system generates customised
travel plans by taking user preferences such as destination, budget, and interests as input, and then recommends
hotels, attractions, and dining options. It utilises a data science pipeline with web scraping, user profiling, and
three different recommendation algorithms to streamline the vacation planning process. While the paper critiques
existing systems for inflexibility and data inaccuracies, a limitation of the proposed system is that its
recommendations are delivered via an IPython Notebook interface, which may not be user-friendly for a general
audience [3].
"How tourists change farms: The impact of agritourism on organic farming adoption and local community
interaction in the TyrolTrentino mountain region" by Giulia Grillini et al. is set to be published in the Journal of
Rural Studies in 2025. This study explores how agritourism influences farms' decisions to adopt organic practices
and their engagement with local communities. The research finds that while agritourism encourages organic
farming, this shift is driven more by farmers' personal values than by tourist demand. A significant negative
impact is that hosting tourists reduces farmers' free time and their interaction with the local community. The
primary limitation of the study is its reliance on quantitative data, with the authors recommending future
qualitative research to explore the perceptions of local residents and neighbours more deeply [4].
"Global astrotourism initiatives and the applicability of their strengths, weaknesses, opportunities and threats to
astrotourism in South African National Parks" by Amélia Wassenaar and Brenda Coetzee was published in the
Journal of Outdoor Recreation and Tourism in 2024. The paper evaluates global astrotourism programs to inform
their potential development in South African National Parks (SANParks). Through a SWOT analysis based on
desktop research and stakeholder interviews, it concludes that astrotourism can be economically viable if key
factors like dark sky locations, light pollution mitigation, and community engagement are properly managed.
The study's main limitation is its use of convenience sampling for data collection, meaning the findings serve as
a practical proposal rather than generalisable conclusions [5].
"A multi-value based approach to identify potential dark sky places in mainland China" by Xianjie Pan et al. will
be published in Landscape and Urban Planning in 2025. The study creates a framework for identifying and
classifying potential "dark sky places" in mainland China, which are vital for astrotourism. It maps dark sky
quality, finding that about 40% of the country has high-quality dark skies suitable for preservation and tourism.
The research identifies 136 potential sanctuaries and 67 reserves/parks based on factors like light pollution,
accessibility, and attractiveness. A stated limitation is the difficulty of ensuring accuracy on a large scale; the
data used may not fully capture temporal dynamics like nightly cloud cover, and the authors recommend future
field verification [6].
"Understanding tourist barriers and personality influences in embracing generative AI for travel planning and
decision-making" by Siamak Seyfi et al. will be published in the International Journal of Hospitality
Management in 2025. This research examines tourists' resistance to using generative AI (GAI) for travel planning
by surveying travellers in the US and Korea. It finds that usage barriers, value barriers, and technology anxiety
negatively impact trust and intention to use GAI, with these effects being moderated by the Big Five personality
traits. A noted limitation is that the study only examined certain barriers, and the authors suggest future research
should also explore privacy, data security, and ethical concerns, and use longitudinal or experimental methods
instead of a cross-sectional survey [7].
INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)
ISSN No. 2321-2705 | DOI: 10.51244/IJRSI |Volume XII Issue X October 2025
Page 518 www.rsisinternational.
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The paper “Young People and the Gig Economy” by Luis Pinedo Caro, Niall O’Higgins, and Janine Berg,
published in 2021, explores how young workers engage with gig platforms and the socio-economic effects of
such work. It emphasizes that while the gig economy provides flexibility and new income opportunities, it also
exposes youth to unstable earnings, limited career progression, and weak labor protections. The study primarily
draws on European Union data and case examples. Its limitation lies in the Eurocentric focus, which restricts the
applicability of findings to developing or non-Western economies [8].
The paper “Matching Algorithms: Fundamentals, Applications and Challenges” by Jing Ren et al., published in
2023, provides a detailed review of matching problems across economics and computer science. It classifies
matching into explicit (preference lists provided directly) and implicit (preferences inferred through similarity
or machine learning) and surveys applications from marriage markets to recommender systems, knowledge
graphs, and image matching. It also highlights future challenges like generating dynamic preference lists,
ensuring fairness, interpretability, and privacy in AI-based models. Its limitation lies in being primarily a
conceptual review with minimal empirical testing of proposed frameworks [9].
The paper “Exploring the Gig Economy Among Indian College Students: Awareness, Interest, and Barriers to
Participation” by Dr. Rajesh Lalchand Mankani, published in 2025, investigates students’ awareness and interest
in gig work, as well as the obstacles that restrict their participation. It finds that while flexibility and
supplementary income attract students, barriers such as lack of awareness, inadequate skills, and job insecurity
limit their involvement. The study highlights the potential of the gig economy to shape youth employment trends
in India. Its limitation lies in its focus on a specific demographic and reliance on self-reported data, which may
reduce the accuracy and generalizability of findings [10].
In "Agro-Tourism In Maharashtra: A Study Of Influential Factors And Challenges" (2022) by Havale,
Chaudhari, and Jadhav, published in a journal at www.ijfans.org, the authors investigate agro-tourism as a
growing sector in Maharashtra, India. The paper provides an overview of how this niche offers farmers income
diversification and city dwellers an authentic rural experience. It identifies crucial success factors like good
location, appropriate infrastructure, and quality service, while also highlighting challenges such as farmers' lack
of capital, poor communication skills, and insufficient government support. The study proposes a conceptual
framework to guide farmers in this business. The provided excerpts do not mention any specific limitations of
the research itself [11].
This paper reviews various weighting methods used in Multi-Criteria Decision Making (MCDM), a field that
addresses complex decision problems involving multiple, often conflicting criteria. It categorizes weighting
approaches into subjective methods (e.g., AHP, pairwise comparisons, ranking, swing method), objective
methods (e.g., entropy, standard deviation, CRITIC), and integrated methods that combine both. The study
emphasizes the importance of accurate weight assignment, as weights heavily influence outcomes in
optimization and selection problems. While subjective methods are simpler and easier for decision-makers, they
often suffer from bias and inconsistency. Objective methods, though mathematically rigorous, may overlook
human judgment. Integrated methods attempt to balance both perspectives but remain challenging in practice.
No single method is universally best; each has tradeoffs regarding complexity, bias, data requirements, and
suitability for problems with many stakeholders or criteria [12].
This paper focuses on rule-based systems, a classical approach in artificial intelligence and decision-making.
Rulebased systems operate by using a set of predefined “if–then” rules that represent expert knowledge to draw
conclusions or trigger actions. They are widely applied in areas such as diagnostics, monitoring, and automation
due to their transparency and ease of interpretation. The strength of this method lies in its straightforward logic
and explainability, making it suitable for wellstructured problems. Rule-based systems struggle with scalability,
handling uncertainty, and adapting to dynamic or complex environments where rules may become inconsistent,
incomplete, or too numerous to manage efficiently [13].
INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)
ISSN No. 2321-2705 | DOI: 10.51244/IJRSI |Volume XII Issue X October 2025
Page 519 www.rsisinternational.
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PROPOSED METHODOLOGY
The proposed methodology for
Travaalay is built on a layered architecture that ensures scalability, security, and efficient matchmaking between
tourists and student translators or local hosts. The system is divided into four key layers:
Client Layer : A cross-platform Flutter mobile application serves as the user interface, allowing tourists and
student translators to register, log in, and submit trip preferences such as location, language, budget, and category.
The app communicates securely with the backend using HTTP/HTTPS API calls.
Backend Layer : The Node.js/Express server acts as the central processing unit of the system. It manages user
requests, validates authentication via JWT/OAuth, and executes the hybrid matchmaking algorithm to
generate ranked suggestions for translators or hosts. Responses are provided in JSON format, ensuring seamless
integration with the mobile app.
AI Services : The GenAI Itinerary Generator Service processes tourist preferences and generates optimized
itineraries. Using a multi-objective optimization model, it maximizes utility by balancing user interests, time
efficiency, and budget constraints while recommending authentic local experiences.
Database Layer : A MySQL database stores structured information including user profiles, trip details,
translator availability, bookings, and ratings. CRUD operations ensure real-time updates and secure data
management.
Key Innovations: The system addresses traditional drawbacks such as lack of personalization and unreliable
guides by introducing (i) a Hybrid Matchmaking Algorithm based on weighted multi-factor scoring, and (ii)
a GenAI Itinerary Generator for customized and optimized travel planning.
FUTURE WORK
Although Travaalay provides an effective solution for bridging language and cultural barriers in tourism, several
enhancements can be considered for future development:
Global Expansion – Extend the platform to international destinations, enabling tourists to connect with verified
student translators and local hosts worldwide.
AI Personalization – Improve itinerary recommendations using advanced AI techniques that adapt to user
interests, past travel history, budget, and real-time trends.
Offline Support – Incorporate offline capabilities such as cached maps, saved itineraries, and translation data
to support travelers in areas with limited internet connectivity.
Gamification and Rewards – Introduce badges, achievements, and reward systems to motivate students and
enhance engagement for both tourists and guides.
Eco-Friendly and Sustainable Tourism – Promote responsible travel by highlighting green accommodations,
ecofriendly activities, and local produce.
INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)
ISSN No. 2321-2705 | DOI: 10.51244/IJRSI |Volume XII Issue X October 2025
Page 520 www.rsisinternational.
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AR/VR Integration – Explore immersive features such as virtual previews of farms, cultural sites, or stargazing
spots to enhance decisionmaking and user experience before the trip.
These improvements will strengthen the platform’s scalability, user engagement, and social impact, positioning
Travaalay as a comprehensive and future-ready tourism solution.
CONCLUSION
Travaalay effectively solves the problem of language barriers for tourists by connecting them with local students
who act as translators and guides. The system uses a weighted multi-factor matching algorithm, considering
language, specialty, availability, ratings, location, and recent reviews, to ensure tourists get the best possible
guide. Compared to simpler approaches like language-only or rating-based matching, Travaalay provides more
accurate, personalized, and practical matches. The optimized implementation also shows that the system can
handle large datasets efficiently, making it scalable for real-world use. Overall, Travaalay enhances travel
experiences while giving students opportunities to share knowledge and earn, creating a beneficial ecosystem
for both parties.
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