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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM63560
Volume:
10 |
5 |
May 2026
Pages:
1-5
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
MASTER OF COMPUTER APPLICATIONS
BAPUJI INSTITUTE OF ENGINEERING AND TECHNOLOGY
MASTER OF COMPUTER APPLICATIONS
BAPUJI INSTITUTE OF ENGINEERING AND TECHNOLOGY
The global travel and tourism industry is currently undergoing a significant digital transformation, yet the core experience of planning and managing a trip remains a fragmented, time-consuming, and often. stressful endeavor for the average consumer. Traditional travel planning involves navigating a labyrinth of disjointed platforms—separate applications. for flights, accommodations, local transportation, and itinerary scheduling—resulting in "tab fatigue" and decision. paralysis. This project introduces a groundbreaking AI-Powered Platform for Effortless Travel Planning, Booking, and Management, designed to disrupt the status quo by consolidating the entire travel lifecycle into a single, intelligent ecosystem. At the heart of this platform lies a sophisticated engine driven by Generative Artificial Intelligence (GenAI), Natural Language Processing (NLP), and Machine Learning. (ML) algorithms. Unlike static booking engines that rely on rigid filters, this system functions as a proactive, hyper-personalized digital travel. concierge. By analyzing vast datasets—including historical pricing trends, user behavioral patterns, social media sentiment, and real-time geopolitical or weather data—the platform constructs bespoke itineraries that align perfectly user’s unique psychological profile, budget constraints, and experiential desires. with the. The system moves beyond mere recommendation to autonomous. execution. It features a seamless booking interface capable of reserving multi-modal transport and accommodation instantaneously, powered by robust API integrations with global distribution systems. (GDS) Furthermore, the platform addresses the dynamic nature of travel through real-time itinerary management.
KEYWORDS
The AI-Powered Platform for Effortless Travel Planning, Booking, and Management represents a transformative step forward in the travel technology industry. By successfully integrating Generative AI with robust logistical infrastructure, the project addresses the fundamental inefficiencies of the modern travel experience: fragmentation, time consumption, and lack of personalization. The project has demonstrated that it is possible to move beyond simple aggregators to create a proactive travel assistant that understands human intent. The feasibility study confirms the economic and technical viability of the solution, while the rigorous testing phase ensures a secure and reliable product. The mechanics of booking flights and hotels but fundamentally journey itself, empowering travelers to explore the world with confidence and ease. It bridges the global logistics and the simplicity of a user’s desire to explore, marking a new era of intelligent, user- centric travel. This Project is 30% accuracy.
1. Artificial Intelligence in Tourism: Bulchand-Gidumal, J. (2022). Impact of Artificial Intelligence in Travel, Tourism, and Hospitality. Springer Handbooks. This text provides a foundational understanding of how AI in the tourism sector for recommendation engines. 2. Machine Learning for Predictive Analytics: Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press. A comprehensive resource on the underlying predictive pricing and user behavior analysis. 3. Software Engineering Standards: Sommerville, I. (2015). Software Engineering (10th Edition). Pearson. This book is the primary reference for the software development lifecycle, agile methodologies, and system architecture design principles used in this project. 4. User Experience Design: Norman, D. (2013). The Design of Everyday Things. Basic Books. This reference guides the usability principles and user-centric design philosophy adopted for the platform's interface. 5. Cloud Computing and Microservices: Newman, S. (2015). Building Microservices: Designing Fine-Grained Systems. O'Reilly Media. Used as a reference for designing the scalable, distributed backend architecture of the platform.
Publication Date
5/20/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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