DOI : https://doi.org/10.18517/ijaseit.14.6.11985

Enhancing Travel Planning Efficiency with a Comprehensive TripEase GenAI Mechanism

Zhi-Sheng Lim (1), Asmar Yulastri (2), Sin-Ban Ho (3), Chuie-Hong Tan (4)
(1) Faculty of Computing and Informatics, Multimedia University, Cyberjaya, Malaysia
(2) Entrepreneurship Research Center, Universitas Negeri Padang, Padang, West Sumatera, Indonesia
(3) Faculty of Computing and Informatics, Multimedia University, Cyberjaya, Malaysia
(4) Faculty of Management, Multimedia University, Cyberjaya, Malaysia
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How to cite (IJASEIT) :
Lim , Zhi-Sheng, et al. “Enhancing Travel Planning Efficiency With a Comprehensive TripEase GenAI Mechanism”. International Journal on Advanced Science, Engineering and Information Technology, vol. 14, no. 6, Dec. 2024, pp. 2090-7, doi:10.18517/ijaseit.14.6.11985.
Citation Format :
This paper highlights the trip-easiness generative AI mechanism to simplify domestic and international travel planning through a comprehensive services range based on the users' locations, including itinerary management and car rental. This research focuses on building TripEase GenAI Mechanism with generative artificial intelligence (AI) for a fully-fledged AI-based trip planner web application. This mechanism would function independently in addition to the alternative of seamless integration with another platform, a car rental and travel planning system. This would enhance the overall user experience. Within our TripEase GenAI mechanism, users can effortlessly create personalized recommended itineraries after providing their essential trip details. This mechanism will generate a complete itinerary. The suggested itinerary would accompany a tailored packing list specific to the destination. We are leveraging cutting-edge tools such as LangChain, Semantic Kernel, and ChatGPT to achieve this objective. Our main aim is to revolutionize the travel planning experience by harnessing the power of AI technology. This research is envisioned to provide travelers with a seamless and personalized journey that caters to their individual preferences and needs. This paper outlines the design, evolution, and planning of the TripEase GenAI mechanism. We have laid a strong foundation for a user-friendly travel planning platform through meticulous documentation, thoughtful design, and iterative development. The ultimate goal is to enhance the overall travel planning experience by efficiently enriching imported services such as itinerary management and car rental modules.

G. Rani, J. Singh, and A. Khanna, “Comparative Analysis of Generative AI Models,” in Proc. 2023 International Conference on Advances in Computation, Communication and Information Technology (ICAICCIT), Faridabad, India, 2023, pp. 760–765, doi:10.1109/ICAICCIT60255.2023.10465941.

M. Jovanovic, and M. Campbell, “Generative artificial intelligence: Trends and prospects,” IEEE Computer, vol. 55, no. 10, pp. 107-112, Oct. 2022, doi: 10.1109/MC.2022.3192720.

M. Fu, C. K. Tantithamthavorn, V. Nguyen, and T. Le, “ChatGPT for Vulnerability Detection, Classification, and Repair: How Far Are We?” in Proc. 2023 30th Asia-Pacific Software Engineering Conference (APSEC), Seoul, Republic of Korea, 2023, pp. 632–636, doi: 10.1109/APSEC60848.2023.00085.

D. Tosic, “Artificial Intelligence-driven web development and agile project management using OpenAI API and GPT technology : A detailed report on technical integration and implementation of GPT models in CMS with API and agile web development for quality user-centered AI chat service experience,” Dissertation, Dept. Computer and Elect. Eng., Faculty of Science, Technology and Media, Mid Sweden University, Sweden, 2023, Accessed on: Sept. 30, 2024, [Online]. Available: https://www.diva-portal.org/smash/record.jsf?pid=diva2%3A1764392&dswid=-5946

M. Hamza, S. U. Bazai, M. I. Ghafoor, S. Ullah, S. Akram, and M. S. Khan, “Generative Adversarial Networks (GANs) Video Framework: A Systematic Literature Review,” in Proc. 2023 International Conference on Energy, Power, Environment, Control, and Computing (ICEPECC), Gujrat, Pakistan, 2023, pp. 1–5, doi:10.1109/ICEPECC57281.2023.10209475.

I. J. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio, “Generative adversarial nets,” Advances in Neural Information Processing Systems, vol. 27, pp. 1–9, 2014, Accessed on: Sept. 30, 2024, [Online]. Available: https://papers.nips.cc/paper_files/paper/2014/hash/5ca3e9b122f61f8f06494c97b1afccf3-Abstract.html.

F. Fahimi, Z. Zhang, W. B. Goh, K. K. Ang, and C. Guan, “Towards EEG Generation Using GANs for BCI Applications,” in Proc. 2019 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI), Chicago, IL, USA, 2019, pp. 1–4, doi:10.1109/BHI.2019.8834503.

S. Sajad, S. Dharshika, and M. Meleet, “Music Generation for Novices Using Recurrent Neural Network (RNN),” in Proc. 2021 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES), Chennai, India, 2021, pp. 1–6, doi:10.1109/ICSES52305.2021.9633906.

S. S. Patil, S. H. Patil, A. M. Pawar, R. Shandilya, A. K. Kadam, R. B. Jadhav, and M. S. Bewoor, “Music generation using RNN-LSTM with GRU” in Proc. 2023 International Conference on Integration of Computational Intelligent System (ICICIS), Pune, India, 2023, pp. 1–5, doi: 10.1109/ICICIS56802.2023.10430293.

D. Gangal, and Y. Kadam, “Unleashing the Melodic Potential: Music Generation with Char RNNs,” in Proc. 2023 2nd International Conference on Futuristic Technologies (INCOFT), Belagavi, Karnataka, India, 2023, pp. 1–6, doi:10.1109/INCOFT60753.2023.10425396.

W. X. Zhao, K. Zhou, J. Li, T. Tang, X. Wang, Y. Hou, Y. Min, B. Zhang, J. Zhang, Z. Dong, Y. Du, C. Yang, Y. Chen, Z. Chen, J. Jiang, R. Ren, Y. Li, X. Tang, Z. Liu, P. Liu, J.-Y. Nie, and J. R. Wen, A Survey of Large Language Models. Beijing, China: Gaoling School of Artificial Intelligence and School of Information, Renmin University of China, Sept. 25, 2024, Accessed on: Sept. 30, 2024, [Online] Available: https://arxiv.org/pdf/2303.18223.

L. Fan, L. Li, Z. Ma, S. Lee, H. Yu, and L. Hemphill, “A bibliometric review of large language models research from 2017 to 2023,” ACM Transactions on Intelligent Systems and Technology, pp. 1-25, May 2024, doi: 10.1145/3664930.

J. Huang, and K. C. C. Chang, “Towards reasoning in large language models: A survey,” in Findings of the Association for Computational Linguistics (ACL 2023), pp. 1049–1065, July 9-14, 2023, doi:10.48550/arXiv.2212.10403.

Y. Chang, X. Wang, J. Wang, Y. Wu, L. Yang, K. Zhu, H. Chen, X. Yi, C. Wang, Y. Wang, W. Ye, Y. Zhang, Y. Chang, P. S. Yu, Q. Yang, and X. Xie, “A survey on evaluation of large language models,” ACM Transactions on Intelligent Systems and Technology, vol. 15, no. 3, pp. 1-45, March 2024, doi: 10.1145/3641289.

D. Jeong, O. Y. Kown, and E. Hwang, “Technological convergence of AI across the industrial sectors,” International Journal on Advanced Science, Engineering and Information Technology, vol. 14, no. 4, pp. 1152–1160, 2024, doi: 10.18517/ijaseit.14.4.18077.

O. M. Kılıçlıoğlu, Ş. T. Özçelik and M. T. Yöndem, “Application of ChatGPT in the tourism domain: Potential structures and challenges,” in Proc. 2023 4th International Informatics and Software Engineering Conference (IISEC), Ankara, Turkiye, 2023, pp. 1–4, doi:10.1109/IISEC59749.2023.10390989.

I. A. Wong, Q. L. Lian, and D. Sun, “Autonomous travel decision-making: An early glimpse into ChatGPT and generative AI,” Journal of Hospitality and Tourism Management, vol. 56, pp. 253–263, Sept. 2023, doi: 10.1016/j.jhtm.2023.06.022.

T. B. Brown, B. Mann, N. Ryder, M. Subbiah, J. Kaplan, P. Dhariwal, et al., "Language models are few-shot learners", Proc. 34th Int. Conf. Neural Information Processing Systems, pp. 1877-1901, 2020.

M. Pillai and P. Thakur, “Developing a website to analyze and validate projects using LangChain and Streamlit,” in 2024 2nd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT), Bengaluru, India, 2024, pp. 1493–1501, doi: 10.1109/IDCIoT59759.2024.10467765.

K. Pandya, and M. Holia, “Automating customer service using LangChain: Building custom open-source GPT chatbot for organizations,” in Proc. of the e 3rd International Conference on Women in Science & Technology: Creating Sustainable Career (ICWSTCSC 2023), Anand, Gujarat, India, pp. 1–4, Dec. 28-30, 2023, Accessed on: Sept. 30, 2024, [Online] Available: https://arxiv.org/pdf/2310.05421.

P. Maddigan, and T. Susnjak, “Chat2VIS: Generating data visualizations via natural language Using ChatGPT, Codex and GPT-3 large language models,” IEEE Access, vol. 11, pp. 45181–45193, 2023, doi: 10.1109/access.2023.3274199.

S. B. Lakshmi, R. S. Varshini, R. Mahadevan, and R. C. S. P. Raman, “Comparative study and framework for automated summariser evaluation: LangChain and hybrid algorithms,” arXiv e-prints, arXiv-2310, Cornell University, Ithaca, NY, USA, Oct. 2023, doi:10.48550/arXiv.2310.02759.

R. N. Alfiani, M. Ushada, M. Ainuri, and M. A. F. Falah, “Modeling consumer overall acceptance for traditional spice-based ready-to-drink using artificial neural network and Kansei engineering,” International Journal on Advanced Science, Engineering and Information Technology, vol. 14, no. 4, pp. 1178–1184, 2024, doi:10.18517/ijaseit.14.4.19314.

S. Sharov, S. Chakraborty, A. Zemlianskyi, V. Kolmakova, and T. Prosiankina-Zharova, “Quantitative analysis of online courses for learning the JavaScript programming language,” International Journal on Advanced Science, Engineering and Information Technology, vol. 14, no. 4, pp. 1216–1225, 2024, doi: 10.18517/ijaseit.14.4.19976.

J.-L. Goh, S.-B. Ho, and C.-H. Tan, “Weather-based arthritis tracking: A mobile mechanism for preventive strategies,” Journal of Informatics and Web Engineering (JIWE), vol. 3, no. 1, pp. 210–225, 2024, doi:10.33093/jiwe.2024.3.1.14.

S.-B. Ho, E.-Y. Chew, and C.-H. Tan, “Streamlining Dental Clinic Management for Effective Digitisation Productivity and Usability,” Journal of Informatics and Web Engineering (JIWE), vol. 3, no. 2, pp. 70–85, 2024, doi: 10.33093/jiwe.2023.3.2.5.

W.-X. Ong, S.-B. Ho, and C.-H. Tan, “Enhancing migraine management system through weather forecasting for a better daily life,” Journal of Informatics and Web Engineering (JIWE), vol. 2, no. 2, pp. 201–217, 2023, doi: 10.33093/jiwe.2023.2.2.15.

S. N. Kalid, S.-B. Ho, A. Ibrahim, J. H. N. Azman, S.-J. Tan, and J.-E. Cheong, “Enhancing personalized healthcare with an effective E-Healthcare Management System,” Journal of System and Management Sciences (JSMS), vol. 14, no. 2, pp. 482–497, 2024, doi:10.33168/JSMS.2024.0230.

X.-X. Cho, S.-B. Ho, and C.-H. Tan, “Improving asthma treatment adherence by integrating weather information with responsive web technique,” AIP Conference Proceedings, vol. 3153, 030005, 2024, doi: 10.1063/5.0216655.

G. A. Makho, S.-B. Ho, and I. Chai, “Exploring the potential of artificial intelligence in the medical sector for patient well-being: A review technique,” AIP Conference Proceedings, vol. 3153, 030003, 2024, doi: 10.1063/5.0216651.

M. E. K. K. Khairi, S.-B. Ho, and C.-H. Tan, “Real-time tracking and category filtering of an automated system for trading cards collections,” AIP Conference Proceedings, vol. 3153, 060001, 2024, doi: 10.1063/5.0216659.

R. J. Y. Kok, S.-B. Ho, and C.-H. Tan, “Improving the prediction resolution time for mobile eczema support system,” AIP Conference Proceedings, vol. 3153, 030007, 2024, doi: 10.1063/5.0216658.

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