Smart Travel Planner

Artificial intelligence (AI) has revolutionized travel planning by automating itinerary generation, optimizing routes, and personalizing travel experiences. AI-powered trip planners integrate machine learning (ML), natural language processing (NLP), and real-time data analytics to recommend destinations, accommodations, and activities based on user preferences. These systems address common travel concerns, such as budget constraints, time limitations, and changing travel conditions. Various approaches, including large language models (LLMs), automated planning algorithms, recommendation engines, and hybrid AI systems, have been explored to improve travel efficiency. AI-powered tools can enhance user satisfaction by providing real-time updates on flights, hotels, and transportation, ensuring a seamless travel experience. However, challenges remain in achieving real-time adaptability, data accuracy, constraint satisfaction, and seamless integration with multiple travel platforms. Keywords—Chatbot, Artificial Intelligence (AI), Machine learning (ML), Travel automation, Smart Travel Assistant

Authors

Publication Details

Journal
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Published
2025-03-14
DOI
https://doi.org/10.55041/ijsrem42872
Citations
1
Primary Topic
Digital Marketing and Social Media
Type
article
Field-Weighted Citation Impact
4.20
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article

Smart Travel Planner

Nilam Honmane, Pratik Bagal, Jagdish Butte, Rohan Gogawale et al.
1 citations
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Digital Marketing and Social Media
4.20
article

Smart Travel Planner

Nilam Honmane, Pratik Bagal, Jagdish Butte, Rohan Gogawale, Mahesh Indalkar
article en
1 citations

Abstract

Artificial intelligence (AI) has revolutionized travel planning by automating itinerary generation, optimizing routes, and personalizing travel experiences. AI-powered trip planners integrate machine learning (ML), natural language processing (NLP), and real-time data analytics to recommend destinations, accommodations, and activities based on user preferences. These systems address common travel concerns, such as budget constraints, time limitations, and changing travel conditions. Various approaches, including large language models (LLMs), automated planning algorithms, recommendation engines, and hybrid AI systems, have been explored to improve travel efficiency. AI-powered tools can enhance user satisfaction by providing real-time updates on flights, hotels, and transportation, ensuring a seamless travel experience. However, challenges remain in achieving real-time adaptability, data accuracy, constraint satisfaction, and seamless integration with multiple travel platforms. Keywords—Chatbot, Artificial Intelligence (AI), Machine learning (ML), Travel automation, Smart Travel Assistant

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTVol. 09(03)
Openalex Percentile: Top 9%
Digital Marketing and Social Media
4.20
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Smart Travel Planner — Nilam Honmane, Pratik Bagal, et al. · INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT (2025) | TGRS Research Map | TGRS