What is it about?
The Mobile Tourism Recommendation System is designed to help tourists discover the best attractions in a city based on their preferences, profile, and interests. This system uses machine learning algorithms to offer personalized recommendations and plans for tourists. The system operates in two main stages: Recommender System: It generates a list of city attractions likely to interest the user. This list is created by considering the user’s demographic classification, past travel preferences, and current visit interests. Machine learning algorithms such as K-nearest neighbors (K-NN) and decision trees are employed to analyze and predict user preferences effectively. Planning Module: Once the recommended places are identified, the planning module schedules visits according to the characteristics of the attractions and the user's constraints. It determines the optimal timing and sequence of activities. To enhance accessibility, especially for blind users, the application provides complete voice assistance and simple navigation via button clicks. Vibratory and voice feedback alerts are included for accurate crash detection. The integration of Android and Internet of Things (IoT) technologies adds smart features to the application. The system aims to be a low-cost, reliable solution to help visually impaired individuals navigate and explore using smartphone technology. It addresses variables such as food options, cleanliness, and opening times of tourist spots. The recommendation process also considers the travel history of the user. The study employs a cross-planning table methodology, combining factors like area popularity, ratings, latent points, and user feedback to optimize recommendations. Algorithms like Latent Dirichlet Allocation (LDA) and Support Vector Machines (SVM) enhance the system’s performance. Ultimately, this project aims to support businesses related to tourism by providing a user-friendly planning tool for tourists.
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Why is it important?
The Mobile Tourism Recommendation System is important for several reasons: Personalized Tourist Experience: Tailored Recommendations: By leveraging machine learning algorithms, the system provides customized suggestions that match a tourist’s preferences, making their experience more enjoyable and relevant. Enhanced Planning: The planning module schedules activities efficiently, helping tourists make the most of their time in a city by optimizing their itinerary based on their interests and constraints. Accessibility for the Visually Impaired: Voice Assistance: Complete voice assistance allows blind users to navigate the system easily. Safety Features: Vibratory and voice feedback provide accurate alerts to prevent crashes, making the application safe and reliable for visually impaired individuals. Affordability: By offering a low-cost solution, the system makes advanced navigation technology accessible to a broader audience, including those who might not afford expensive specialized devices. Integration of Advanced Technologies: Android and IoT Support: The incorporation of Android and Internet of Things (IoT) technologies adds smart features that enhance the functionality and user experience of the application. Support for Tourism Businesses: Business Growth: By providing a tool that enhances the tourist experience, businesses related to tourism can benefit from increased customer satisfaction and potentially higher foot traffic. Data-Driven Insights: The system’s use of various data points (like area popularity, ratings, and user feedback) offers valuable insights that can help businesses tailor their offerings to meet tourist demands. Comprehensive Tourist Information: Variable Consideration: The system takes into account factors such as food options, cleanliness, and opening times, ensuring tourists receive comprehensive and practical recommendations. Travel History Utilization: By considering the user’s travel history, the system can provide more accurate and relevant suggestions, enhancing repeat tourist experiences. Overall, the Mobile Tourism Recommendation System enhances the travel experience for tourists, supports visually impaired individuals, and aids tourism-related businesses, contributing to a more inclusive and efficient tourism ecosystem.
Perspectives
The Mobile Tourism Recommendation System offers various perspectives on its significance and impact: Tourist Perspective: Enhanced Experience: Tourists receive personalized recommendations based on their interests and previous travel experiences, making their trips more enjoyable and memorable. Efficient Planning: The system helps tourists make the most of their time by providing well-organized itineraries that consider opening times, distances, and personal constraints. Accessibility: For visually impaired tourists, the voice assistance and safety features (like vibratory feedback) make travel more accessible and safe, enabling them to explore new places with greater independence. Business Perspective: Increased Customer Satisfaction: Tourism businesses can benefit from higher customer satisfaction as tourists are guided to attractions that match their preferences, leading to positive experiences and reviews. Targeted Marketing: Businesses can use insights from the system to tailor their marketing strategies, focusing on the attractions and services that are most popular with different demographic groups. Operational Efficiency: Understanding peak times and tourist preferences can help businesses optimize their operations, ensuring they are adequately staffed and stocked during busy periods. Technological Perspective: Machine Learning Application: The use of algorithms like K-NN, decision trees, LDA, and SVM demonstrates the practical application of machine learning in enhancing user experiences and making data-driven decisions. Integration of IoT: Incorporating IoT technology showcases the potential for smart environments and connected devices to improve tourism services, offering real-time data and interactions. Advancements in Accessibility: The system highlights how technology can be used to create inclusive solutions, particularly for individuals with disabilities, demonstrating a commitment to universal design principles. Social Perspective: Inclusivity: By providing a low-cost, accessible solution for visually impaired individuals, the system promotes social inclusivity and equal access to travel experiences. Cultural Exchange: Enhanced travel experiences foster greater cultural exchange and understanding as tourists can explore a wider range of attractions tailored to their interests. Community Engagement: The system can encourage local communities to improve and maintain their attractions, knowing that they are more likely to be visited and appreciated by tourists. Economic Perspective: Tourism Growth: Improved tourist experiences can lead to increased tourism traffic, benefiting local economies and generating revenue for businesses and municipalities. Job Creation: The growth in tourism can create jobs in various sectors, from hospitality and transport to retail and cultural services. Sustainable Development: By optimizing tourist flows and reducing overcrowding at popular sites, the system can contribute to more sustainable tourism practices, spreading the economic benefits more evenly. Future Development Perspective: Scalability: The system can be expanded to cover more cities and regions, providing personalized recommendations on a global scale. Enhanced Features: Future iterations could include augmented reality (AR) for enhanced navigation and exploration, multilingual support for international tourists, and integration with other travel services like accommodation and transport. Data Privacy: As the system collects and analyzes personal data, ongoing attention to data privacy and security will be crucial to maintain user trust and comply with regulations. In summary, the Mobile Tourism Recommendation System has the potential to transform the travel experience from multiple perspectives, enhancing satisfaction, accessibility, economic impact, and technological innovation.
VIDHUSHAVARSHINI S
Sona College of Technology
Read the Original
This page is a summary of: Mobile Tourism Recommendation System for Visually Disabled, August 2023, Bentham Science Publishers,
DOI: 10.2174/9789815136746123010013.
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