用可穿戴设备和AI实现旅行实时个性化推荐
INDIANA: Personalized Travel Recommendations Using Wearables and AI
- 融合可穿戴数据、位置、天气等多源信息做动态推荐
- 支持游客体验优化与旅游服务改进双目标
- 适合智能旅游、人机交互领域研究者参考
本工作介绍了作为INDIANA平台一部分的个性化旅行推荐系统，旨在通过整合可穿戴设备数据、用户偏好、当前位置、天气预报及活动历史，为游客提供实时、上下文感知的个性化活动建议。该平台不仅帮助个体游客最大化旅行体验，还为旅游专业人士提供服务优化洞察。通过集成AI、物联网和可穿戴分析等现代技术，实现了旅行者无缝、个性化且互动性强的体验。
原文摘要 · Abstract (English)
This work presents a personalized travel recommendation system developed as part of the INDIANA platform, designed to enhance the tourist experience through tailored activity suggestions, by leveraging data from wearable devices, user preferences, current location, weather forecasts, and activity history to provide real-time, context-aware recommendations. The platform not only supports individual tourists in maximizing their travel experience but also offers insights to tourism professionals to enhance service delivery, and by integrating modern technologies such as AI, IoT, and wearable analytics, it provides a seamless, personalized, and engaging experience for travelers.
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