基于RFID的景区游客定位追踪系统

基于RFID技术,同时结合载波通信和数据库技术,设计一种新型景区游客追踪定位系统。系统以电子标签为游客信息载体,通过电力载波模块将读写器读取的标签信息传输至上位机,上位机查询读写器与景点位置信息的映射确定游客位置,并进行图形化显示,同时存储读取记录至数据库。通过查询读取记录得到游客完整路径信息及当前游客位置分布,为游客分流提供科学有效的依据。该系统可以实现景区游客追踪和定位,对于改善游客旅行体验,提高景区管理效率有积极的意义。     

基于Android的自助导游服务系统

为了满足游客自助游的需要,使游客能够对旅游中的衣食住行及路线问题进行合理的规划,以Android手机系统为平台,并结合A-GPS、二维码、无线互联网、智能语音等技术,以泰山景区为例设计出一种自助旅游应用系统,同时系统着重突出外文版应用,方便外籍游客。系统运行界面简洁友好,便于操作,具有很大的推广和应用价值。     

基于多维因素的欢乐谷智能导游系统设计

随着信息技术的广泛应用,导游系统能实现的功能也愈加丰富。在现有文献和已开发系统的基础上,文章拟站在游客角度,将游客需求作为设计的出发点,结合"排队"、"距离"等游乐场如今存在的热点问题,挖掘系统空白和市场需求,创新系统功能,利用数据结构相关知识,以欢乐谷作为案例设计背景,确定出"最短距离"、"用户偏好"、"实时排队人数"三个影响因素及其权重,运用C语言设计出一个基于多权重分析的导游系统,以节省游客的游玩时间和成本,从而提高顾客的满意度,另一方面也在一定程度上使得管理方的管理更加便捷化,提高其效益。     

基于ZigBee旅游景区内游客定位系统的研究

针对旅游景区内游客自由参观时迷路而找不到旅游团、导游召集游客难等一系列问题,文章以CC2430/CC2431芯片为系统核心模块,设计了一种基于ZigBee技术的旅游景区内游客定位系统。该系统是对无线传感网络应用的一次探索,对于无线传感网络在一维定位上面的应用已经有相关实例了,例如矿井内工人的定位。系统采用ZigBee技术组建无线传感网络,结合RSSI定位算法实现了对景区内游客的二维定位,较一维定位效果更好。     

云环境下景区游客流量监控与推荐系统设计

设计了云环境下景区游客流量监控与推荐系统,包括CC3200流量监控与景点推荐两部分,流量监控由RFID电子门票统计游客数量,数据经Wi-Fi上行本地AP节点,由AP节点汇聚至云推荐服务器;当前游客流量、时间富裕度、游客满意度,经服务器解析计算得景点综合推荐指数,主动为游客推荐旅游景点,规划最佳游览路线;经测试,系统工作稳定、数据准确,适用于各类景区游客流量监控与推荐服务。     

游客满意度仿真方法研究

以上海旅游服务系统为例,设计调查问卷对游客进行访问以获得相关数据,分析样本数据的概率分布情况,并建立游客满意度计算机仿真模型,基于蒙特卡洛方法,借助MATLAB软件及其Simulink仿真工具箱,对旅游服务系统的游客满意度进行模拟和仿真,其结果对于发展旅游业具有一定的参考作用.     

便携式智能导游系统的设计与实现

针对现有智能导游系统在普及和应用中的缺陷,基于以用户为中心的交互设计原理,从可用性和用户体验的角度设计智能导游系统iGuider。该系统结合全球定位系统、地理信息系统及多通道交互技术,为游客提供相关景点的多媒体信息。测试结果表明,系统运行可靠,直观自然的用户界面和反馈信息能使用户轻松使用该系统。     

少数民族地区水族村寨游客体验影响因素研究

文章主要是对少数民族地区游客的旅游体验存在的问题进行研究,对旅游中游客存在的问题以及游客的旅游满意程度进行系统的研究分析,得出对旅游中游客的旅游体验的提升方法,增强游客体验,提高游客满意度。将为今后在少数民族地区游客旅游体验的领域上给出更深一步的理论支持。为后续智慧旅游平台下水族村寨旅游智能终端应用设计与研究提供建议。     

基于ASP．NET的单点登录在图书馆门户系统中的实现

实现了一个基于ASP．NET的单点登录系统,对图书馆门户系统后台进行分类和角色管理,采用了Form身份认证机制,通过基于角色的授权访问控制机制,实现了后台管理游客、管理员、普通用户3类用户,并设计一个用户账号只能在同一系统中进行唯一登录的功能。     

基于微信平台的景区智能导游系统设计

目前景区导游主要由讲解人员完成,但这种方式适合为旅游团提供服务,而对于分散的游客来说却存在很多弊端。本研究设计一款基于微信小程序平台的景区导游系统,使用JavaScript语言、数据库技术和GPS技术结合Floyd最短路径算法实现景区的智能化导游。系统功能主要包括景区介绍、语音导航,路线规划等,目的在于提升游客自助游质量,缓解旅游高峰期导游的压力,避免出现游客在景区迷失方向,错过景点的情况,并且可以缓解景区拥堵,达到智能导游的效果。     

Beyond destinations: exploring tourist technology design spaces through local–tourist interactions

The design of digital tourist technologies is traditionally situated in an understanding of tourism as an information consumption practice. In contrast, this article takes a ‘performative’ view of tourism as its starting point. The research presented is part of a larger goal, which is to propose a shift in the socio-technical environment in which the design of engaging technologies for tourists takes place. By drawing on recent approaches for understanding the lived social and material conditions of tourist places, we first show how contemporary tourism can be usefully understood as a form of networking. The article then draws on early research about the roles of locals and tourists in the making of place during the course of their networking activities, and suggests how an understanding of the social environment of tourists might be used as a grounded resource for design. Our analysis of a staged encounter between a single tourist and four locals generates insights used to shape a design space, a first step in the development of appropriate, engaging design interventions in the domain of tourism.     

Virtools在开发虚拟旅游区漫游系统中的应用

随着旅游业的不断发展,为使旅游者对旅游目的地可以事先进行网上游览,从而使得旅游区信息能被广泛传播和迅速获取,开发虚拟旅游区漫游系统就显得尤为重要.漫游系统采用3DS MAX对旅游区场景和游览角色的进行三维建模,在做好纹理、贴图及相关动作设置以后,利用Virtools进行系统的设计与开发,并采用碰撞侦测等技术来保证系统的...     

“武汉印象”旅游招贴设计中水墨元素的运用

以旅游招贴设计中民族特色的文化式样运用为题,分析了武汉旅游文化特色,提出了使"水"成为旅游者对武汉城市的第一感知,使"水文化"的旅游底色在城市中彰显,让武汉成为名副其实的"知音江城、人文水都"。在此基础上,以中国水墨画中水墨元素的创意构思来源为启示,论述了将中国水墨画中的水墨元素与"武汉印象"旅游招贴结合的可能性与必要性,别具一格地将武汉旅游文化特色淋漓尽致的体现出来。     

A real-time personalized route recommendation system for self-drive tourists based on vehicle to vehicle communication

Recently, traffic jams and long queuing problems in tourist hot spots is growing with the increasing number of self-drive tourists. Some recommendation systems have been developed in attempt to relieve these problems. However, all these systems lack information pertaining to real-time traffic as well as the ability of personalization. In this research, we have developed a novel route recommendation system to provide self-drive tourists with real-time personalized route recommendations. This will help to reduce the traffic jams and queuing time in tourist hot spots. It will also help to personalize visiting routes based on the user’s specific preferences. Ultimately, based on the evaluation results given by experienced self-drive tourists, we have shown that the proposed system not only saves total visiting time, but also meets their specific visiting preferences.     

Uncover: supporting city exploration with egocentric visualizations of location-based content

This paper describes the design and evaluation of Uncover: a mobile application that supports users in exploratory pedestrian behavior to gain situational awareness of their immediate environment. The design was based on guidelines derived from foraging theory and relies on egocentric views, which keep the virtual content automatically aligned with the real world. We carried out two studies with Uncover, which examine the successfulness of design choices aiming to support tourists’ city exploration while interfering with experiencing the surroundings as little as possible. A lab study tested the effect of different marker and background types on the time to recognize the direction with most content. The designs performing best were implemented in the final prototype, and a field study analyzed the exploration behavior tourists and visitors exhibited while using it. The study showed that supporting the exploration can be improved by enabling features that are either disabled by default or not available at all in commercial map applications, like egocentric orientation of the map, providing images of venues just by pointing to their direction, and displaying clusters of several venue types.     

A neural multi-context modeling framework for personalized attraction recommendation

In attraction recommendation scenarios, how to model multifaceted tourism contexts so as to accurately learn tourist preferences and attraction tourism features is a keystone of generating personalized recommendations. However, most of existing works generally focused on modeling spatiotemporal contexts of historical travel trajectories to learn tourists’ preferences, while neglected rich heterogeneous tourism side information, i.e., personal tourism constraints of tourists and tourism attributes of attractions. To this end, we propose a Neural Multi-context Modeling Framework (NMMF) to learn tourism feature representations of tourists and attractions by modeling multiple tourism contexts. Initially, we leverage a travel knowledge graph and massive original travelogues to construct the tourism attribute context of attractions and the travel trajectory context of tourists. Then, we design two context embedding models, named TKG2vec and Traj2vec, to model two kinds of context respectively. Both models learn feature vectors of tourist and attraction in contexts by elaborating neural networks to project each tourist and attraction into a uniform latent feature space. Finally, our framework integrates feature vectors derived from two models to acquire complete feature representations of tourists and attractions, and recommends personalized attractions by calculating the similarity between tourist and candidate attractions in the latent space. Experimental results on a real-world tourism dataset demonstrate our framework outperforms state-of-the-art methods in two personalized attraction recommendation tasks.

     

Application of particle swarm optimization and perceptual map to tourist market segmentation

This study intends to apply particle swarm optimization algorithm to cluster analysis for investigating market segmentation of Taiwanese tourists based on their motivation to visit Indonesia. In addition, Taiwanese tourists’ preference of several types of tourism destinations offered in Indonesia will also be studied. According to the cluster analysis results, we will propose marketing strategy based on market segmentation and tourists’ preferences revealed. The computational results reveal that there were four clusters formed. Moreover, by using perceptual map, it was also known that most of respondents tend to visit heritage, culture, and nature-based tourism destinations offered in Indonesia.     

The effects of perceived relevance of travel blogs’ content on the behavioral intention to visit a tourist destination

The tourism industry is characterized by ever-increasing competition, causing destinations to seek new methods to attract tourists. Traditionally, a decision to visit a destination is interpreted, in part, as a rational calculation of the costs/benefits of a set of alternative destinations, which were derived from external information sources, including e-WOM (word-of-mouth) or travelers’ blogs. There are numerous travel blogs available for people to share and learn about travel experiences. Evidence shows, however, that not every blog exerts the same degree of influence on tourists. Therefore, which characteristics of these travel blogs attract tourists’ attention and influence their decisions, becomes an interesting research question. Based on the concept of information relevance, a model is proposed for interrelating various attributes specific to blog’s content and perceived enjoyment, an intrinsic motivation of information systems usage, to mitigate the above-mentioned gap. Results show that novelty, understandability, and interest of blogs’ content affect behavioral intention through blog usage enjoyment. Finally, theoretical and practical implications are proposed.     

基于层次分析法的乡村旅游影响因素研究

通过对影响乡村旅游发展的因素进行定量分析,以期对商洛市乡村旅游资源可持续开发利用提供合理的参考建议。首先构建基于游客的4个准则25个指标的乡村旅游评价体系,其次对商洛市9个乡村旅游示范村的游客进行问卷调查,依据调查结果从乡村旅游的旅游资源、基础设施、餐饮交通、综合感知等方面运用层次分析法构建模型,然后评价结果分析影响乡村可持续发展的因素,最后依据调查分析结果并提出有针对性的发展策略。