PRE2024 3 Group16

Group members

Name	Studentnumbers
Tim Hobbes	1798251
Eline Smit	1903071
Veselin Todorov	1789198
Georgi Kalchev	1855441
Ania Bărbulescu	1823612

AI-powered social robot intended to assist tourists in cities

Introduction

Problem statement

Tourism is a vital component of many cities' economies, attracting millions of visitors each year. However, tourists often face challenges when navigating unfamiliar cities, such as language barriers, difficulty finding attractions, and accessing real-time, reliable information about transportation, local events, and cultural landmarks. Traditional resources, like guidebooks, maps, static information kiosks or local transportation apps often fall short in providing personalized, interactive, and immediate assistance. Human guides, while helpful, may not always be available, accessible or financially sustainable. As tourism continues to grow worldwide, there is a growing need for innovative, scalable solutions that enhance the tourist experience and alleviate these challenges.

Objectives

The primary objective of this project is to develop an AI-powered social robot designed to assist tourists in cities by providing real-time, interactive, and personalized support. The robot will serve as a multilingual city guide, offering recommendations, directions, cultural insights, and event updates to tourists in a friendly and accessible manner. Our key objectives are to:

• Enhance the tourist experience: Provide immediate, accurate, and useful information to visitors.
• Breaking the language barriers for tourists: Equip the social robot with multilingual capabilities to assist tourists from diverse backgrounds
• Promoting local attractions and businesses: Offer tailored suggestions to tourists based on the tourists’ interests and the interests of the local community
• Establish an effective means of communication: The social robot should establish an effective means of communication with the tourists so that the social robot can be understood effectively

Target group and users

The primary target group for this AI-powered social robot consists of domestic and international tourists exploring cities. Tourists often arrive in unfamiliar environments with limited knowledge of the city's layout, attractions, and cultural norms. Language barriers, confusing public transportation systems, and the overwhelming amount of information available online can create a sense of disorientation and frustration. The social robot is designed to address these challenges by serving as an intelligent, interactive guide that enhances the tourist experience from the moment they arrive until their departure.

A significant secondary target group, and the group poised to benefit most from a financial perspective, are local business owners and the city tourism board in the areas where the social robot operates. By enhancing the overall experience for tourists, these stakeholders can directly influence visitor satisfaction, which, in turn, contributes to long-term economic growth within the city.

The social robot, through its personalized recommendations and real-time information delivery, can promote local attractions, restaurants, shops, and cultural events. This not only increases tourist engagement with local businesses but also fosters greater spending and prolonged stays. By providing tailored suggestions based on user preferences, the robot acts as a dynamic marketing tool, directing tourists toward hidden gems, seasonal events, and locally-owned establishments that might otherwise go unnoticed.

For the city tourism board, the robot serves as a powerful tool for promoting the city’s cultural identity and ensuring positive word-of-mouth among visitors. A seamless, enjoyable tourist experience enhances the city’s reputation, encouraging repeat visits and attracting new travelers.

State-of-the-art

Number	Summary	Citation
1	Mobile application with p.o.i. and ML to guide tourists between p.o.i.	T. Ghani, N. Jahan, S. H. Ridoy, A. T. Khan, S. Khan and M. M. Khan, "Amar Bangladesh - a Machine Learning Based Smart Tourist Guidance System," 2018 2nd International Conference on Electronics, Materials Engineering & Nano-Technology (IEMENTech), Kolkata, India, 2018, pp. 1-5, doi: 10.1109/IEMENTECH.2018.8465377. keywords: {Smart phones;Mobile applications;Databases;Google;Machine learning;Real-time systems;Linear regression;smartphone;mobile application;technology;machine learning;analysis},
2	Using courd-sourced movement data tourists are guided based on how other tourists went	Basiri, A., Amirian, P., Winstanley, A. et al. Making tourist guidance systems more intelligent, adaptive and personalised using crowd sourced movement data. J Ambient Intell Human Comput 9, 413–427 (2018). https://doi.org/10.1007/s12652-017-0550-0
3	Old system first introducing a tourist guide, without the use of mobile data or GPS	Cheverst, K., Davies, N., Mitchell, K., & Friday, A. (2000). Experiences of developing and deploying a context-aware tourist guide. Proceedings Of The 28th Annual International Conference On Mobile Computing And Networking. https://doi.org/10.1145/345910.345916
4	the a long and windy introduction to the use of API's	El-Sofany, H., & El-Seoud, S. A. (2011). Mobile Tourist Guide â?? An Intelligent Wireless System to Improve Tourism, using Semantic Web. International Journal Of Interactive Mobile Technologies (iJIM), 5(4), 4. https://doi.org/10.3991/ijim.v5i4.1695
5	development of a computer simulator that can evaluate the effectiveness of various evacuation guidance methods for tourists from disaster areas	Emori, N., Izumi, T., & Nakatani, Y. (2016). A support system for developing tourist evacuation guidance. In Springer eBooks (pp. 15–28). https://doi.org/10.1007/978-981-10-0551-0_2
6	Mobile application with p.o.i.	Chavan, R., Bhoir, M., Sapkale, G., & Mhatre, A. (2023). Smart Tourist Guide System. Engpaper Journal.
7	Findings reveal that the guides do not believe that digital development will affect their jobs negatively soon but they know there is a threat of robots with artificial intelligence, the use of digital applications, and smart technologies.	Nazli, M. (2020). THE FUTURE OF TOURIST GUIDANCE CONCERNING THE DIGITAL TECHNOLOGY: a COMPARATIVE STUDY. International Journal of Contemporary Tourism Research, 66–78. https://doi.org/10.30625/ijctr.692463
8	Then by defining collaborative filtering approach on the history meaningful POIs are extracted.	Fenza, G., Fischetti, E., Furno, D., & Loia, V. (2011). A hybrid context aware system for tourist guidance based on collaborative filtering. 2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). https://doi.org/10.1109/fuzzy.2011.6007604
9	The paper also describes our development of an efficient broadcast mechanism which enables visitors' requests for information to be serviced quickly despite the wireless communications infrastructure employed.	Davies, N., Cheverst, K., Mitchell, K., & Friday, A. (1999). “Caches in the air”: disseminating tourist information in the GUIDE system. Proceedings WMCSA’99, 11–19. https://doi.org/10.1109/mcsa.1999.749273
10	This paper is a historical analisis of where the tourist guide comes from	Cohen, E. (1985). The tourist guide. Annals of Tourism Research, 12(1), 5–29. https://doi.org/10.1016/0160-7383(85)90037-4
11	This paper describes mobile tourist guide - a complex system that enables comprehensive up-to date information search along with personalized recommendations and services.	Smirnov, A., Kashevnik, A., Balandin, S. I., & Laizane, S. (2013). Intelligent Mobile Tourist Guide. In Lecture notes in computer science (pp. 94–106). https://doi.org/10.1007/978-3-642-40316-3_9
12	This paper automatically generates p.o.i. by looking at what people are saying on social media	Meehan, K., Lunney, T., Curran, K., & McCaughey, A. (2016). Aggregating social media data with temporal and environmental context for recommendation in a mobile tour guide system. Journal of Hospitality and Tourism Technology, 7(3), 281–299. https://doi.org/10.1108/jhtt-10-2014-0064
13	Our proposed system is a centralized system based on web services which provides all necessary information and tools that can be used by tourists to organize their trip.	Singh, V., Bali, A., Adhikthikar, A., & Chandra, R. (2014). Web and mobile based tourist travel guide system for fiji’s tourism industry. Asia-Pacific World Congress on Computer Science and Engineering, 1–7. https://doi.org/10.1109/apwccse.2014.7053840
14	proposes an alternative network to 4G specially for tour guides	Davies, N., Cheverst, K., Mitchell, K., & Efrat, A. (2001). Using and determining location in a context-sensitive tour guide. Computer, 34(8), 35–41. https://doi.org/10.1109/2.940011
15	evaluating different guideance systems to prevent overcrowding during an emergancy	Kinugasa, S., Izumi, T., & Nakatani, Y. (2012). Evaluation of a support system for large area tourist evacuation guidance: Kyoto simulation results. IEEE, 440–445. https://doi.org/10.1109/scis-isis.2012.6505119
16	The proposed model mimic the human tourism guide, through building relationships between knowledge based-system with the role of tourist-guide	Owaied, H., Farhan, H., Al-Hawamde, N., & Al-Okialy, N. (2011). A model for intelligent tourism guide system. Journal of Applied Sciences, 11(2), 342–347. https://doi.org/10.3923/jas.2011.342.347
17	Explores the pitfalls in a tourist guide system, mainly overcourding	Bornt, Christian & Cheverst, Keith. (2003). Social and technical pitfalls designing a tourist guide system.
18	Google maps with custom p.o.i.	Soe, H., & Sein, M. M. (2017). Tourist Guide Information System using Google Map and GPS. International Journal of Advanced Engineering Research and Science, 4(3), 205–209. https://doi.org/10.22161/ijaers.4.3.32
19	Overall, the feedback emphasizes the need for design improvements to enhance the tourist experience and competitiveness of Yuanjiacun.	Zhang, X. ., Disatapundhu, S. ., & Waijittragum, P. . (2024). AN EXAMINATION OF VISUAL GUIDANCE SYSTEMS FOR TOURIST ATTRACTIONS: CASE STUDY OF YUANJIACUN SCENIC AREA. FOCUS ON ARTS : FAR, SSRU, 2(2), 21–33. retrieved from https://so18.tci-thaijo.org/index.php/forfar/article/view/803
20	A guidance routing system based on GPS, the multi-routes are pre-calculated	US20060100778A1
21	Glasses to capture what the user is looking at for guidance	US10268888B2
22	AR on streetview to show POI	US11692842B2
23	A humanoid looking system to guide users	US11409294B2
24	A guidance system to help tourist using POI on Google Maps	Hema, L., Indumathi, R., Prabhakaran, N., & Kumari, D. (2021). Handheld tourist guidance system using GPS. Materials Today Proceedings, 47, 351–354. https://doi.org/10.1016/j.matpr.2021.04.561
25	Introduction of an E-tourism guide	Smirnov, A., Kashevnik, A., Ponomarev, A., Shchekotov, M., & Kulakov, K. (2015). Application for e-Tourism: Intelligent Mobile Tourist Guide. e-Tourism, 40–45. https://doi.org/10.1109/iiai-aai.2015.190

Planning

Week 1

Name	Total	Break-down

Week 2

Name	Total	Break-down

Week 3

Name	Total	Break-down

Week 4

Name	Total	Break-down

Week 5

Name	Total	Break-down

Week 6

Name	Total	Break-down

Week 7

Name	Total	Break-down