The Development of Semantic Augmented Reality on Mobile Devices for Chronic Disease Care of Aging, Watbot District, Phitsanulok Province

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Yodpeth Tongkhao

Abstract

The aims of this study, carried out in Watbot district, Phitsanulok province, were 1) to study the pattern of the semantic knowledge base for chronic disease care of the elderly; 2) to develop the semantic augmented reality on mobile devices for chronic disease care of the elderly; and 3) to assess performance of the retrieval of semantic knowledge linked to AR for chronic disease care of the elderly. This research collected data from medical textbooks and in-depth interviews with 10 medical persons in order to create the semantic knowledge base using the concept of ontology, which helped to organize the AR on a mobile application and assess searching accuracy. This research found that the semantic knowledge base was divided into 3 layers and linked to AR for recommending the observation of abnormal physical symptoms, related diseases, nutrition, and exercises. The result of accuracy assessment using F-measure was 84.8%. Overall, users’ satisfaction with the system was at a very high level.

Article Details

Section
บทความวิจัย

References

Foundation of Thai Gerontology Research and Development Institute. (2016).
Situation of the Thai elderly 2016. Bangkok: Foundation of Thai Gerontology
Research and Development Institute.
Tupmongkol S, Pilabutr S. Thailand's tourism semantic web with ontology (RDF and
SPARQL). (2016). APHEIT Journal Science & Technology, Vol 5 No 2 (July –
December 2016), pp(5-11).
Sivilai, S and Snae, C. (2013). The development of a question - answer system for
recommending appropriate food for patients. Academic conference
National Level in Information Technology No. 5, Phetchaburi, Thailand, 26-27
February 2013, pp(167-172).
Hayun KimEmail authorTamás MatuszkaJea-In Kim Jungwha and Kim Woontack Woo.
(2017). Ontology-based mobile augmented reality in cultural heritage
sites: information modeling and user study. Multimedia Tools and
Applications December 2017, Volume 76, Issue 24, pp 26001–26029.
L. Kerschberg, M. Chowdhury, A. Damiano, H. Jeong, S. Mitchell, J. Si, and S. Smith.
(2004). Knowledge Sifter: Ontology-Driven Search over Heterogeneous
Databases. USA : George Mason University, Fairfax, Virginia.
United Nation. (2015). United Nations Summit on Sustainable Development 2015.
New York : United Nations Headquarters.