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Mobile application of local baba-peranakan food tourism for generation y: A case study of phuket province, thailand
(2024-08-01)
Surapiyawong, Paranee
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Kasemsarn, Kittichai
Local food in Phuket, which was awarded UNESCO’s City of Gastronomy in 2015, has received attention, especially the local cuisine representing the Baba–Peranakan people. However, studies and information about Thailand’s Baba cuisine are vague, limited, and in need of support because of the lack of storytelling, technology, and targeted tourist channels. Therefore, this research aimed to study Baba cuisine, to design guidelines, and to create and evaluate a mobile phone application (or app, in popular usage) prototype to promote food tourism in Phuket province for Generation Y. First, 20 mobile food apps were analyzed, reviewed, and interviewed by ten experts from the fields of local food tourism and app design. Next, the researchers designed a logo, icons, and site map; chose a color scheme and font; and took pictures for a Baba food mobile app prototype. In the evaluation stage, 100 online questionnaires were distributed and evaluated in terms of the following five factors: User experience, user interface, information content, usefulness, and building a good image. The average mean score for all factors was 4.55 (strongly agree). This research contributes to knowledge about how to promote local food and cultural tourism for Generation Y through mobile applications. It could be applied not just in Phuket but in all cities, leading to an improvement in local economies.
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Mobile Bot Application for Identification of Trypanosoma evansi Infection through Thin-Blood Film Examination Based on Deep Learning Approach
(2023-01-01)
Jomtarak, Rangsan
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Kittichai, Veerayuth
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Kaewthamasorn, Morakot
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Thanee, Suchansa
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Arnuphapprasert, Apinya
Trypanosomiasis caused Trypanosoma evansi is current public health concern especially, in south Asia and Southeast Asia. Although polymerase chain reaction is currently used as a standard method, the techniques required skilled personnel, were performed in multiple steps, and required expensive instruments. Fundamental microscopic approach also has limitation in use by facing both inter- and intra-variability of interpretation by examiners. New automatic tool with the microscopic examination is needed. The study aimed to develop the mobile application-based YOLO neural network algorithms to predict T. evansi blood stages from thin-blood film examination. YOLO v4 tiny model is outperformed to localize and classify unseen images with the best performance at 95% of sensitivity, specificity, precision, accuracy and F1 score, respectively, with less misclassification rate than 5%. Simulation implementation platform, calling CiRA bot, give the empirical result and reliably comparable to that from the computational experiment studied with the area under ROC and precision-recall curves as 0.964 and 0.962, respectively. The result obtained from the CIRA bot platform is good enough for further distribution in field site. In the future, the study could contribute human and animal public health staff to simply identify the unicellular parasitic flagellate infection and also benefit them for designing the strategy in prevention and treatment of the disease.
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Chertify: Wood Identification-Based Mobile Cross-platform by Deep Learning Technique
(2022-01-01)
Wongpoo, Teerasak
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Sriwan, Wannamongkol
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Titijaroonroj, Taravichet
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Jamsri, Pornsuree
Thailand’s economic trees are counted as one of its most valuable domestic assets and well known internationally as a high quality natural wood resource. However, there is a need for basic wood identification whether or not for a required certificate by individuals, entrepreneurs, and organizations. Currently, the wood identification process is manually accomplished only by an expert at the Forest Research and Development Office, the Royal Thai Forest Department. This is a time consuming complex process for two reasons–required experience and limited experts. Given the complexity of wood identification, a new approach is offered, namely, to identify different types of wood with an image from a smartphone. The researcher initially proposes a mobile application, “Chertify”, that has five features (login, wood check, wood check history, manual, and wood knowledge). This app can serve both iOS and Android platforms and targets the general user. Chertify aims to simplify identification of an economic wood type by combining deep learning technology with an actual wood image on a Smartphone. The selected deep learning algorithm will be applied to 258 trained group images of seven wood types based on highest accuracy and lowest standard deviation. Chertify relies on a handcrafted method (HOG and SVM) and a learning-based method (Alexnet) with accuracy of 69.4% and 84.73% and SD at 5.37% and 3.07% values, respectively.
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A check-in system supporting multiple attendees check-in at a time by proximity-based methods
(2021-05-19)
Sae-Lim, Nopparut
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Sinchai, Ananta
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Yiangsupapaanontr, Nathan
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Tuwanut, Panwit
Every year, tons of events are held. One essential problem of each event is a check-in process. The check-in process wastes plenty of time because each check-in unit is able to check only single participant at a time. Diverse approaches using proximity-based methods have been developed to lessen the check-in processing time. To improve the check-in processing time, these methods are surveyed in this paper. The survey has found that most proximity-based schemes still verify attendees in the same manner but consume lesser time. In addition to the survey, a solution that offers a check-in system that is capable of checking in multiple attendees at a time is proposed. The proposed solution employs beacon technology which is already installed on most mobile devices to provide a unique electronic ticket for each device. With this presented solution, each participant already having the unique electronic ticket on his/her device registered is automatically checked in when walking into an event venue. This significantly helps reduce time consumed in the check-in process.
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A Sufficiency Agriculture Learning Platform for the Development of New Agriculturists
(2021-01-01)
Komatsu, Kazuya
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Yoothong, Pimlapat
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Jamsri, Pornsuree
The agricultural industry has the problem of price reduction of products and market oversupply. The root cause comes from Thai farmers practicing monoculture, plant and cultivation of the same types of products at the identical time in a nearby area. To address this problem our team developed a mobile application “Kueakul”. This application serves a sufficiency agriculture platform for a new agriculturist to strengthen a cooperative society of agriculturists. The application is accessible through iOS and Android platforms. It provides eight major features: (1) login; (2) agriculturist profile; (3) preference of users; (4) advising services for basic agriculture; (5) allocation of land and plant model; (6) knowledge for mixed crops (7) crop nourishment (watering); (8) and a discussion forum. The applications “Kueakul” can help Thai agriculturists have better understanding of correct information to best-manage their resources. The application was successfully implemented and evaluated by 2 groups—target users and an expert. The results and evaluation found three most useful features: land allocation, watering scheduling and discussion forum with significant potential for sufficiency agriculture.
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Development of soil moisture monitoring by using IoT and UAV-SC for smart farming application
(2020-07-01)
Duangsuwan, Sarun
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Teekapakvisit, Chakree
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Maw, Myo Myint
Soil moisture is a fundamental factor for smart farming that is used to control the water management system. In this paper, the unmanned aerial vehicle (UAV) small cell (UAV-SC) can provide Internet of things (IoT) as the hotspot mobility network, due to the minimum limitation energy of connected IoT. The development of ground sensor (GS) communicates to the UAV-SC called GS-UAV-SC model for soil moisture monitoring is proposed to smart farming. UAV-SC aims to fulfill the data collection task with a limitation of GSs power. In the experiment, the two case scenarios: Napier grass farm and Ruzi grass farm are implemented. The result of soil moisture status is demonstrated as an example of data in real time on a mobile application monitoring system. The proposed system is useful for users/farmers to know the soil moisture data quickly for smart farming applications.
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Elemem: Interactive digital card game for chemistry
(2020-04-01)
Boonpotjanawetchakit, Paiboon
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Kaweerat, Kansinee
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Vittayakorn, Sirion
Games are popular media among youth since they are not only entertaining but also provide exotic experiences and establish relationships between players. In this work, we propose a game-based learning tool for Chemistry called Elemem which aims to 1) demonstrate the relevance of the periodic table in the context of everyday life in order to improve the understanding of the periodic table and its elements, and 2) provide an alternative and attractive learning tool for use both at school (group-learning) and at home (self-learning). Several experiments reveal that Elemem is not only an enjoyable and encouraging self-learning process, but also educational; 79% of the students said they will recommend Elemem to their friends and others.
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AR Development for Room Design
(2018-09-06)
Reuksupasompon, Peeranut
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Aruncharathorn, Maytichai
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Vittayakorn, Sirion
Arranging your furniture correctly can be the difference between having a cramped, gloomy, impractical space and a cozy, elegant and functional room. Although everyone wants their place to be functional and stylish, room design demands time and expertise. While there are extensive systems for room and layout design, most of them require users to drag and drop the 3D furniture models into their 3D room, modify the furniture size/color/texture or change the camera viewpoint around to see their newly designed room from different perspectives by means of the mobile phones or tablets screen. These complications diminish the user satisfaction as well as restrict synchronous collaboration among multiple users. In this work, we propose a system for designing a furniture layout based on the augmented reality technology. Given the room floor plan and multiple QR markers, users are able to physically move their furniture (each QR marker corresponds to a 3D furniture model) around the limited space (inside the specific area defined by the room plan) to design their own functional and stylish room layout. Finally, We demonstrate that our system can not only alleviate the difficulties of existing room design systems, but also amplify the users satisfaction of room design application. Moreover, we posit that it will encourage co-design from simultaneous multiple users.
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The influence of colour on intention to adopt food delivery service mobile app
(2017-11-24)
Satcharoen, Kleddao
This research investigates the connections between colour usage, food appetite, and intention to adopt a food delivery services mobile app. Although research has established a connection between colour perception and appetite, hunger, and food choice, the research was designed to explore the importance of colour in app design and the link between appetite for food and adoption of the app. The research used a quantitative, scenario-based online questionnaire distributed to Thai mobile Internet users (n = 398). Users were asked about their perception of the colours and appetite, followed by a mobile app adoption scenario. Results showed that Orange, Red, Yellow, and Blue were associated with food appetite, while Orange, Red, and Blue were associated with adoption intention. Food appetite and adoption intention were positively and strongly associated. The implication of this research is that app designers need to consider the psychological implications of their aesthetic design.
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Factors affecting disclosure of personal health information via mobile application
(2017-06-27)
Atchariyachanvanich, Kanokwan
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Mitinunwong, Nichaporn
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Tamthong, Butsaraporn
This study explored the factors that affect personal health information (PHI) disclosure via a mobile application (app) in Thailand. Since mobile apps are increasingly popular, as is the Thai people's concern on their health condition, many mobile app service providers want to know which factors would persuade customers to reveal their PHI via mobile apps. This research model was, therefore, developed and included the six factors of: personalized service, self-presentation, mobile app reputation, familiarity, perceived benefits and privacy concerns. The hypotheses were tested by structural equation modeling using the questionnaire responses from 252 valid subjects. Surprisingly, privacy concern was not significantly negatively related to the intention to disclose PHI. However, the significance effect of the perceived benefit, personalized service and self-presentation were consistent with previous studies. The implication of the result will shed light on the development of healthcare mobile apps.

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