Blockchain technology is a secure distributed ledger for lists of transactions, which has immense potential to solve traditional agri-food supply chain issues. An increasing number of research on blockchain-based traceability applications aims to improve food quality and safety. Still, relatively few works considered user interfaces when developing and reporting their applications, which could lead to usability issues. This paper aims to address this gap by reviewing existing works from user interface perspectives. We gathered 25 review papers on blockchain or agri-food supply chain and 39 research papers that presented screenshots of user interfaces of related applications. We first reviewed 7 review papers that focused on the blockchain-based agri-food supply chain to understand the benefits and challenges in the blockchain applications. We then analyzed 14 blockchain-based agri-food traceability applications and 10 non-blockchain-based agri-food traceability applications. The analysis resulted in categorizations of 5 target user groups, 3 main approaches for collecting data, 5 main approaches for visualizing data, and a discussion of other aspects of user interfaces. However, we found insufficient details and discussions on the user interfaces and design decisions of the applications for further usability assessment. Additionally, user involvement for evaluation is lower in blockchain-based researches than in non-blockchain-based researches. This trend could lead to usability problems of blockchain applications, causing blockchain technology to be underutilized. Finally, we discussed research gaps and future research directions related to user interface design, which should be addressed to ease future blockchain adoption.

Pose estimation has various applications in analyzing human body movement and behavior, including providing feedback to users about their movements so they can adjust and improve their movement skills. To investigate the current research status and possible gaps, we searched Scopus and Web of Science for articles that (1) human 'body' pose estimation is used and (2) user movement is assessed and communicated. We used either a bottom-up or top-down approach to analyze 45 articles for methods used to estimate human body pose, assess movement, provide feedback to users, as well as methods to evaluate them. Our review found that pose estimation systems typically used CNNs while movement assessment methods varied from mathematical formulas or models, rule-based approaches, to machine learning. Feedback was primarily presented visually in verbal forms and nonverbal forms. The experiments to evaluate each part ranged from the use of public datasets to human participants. We found that pose estimation libraries play an important role in the advancement of this field. Nevertheless, the effectiveness and factors for choosing movement assessment methods for a new context are still unclear. In the end, we suggest that studies about feedback prioritization and erroneous feedback are needed.

We explored the use of blockchain technology for traceability to improve the safety and value of food, focusing on the coffee supply chain as a case study. The main goal was to evaluate the feasibility in terms of design, perceived benefits, and challenges of applying blockchain and traceability from the users’ perspective. We implemented a prototype using a user-centered iterative interface design. Then we used the prototype to answer our research questions in mixed-method research, including in-depth interviews (10 participants) and a survey (350 participants) with stakeholders in the coffee supply chain in Thailand. The results showed that timeline-based design was preferred over map-based or text-based design for the visualization of traceability information and that blockchain was a promising technology, as 67% of the survey participants saw a positive influence of blockchain on the adoption of applications. The most notable benefits were origin checking and increasing product trustworthiness. The most notable challenges were inaccurate or incomplete information and the disclosure of trade secrets. More work is required to address the challenges for everyone in the supply chain ecosystem to adopt the proposed traceability system, including (1) providing trustworthiness and completeness of information by cross-checking with third parties or other users, (2) protecting sensitive information by aligning users’ interests or allowing control of information disclosure, and (3) educating and giving producers the motivation for the difficulty and the extra work.

Blockchain technology, a decentralized database that encourages collaboration, transparency, and security, is popular in Thailand, as seen from many practical projects. Nevertheless, information about Thailand’s blockchain ecosystem is incomplete. We conducted literature reviews of research articles, education courses, and industry projects, to explore blockchain from the technology adoption flow including academic research, knowledge acquisition, and project implementation. Blockchain research articles were collected from the Scopus database, while projects and courses were retrieved from an internet search. After applying inclusion and exclusion criteria, a total of 13 research articles, 50 courses, and 54 industry projects, dated from 2016 to 2020, were included in our review. Based on an analysis with respect to trends, focuses, and characteristics in all three aspects, we found that blockchain technology in Thailand was in its infancy, but has been increasing in numbers and domain varieties. However, blockchain technology did not move towards the same direction for all aspects. Most research articles were found in government services, supply chain, and traceability domains; while most projects were in the financial domains. We offer possible explanations for this observation. This paper provides challenges and opportunities for the research community and involved parties in practical implementation.

Pose estimation has various applications in analyzing human movement and behavior, including providing feedback to users about their movements so they could adjust and improve their movement skills. To investigate the current research status and possible gaps, we searched Scopus and Web of Science for articles that (1) human `body' pose estimation is used and (2) user movement is assessed and communicated. We used either a bottom-up or top-down approach to analyze 20 articles for methods used to estimate human pose, assess movement, provide feedback to users, as well as methods to evaluate them. Our review found that pose estimation systems typically used CNNs while movement assessment methods varied from mathematical formulas or models, rule-based approaches, to machine learning. Feedback was primarily presented visually in verbal forms and nonverbal forms. The experiments to evaluate each part ranged from the use of public datasets to human participants. We found that while there was an improvement, the majority of pose estimation challenges remain. The effectiveness and factors for choosing movement assessment methods for a new context are still unclear. In the end, we suggest that studies about feedback prioritization and erroneous feedback are needed.