• Journal of Korean Society for Quality Management
• /
• v.49 no.2
• /
• pp.127-143
• /
• 2021

Purpose: Smart Safety Living Lab is a Living Lab facility, constructed and operated by KITECH in Korea, to support the user experience(UX) evaluation, planning and certification of smart safety products and services. The purpose of this study is to develop a UX evaluation methodology that accommodates the characteristics of the Living Lab and smart safety products and services for a systematic and efficient UX evaluation in the Smart Safety Living Lab. Methods: A generic model of UX evaluation was first derived based on a review of related literature. Then, the generic model is revised to accommodate the characteristics of the Smart Safety Living Lab and smart safety products and services, resulting in the UX Evaluation Methodology for Smart Safety Living Lab (SSLL-UXEM). Results: The developed SSLL-UXEM consists of a structured process for UX evaluation, a guideline for conducting each step of the process, and a set of forms for recording the major evaluation results in each step. Conclusion: SSLL-UXEM can help to enhance the efficiency of the UX evaluation process and the consistency of the UX evaluation results. SSLL-UXEM is also expected to serve as a basis for UX evaluation in various living lab environments in the future.

• Journal of Korean Society for Quality Management
• /
• v.50 no.4
• /
• pp.679-700
• /
• 2022

Purpose: Smart lighting adjusts brightness and color temperature according to weather, the user's activity, mood, etc. This study performed user experience(UX) evaluation of smart lighting in a living lab. The purpose of evaluating UX and analyzing the evaluation results is to improve user-friendliness and market competitiveness of smart lighting Methods: A living lab is a virtual or physical space where various stakeholders participate to develop, verify, and evaluate products, services, or systems in a real-life environment. In this study, an environment of using smart lighting was established in the Smart Safety Living Lab. Subjects performed UX evaluation after interacting freely with smart lighting in the Smart Safety Living Lab. Results: As a result of UX evaluation, it was confirmed that UX was overall excellent and subjects were satisfied with setting a desired indoor mood through smart lighting. However, operating the switch of smart lighting may be difficult due to its complexity, and it is needed to improve some functionalities such as the brightness range provided by smart lighting. Conclusion: This study is expected to contribute to establishing the way of UX improvement of smart lighting. This study is also expected to contribute to developing smart lighting as a high-quality product by reflecting the subjects' needs and UX derived in a real-life environment.

• Journal of Drive and Control
• /
• v.19 no.3
• /
• pp.23-31
• /
• 2022

Traffic safety issues have recently been seriously magnified, due to child deaths in apartment complexes and parking lots. Accordingly, traffic safety technologies are being developed to recognize dangerous situations on living roads and to provide warning services. In this study, a collision detection algorithm was developed to prevent collision accidents between moving objects, by using object type and location information provided from CCTV monitoring devices. To determine the exact collision between moving objects, an object movement model was developed to predict the range of movement by considering the moving characteristics of the object, and a collision detection algorithm was developed to efficiently analyze the presence and location of the collision. The developed object movement model as well as the collision detection algorithm were simulated, in a virtual space of an actual living road to verify performance and derive supplementary matters.

• Journal of Information Technology Services
• /
• v.20 no.6
• /
• pp.141-150
• /
• 2021

With the recent spread of the concept of Smart Cities which is to solve urban problems with ICT technology, Living Lab, which identifies the demands of citizens who dwell in the city and verifies the acceptability of the services being introduced, has become an important topic. Living Lab is an open innovation platform introduced in consideration of the user's perspective in real life and is a new approach in that service developers use collective intelligence in the process of Co-creation with users. Living Lab is operated on topics which is close to citizens' daily lives such as energy, housing, transportation, and education. In particular, as energy and environmental-focused Living Lab emerges in accordance with the 'Korean New Deal Policy', interest and importance in the field are increasing. The paper derives the characteristics of water resource Living Lab through case analysis of several Living Lab practices. Water resource Living Lab in Daejeon and Chuncheon, which are located in Korea, and water resource Living Lab in Romania and Indonesia are covered in this paper as the reference. The paper finally analyzes the case of Sambang Water Living Lab in Gimhae, which is the city located in southern part of Korea. As a result of case analysis, the urban water resource Living Lab focuses on the raw water of urban water resource and should respond sensitively to the safety of citizens. And for the success of this urban water resource Living Lab, it is essential to ensure that citizens participating in the Living Lab clearly understand the concept of water resources, and citizens' opinions to be implemented as services.

• Journal of IKEEE
• /
• v.24 no.4
• /
• pp.1180-1183
• /
• 2020

Recently, the daily life safety detection functionalities such as fall accident detection and burn danger detection are widely disseminated along with the development of IoT and smart home. These safety detection functionalities are mostly performed by artificial intelligence. However, simple accuracy measurement of the safety detection in laboratory environment is often far from practical performance in daily life environment. To mitigate this problem, this paper introduces two techniques, i.e. living lab and confusion matrix. Living lab is more than simple simulation of daily life environment, and it enables users to directly participate technology development and product design. Various performance measures induced from confusion matrix significantly help to evaluate the performance of artificial intelligence system for proper application purposes.