Platform design for lifelog-based smart lighting control

Lifelog refers to daily life records of individuals and includes their environmental, activity, emotional, and biometric information. The utilization of lifelogs makes it possible to provide a personalized lighting environment in line with a user's characteristics. However, no such customized lighting environment has been proposed thus far because methods for collecting and classifying the necessary data and a platform for synthesizing the data are not available. Therefore, in this study, the concept of the lifelog-based smart lighting control is introduced, and lifelog collection methods and a method to recommend the appropriate lighting environment for an individual by analyzing the collected information are proposed. Sensors, lighting controllers, and control interfaces required for lifelog-based smart lighting control were installed in a mock-up space, a machine learning server was set up, and a platform for implementing the optimal lighting environment was constructed by connecting these devices to the cloud. The platform constructed in this study creates a personalized lighting environment by utilizing lifelogs that are divided into emotional information collected via instant message (IM) text analysis, activity information collected using a location and activity tracker, and environmental information collected from weather data.