Nowadays, healthy lifestyle, fitness, and diet habits have become central applications in our daily life. Positive psychology such as well-being and happiness is the ultimate dream of everyday people’s feelings (even without being aware of it). Wearable devices are being increasingly employed to support well-being and fitness. Those devices produce physiological signals that are analyzed by machines to understand emotions and physical state. The Internetof Things (IoT) technology connects (wearable) devices to the Internet to easily access and process data, even using Web technologies (aka Web of Things).

We design IAMHAPPY, an innovative IoT-based well-being recommendation system to encourage every day people’s happiness. The system helps people deal with day-to-day discomforts (e.g., minor symptoms such as headache,fever) by using home remedies and related alternative medicines (e.g., naturopathy, aromatherapy), activities to reduce stress, etc. To achieve this system, we build a web-based knowledge repository for emotion with a focus on happiness and well-being. The knowledge repository helps analyze data produced by IoT devices to understand users’ emotions and health. The semantics-based knowledge repository is integrated with a rule-based engine to suggest recommen-dations to achieve everyday people’s happiness. The naturopathy application scenario supports the recommendation system.