Exploring Machine Learning Applications for Biophilic Art Displays to Promote Health and Well-being

Research has shown that the use of biophilic elements in public or private spaces is effective in alleviating stress, improving mental well-being, and increasing innovativeness in the general public. Studies reveal that exposure to Biophilic art can improve an individual's mental well-being. Many urban settings have few natural representations hence, the goal of our research is to use machine learning algorithms to develop a novel digital biophilic art categorization and display system to promote mental health and well-being. An initial survey conducted indicates a strong correlation between biophilia and positive emotions. We applied classification algorithms to develop an artwork recommendation system based on self-reported emotional responses to biophilic art pieces. Initial findings suggest a reduction in negative emotions and an increase in positive emotions, whilst using the system. This supports machine learning for the categorization and recommendation of biophilic art. It is in line with the importance of the integration of nature into built environments, and advocates the expansion of biophilic art databases, using more inclusive, emotionally responsive art recommendation systems.