It is urgent issue to develop a re-usable energy system, low carbon resources, and a food production system compatible with natural environment and we should find an optimized solution in an economic society. Smart environment is one of the solutions. The smart environment is expected to optimize a balance of wellbeing versus energy cost. However, what would be the balance and how we find it? Here, we attempted to develop a bio-eco system where we sense human behavioral and physiological response under certain environment to automatically regulate environment to realize a balance which improves human health with minimum energy cost. We describe an information processing method based on principal components analysis to visualize the correlation structure of behavioral and environmental parameters in social interaction of animals and humans. In a primate model, we analyzed the animal's psychological lifelong development to find any susceptible period to environments which is critical to confer their lifelong adaptability to environment. In the study, we could confirm usefulness of blood glucose sensing to infer developmental stages.