Abstract: A mobile device can be used for detecting and communicating to a user at a location, sunlight exposure in relation to the user at the location. Sunlight intensity data at a location of a mobile device is determined, in response to receiving at the computer, GPS (Global Positioning System) data for the mobile device. The sunlight intensity data and the GPS data is analyzed to generate an estimate of sunlight exposure for a user using the mobile device at the location. A level of sunlight exposure for the user is determined, based on the estimate of sunlight exposure for the user, and using the mobile device, the level of sunlight exposure to the user is communicated to the user.

Abstract: Systems, methods, and computer programming products for generating, rendering and/or displaying a computer-generated virtual environment as augmented reality and/or virtual reality. The physical boundaries containing the active area where the virtual environments are rendered and displayed are established. Based on the constraints and characteristics of the physical boundaries, virtual environments are mapped using assets from real, historical and/or fictitious locations. The assets can be dynamically re-sized and distanced to fit constraints of the physical space. Based on historical levels of interactivity with the selected environments, the virtual assets can be sorted and tagged as points of interest or filler assets, then mapped to the virtual environment using GAN technology and other machine learning techniques to re-create unique versions of the selected environments.

Abstract: Systems, methods, and computer programming products for generating, rendering and/or displaying a computer-generated virtual environment as augmented reality and/or virtual reality. The physical boundaries containing the active area where the virtual environments are rendered and displayed are established. Based on the constraints and characteristics of the physical boundaries, virtual environments are mapped using assets from real, historical and/or fictitious locations. The assets can be dynamically re-sized and distanced to fit constraints of the physical space. Based on historical levels of interactivity with the selected environments, the virtual assets can be sorted and tagged as points of interest or filler assets, then mapped to the virtual environment using GAN technology and other machine learning techniques to re-create unique versions of the selected environments.