Abstract: Techniques for determining levels of interest, activity, or occupancy at a physical location can include receiving data corresponding to physical parameters sensed by a plurality of sensors at the physical location. The physical parameters can include temperature, humidity, pressure, sound, distance to an object, visible light, infra-red light, motion of objects, acceleration, magnetic field, vibration, and radio signals. Synthetic variables can be generated based on the received data and can represent a processed or combined value for its corresponding physical parameters. The physical parameters and synthetic variables can be stored in a memory device. One or more indicators for a level of: (i) interest, (ii) activity, or (iii) occupancy at the physical location can be generated based on the received data and the one or more synthetic variables by utilizing a machine learning model and output to a user computing device for display in a user interface.

Abstract: Techniques for determining levels of interest, activity, or occupancy at a physical location can include receiving data corresponding to physical parameters sensed by a plurality of sensors at the physical location. The physical parameters can include temperature, humidity, pressure, sound, distance to an object, visible light, infra-red light, motion of objects, acceleration, magnetic field, vibration, and radio signals. Synthetic variables can be generated based on the received data and can represent a processed or combined value for its corresponding physical parameters. The physical parameters and synthetic variables can be stored in a memory device. One or more indicators for a level of: (i) interest, (ii) activity, or (iii) occupancy at the physical location can be generated based on the received data and the one or more synthetic variables by utilizing a machine learning model and output to a user computing device for display in a user interface.