Abstract: A prefabricated construction wall assembly comprising: a frame structure having a first thermal expansion coefficient; and a panel configured for covering at least a majority of the a face of the frame structure, said panel having a second thermal expansion coefficient different from the first thermal expansion coefficient, and a solid-surface exterior face exposed to an exterior of the wall assembly and an interior face connected to the face of the frame structure so as to withstand the thermal structural differences between the frame structure and the exterior face.

Abstract: Prefabricated wall panels simplify the constructive of building units and other structures. The prefabricated wall panels can include a set of conduits pre-installed within the wall panels that enable simplified installation and conduit routing within a building unit or structure. The set of conduits can include electrical conduit, plumbing conduit, HVAC conduit, networking conduit, fire alarm conduit, and fire sprinkler conduit. The prefabricated wall panels can include above-door cavities to assist with structure design and coupling conduits between prefabricated panels. The prefabricated panels can additionally include dual-headed fire sprinklers that enable one fire sprinkler conduit to spray into multiple rooms, reducing the overall number of fire sprinkler conduits required within a structure.

Abstract: A central hub and database for a smart home environment enable the learning of states associated with items within the smart home and the training one or more machine-learned models associated with the items. After training the machine-learned models, the central hub can modify a state of an item based on the machine-learned model associated with the item. For instance, a window can be opened or shut, a light can be dimmed or turned off, and a door can be locked. Each state of the object can be associated with a set of conditions that, when satisfied, cause the central hub to change the state of the object using the corresponding machine-learned model, for instance without receiving an explicit input from a user.