Abstract: A smart window-based security system is provided. The system includes a plurality of smart windows, each smart window of the plurality of smart windows having at least one electrochromic window and at least one sensor integrated into the smart window. The plurality of smart windows are coupled together in a system having at least one processor configured to detect a personal or property security threat, such as an intruder or fire based, on information from sensors of the plurality of smart windows.

Abstract: A smart window-based security system is provided. The system includes a plurality of smart windows, each smart window of the plurality of smart windows having at least one electrochromic window and at least one sensor integrated into the smart window. The plurality of smart windows are coupled together in a system having at least one processor configured to detect a personal or property security threat, such as an intruder or fire based, on information from sensors of the plurality of smart windows.

Abstract: A smart window system is provided. The system includes a plurality of smart windows, each having at least one electrochromic window and a plurality of sensors. The system includes a control system coupling the plurality of smart windows and the plurality of sensors. The control system is configured to couple to a network, and configured to generate a building model that includes information regarding the plurality of smart windows and is based on information from the plurality of sensors and information from the network.

Abstract: A smart window system is provided. The system includes a plurality of smart windows, each having at least one electrochromic window and a plurality of sensors. The system includes a control system coupling the plurality of smart windows and the plurality of sensors. The control system is configured to couple to a network, and configured to generate a building model that includes information regarding the plurality of smart windows and is based on information from the plurality of sensors and information from the network.

Abstract: A smart window-based security system is provided. The system includes a plurality of smart windows, each smart window of the plurality of smart windows having at least one electrochromic window and at least one sensor integrated into the smart window. The plurality of smart windows are coupled together in a system having at least one processor configured to detect a personal or property security threat, such as an intruder or fire based, on information from sensors of the plurality of smart windows.

Abstract: A smart window-based security system is provided. The system includes a plurality of smart windows, each smart window of the plurality of smart windows having at least one electrochromic window and at least one sensor integrated into the smart window. The plurality of smart windows are coupled together in a system having at least one processor configured to detect a personal or property security threat, such as an intruder or fire based, on information from sensors of the plurality of smart windows.

Abstract: A cloud learning system for smart windows is provided. The system includes at least one server configured to couple via a network to a plurality of window systems, each of the plurality of window systems having at least one control system and a plurality of windows with electrochromic windows and sensors, wherein the at least one server includes at least one physical server or at least one virtual server implemented using physical computing resources. The at least one server is configured to gather first information from the plurality of window systems, and configured to gather second information from sources on the network and external to the plurality of window systems. The at least one server is configured to form at least one rule or control algorithm usable by a window system, based on the first information and the second information, and configured to download the at least one rule or control algorithm to at least one of the plurality of window systems.

Abstract: A cloud learning system for smart windows is provided. The system includes at least one server configured to couple via a network to a plurality of window systems, each of the plurality of window systems having at least one control system and a plurality of windows with electrochromic windows and sensors, wherein the at least one server includes at least one physical server or at least one virtual server implemented using physical computing resources. The at least one server is configured to gather first information from the plurality of window systems, and configured to gather second information from sources on the network and external to the plurality of window systems. The at least one server is configured to form at least one rule or control algorithm usable by a window system, based on the first information and the second information, and configured to download the at least one rule or control algorithm to at least one of the plurality of window systems.

Abstract: A smart window-based security system is provided. The system includes a plurality of smart windows, each smart window of the plurality of smart windows having at least one electrochromic window and at least one sensor integrated into the smart window. The plurality of smart windows are coupled together in a system having at least one processor configured to detect a personal or property security threat, such as an intruder or fire based, on information from sensors of the plurality of smart windows.

Abstract: A smart window system is provided. The system includes a plurality of smart windows, each having at least one electrochromic window and a plurality of sensors. The system includes a control system coupling the plurality of smart windows and the plurality of sensors. The control system is configured to couple to a network, and configured to generate a building model that includes information regarding the plurality of smart windows and is based on information from the plurality of sensors and information from the network.

Abstract: A smart window-based security system is provided. The system includes a plurality of smart windows, each smart window of the plurality of smart windows having at least one electrochromic window and at least one sensor integrated into the smart window. The plurality of smart windows are coupled together in a system having at least one processor configured to detect a personal or property security threat, such as an intruder or fire based, on information from sensors of the plurality of smart windows.

Abstract: A smart window-based security system is provided. The system includes a plurality of smart windows, each smart window of the plurality of smart windows having at least one electrochromic window and at least one sensor integrated into the smart window. The plurality of smart windows are coupled together in a system having at least one processor configured to detect a personal or property security threat, such as an intruder or fire based, on information from sensors of the plurality of smart windows.

Abstract: A cloud learning system for smart windows is provided. The system includes at least one server configured to couple via a network to a plurality of window systems, each of the plurality of window systems having at least one control system and a plurality of windows with electrochromic windows and sensors, wherein the at least one server includes at least one physical server or at least one virtual server implemented using physical computing resources. The at least one server is configured to gather first information from the plurality of window systems, and configured to gather second information from sources on the network and external to the plurality of window systems. The at least one server is configured to form at least one rule or control algorithm usable by a window system, based on the first information and the second information, and configured to download the at least one rule or control algorithm to at least one of the plurality of window systems.

Abstract: A vehicle seat bar assembly having a seat with first and second engagement members. A rear seat bracket extends between the first and second engagement members of a seat. A torsion bar extends between the first and second engagement members and is operably engaged therewith. The torsion bar includes an intermediate bracket engagement portion and a first and second linear portion that extends between the first engagement member and the intermediate bracket engagement portion and the second engagement member and the intermediate bracket engagement portion. The torsion bar also includes a first and second distal end configured to engage the first and second engagement members, respectively, which induces a torsional resistance in the torsion bar when the seatback is at a fully reclined position and when the seatback is at a fully folded position.

Abstract: A vehicle seat bar assembly having a seat with first and second engagement members. A rear seat bracket extends between the first and second engagement members of a seat. A torsion bar extends between the first and second engagement members and is operably engaged therewith. The torsion bar includes an intermediate bracket engagement portion and a first and second linear portion that extends between the first engagement member and the intermediate bracket engagement portion and the second engagement member and the intermediate bracket engagement portion. The torsion bar also includes a first and second distal end configured to engage the first and second engagement members, respectively, which induces a torsional resistance in the torsion bar when the seatback is at a fully reclined position and when the seatback is at a fully folded position.

Abstract: Systems comprising an optical fiber switch connected to a light source and an optical fiber probe, the optical fiber probe comprising a first optical fiber connected to the optical fiber switch and a second optical fiber connected to a spectrophotometer. Methods for determining one or more tissue parameters comprising: emitting light from a first optical fiber into a tissue; collecting the light reemitted from the tissue with a second optical fiber; generating a spectra of the light reemitted from the tissue with a spectrophotometer; and utilizing a look-up table based algorithm to determine one or more tissue parameters, wherein the lookup-table based algorithm comprises the steps of: generating a look-up table by measuring the functional form of a reflectance measured by the spectrophotometer using one or more calibration standards with known optical properties; and implementing an iterative fitting routine based on the lookup-table.