Abstract: A building intelligence gathering, assessment and decision-support system including a GPS system deployed about the Earth and supporting a plurality of GPS satellites for transmitting GPS signals to the surface of the Earth. A building data sensor network, including a plurality of GPS-tracked rooftop-mounted sensors, are mounted on the rooftop surface of the building, and adapted for collecting GPS-indexed data specifying conditions on the rooftop surface at particular dates and times of the year. The building rooftop conditions includes one or more conditions selected from the group consisting of snow load conditions, windspeed and direction, and temperature. The system also includes one or more hand-held mobile augmented-reality (AR) based rooftop navigation and inspection devices, each configured for communication with communication servers within a data center over a wireless data communication network.

Abstract: A system network and methods supported by a constellation of GNSS satellites orbiting around the Earth, and deployed for precise remote monitoring of the spatial displacement, distortion and/or deformation of stationary and/or mobile systems, including buildings, bridges, and roadways. The methods involve (i) embodying multiple GNSS rovers within the boundary of the stationary and/or mobile system being monitored by the GNSS system network, (ii) receiving GNSS signals transmitted from GNSS satellites orbiting the Earth, and (iii) determining the geo-location and time-stamp of each GNSS rover while the stationary and/or mobile system is being monitored for spatial displacement, distortion and/or deformation, using GNSS-based rover data processing methods practiced aboard the system, or remotely within the application and database servers of the data center of the GNSS system network.

Abstract: A system network and methods supported by a constellation of GNSS satellites orbiting around the Earth, and deployed for precise remote monitoring of the spatial displacement, distortion and/or deformation of stationary and/or mobile systems, including buildings, bridges, and roadways. The methods involve (i) embodying multiple GNSS rovers within the boundary of the stationary and/or mobile system being monitored by the GNSS system network, (ii) receiving GNSS signals transmitted from GNSS satellites orbiting the Earth, and (iii) determining the geo-location and time-stamp of each GNSS rover while the stationary and/or mobile system is being monitored for spatial displacement, distortion and/or deformation, using GNSS-based rover data processing methods practiced aboard the system, or remotely within the application and database servers of the data center of the GNSS system network.

Abstract: A system network and methods supported by a constellation of GNSS satellites orbiting around the Earth, and deployed for precise remote monitoring of the spatial displacement, distortion and/or deformation of stationary and/or mobile systems, including buildings, bridges, and roadways. The methods involve (i) embodying multiple GNSS rovers within the boundary of the stationary and/or mobile system being monitored by the GNSS system network, (ii) receiving GNSS signals transmitted from GNSS satellites orbiting the Earth, and (iii) determining the geo-location and time-stamp of each GNSS rover while the stationary and/or mobile system is being monitored for spatial displacement, distortion and/or deformation, using GNSS-based rover data processing methods practiced aboard the system, or remotely within the application and database servers of the data center of the GNSS system network.

Abstract: A building intelligence gathering, assessment and decision-support system including a GPS system deployed about the Earth and supporting a plurality of GPS satellites for transmitting GPS signals to the surface of the Earth. A building data sensor network, including a plurality of GPS-tracked rooftop-mounted sensors, are mounted on the rooftop surface of the building, and adapted for collecting GPS-indexed data specifying conditions on the rooftop surface at particular dates and times of the year. The building rooftop conditions includes one or more conditions selected from the group consisting of snow load conditions, windspeed and direction, and temperature. The system also includes one or more hand-held mobile augmented-reality (AR) based rooftop navigation and inspection devices, each configured for communication with communication servers within a data center over a wireless data communication network.

Abstract: An Internet-based system for helping building management team members in significant ways: (i) predicting and forecasting when excessive snow load conditions present serious risks to a building's structure; (ii) receiving automatic notifications when snow load conditions are developing at specific regions on a building rooftop to warrant intervention and automated mitigation through the use of VR-guided snow removing robot systems; (iii) collecting various forms of intelligence about conditions developing on and about a building rooftop and storing such information with annotations for use in supporting intelligent decision making processes; (iv) quickly, efficiently and safely removing dangerous risk-presenting snow load conditions on a building rooftop while minimizing risk to human workers and increasing building operating efficiency; and (v) automatically removing excessive snow load conditions at specified regions on a building's rooftop.

Abstract: A snow water equivalent (SWE) networked array for installation on ground surface of variable surface geometry, and configured for measuring snow water equivalent (SWE) in remote snow fall accumulations. The SWE-measuring networked array includes a plurality of snow data collection modules (SDCM) connected together over a specified region of space, and each SDCM measuring the weight and temperature of snow over its local weight surface, and generating electrical signals representative of the weight and temperature of the snow load on the weigh surface.

Abstract: A snow water equivalent (SWE) networked array for installation on ground surface of variable surface geometry, and configured for measuring snow water equivalent (SWE) in remote snow fall accumulations. The SWE-measuring networked array includes a plurality of snow data collection modules (SDCM) connected together over a specified region of space, and each SDCM measuring the weight and temperature of snow over its local weight surface, and generating electrical signals representative of the weight and temperature of the snow load on the weigh surface.

Abstract: An Internet-based system for helping building management team members in significant ways: (i) predicting and forecasting when excessive snow load conditions present serious risks to a building's structure; (ii) receiving automatic notifications when snow load conditions are developing at specific regions on a building rooftop to warrant intervention and automated mitigation through the use of VR-guided snow removing robot systems; (iii) collecting various forms of intelligence about conditions developing on and about a building rooftop and storing such information with annotations for use in supporting intelligent decision making processes; (iv) quickly, efficiently and safely removing dangerous risk-presenting snow load conditions on a building rooftop while minimizing risk to human workers and increasing building operating efficiency; and (v) automatically removing excessive snow load conditions at specified regions on a building's rooftop.