PORTABLE GAS ANALYZER
    12.
    发明公开

    公开(公告)号:US20230314391A1

    公开(公告)日:2023-10-05

    申请号:US17594751

    申请日:2020-05-08

    IPC分类号: G01N33/00

    摘要: A portable gas analyzer includes multiple docking stations connected to a pneumatic flowpath through the gas analyzer. Modules are removably mounted to the docking stations. Some modules can be mounted at any one of the docking stations. The modules can include gas sensors and a microcontroller configured to generate data based on signals generated by the gas sensors. The modules are configured to simultaneously form each of electrical, mechanical, and pneumatic connections with the gas analyzer when mounted to the docking station.

    Environmental emission monitoring system with GHG emission thresholding and related method

    公开(公告)号:US11719678B2

    公开(公告)日:2023-08-08

    申请号:US17241468

    申请日:2021-04-27

    摘要: An environmental emission monitoring system may include satellites configured to sense GHG emissions data for an AOI, and a server. The server may be configured to obtain the sensed GHG emissions data from the satellites, obtain geospatial positions of stationary GHG emitting point sources within the AOI, and generate expected stationary GHG emission data for the stationary GHG emitting point sources within the AOI and based upon the geospatial positions. The server may also be configured to obtain geospatial path data for GHG emitting vehicles moving within the AOI, generate expected vehicle GHG emission data for the GHG emitting vehicles moving within the AOI and based on the geospatial path data, and compare a sum of the expected stationary GHG emission data and expected vehicle GHG emission data with the sensed GHG emissions data to identify any stationary GHG emitting point source and any GHG emitting vehicle outside of a respective GHG emission threshold.

    Machine learning monitoring air quality

    公开(公告)号:US11719676B2

    公开(公告)日:2023-08-08

    申请号:US17221741

    申请日:2021-04-02

    IPC分类号: G01N33/00 G06N20/00

    摘要: A system, method and a monitoring device for monitoring air quality of a closed space are disclosed. A plurality of ducts is coupled with the closed space and the plurality of monitoring devices monitors a quality of air inside the plurality of ducts. Each of the plurality of monitoring devices stores a location of placement of each of a monitoring device present inside the closed space, learns a level of carbon dioxide present inside the closed space over a period of time and estimate a number of occupants present inside the closed space based on the level of carbon dioxide present inside the closed space using a machine learning model. Further, the plurality of monitoring devices transmits the monitored quality of air inside the closed space along with the location of the placement of each of the monitoring device and the identified number of occupants to a cloud server.

    FLUID QUALITY TRACING METHOD AND SYSTEM
    19.
    发明公开

    公开(公告)号:US20230184732A1

    公开(公告)日:2023-06-15

    申请号:US17945901

    申请日:2022-09-15

    IPC分类号: G01N33/00 G06F16/29

    摘要: A fluid quality tracing method includes obtaining pieces of fluid concentration distribution data of a detected region corresponding to detection time points respectively, generating pieces of concentration grid data respectively according to the pieces of fluid concentration distribution data, obtaining pieces of fluid moving data of the detected region corresponding to the detection time points respectively, obtaining estimated positions according to the fluid moving data and an initial position, and creating a fluid concentration trajectory according to the pieces of concentration grid data, the initial position and the estimated positions. The initial position and the estimated positions are located in the detected region. The fluid concentration trajectory includes line segments with terminals corresponding to the initial position and the estimated positions respectively, and the line segments indicate concentration representative values respectively.