Abstract: Novel tools and techniques are provided for implementing visual impairment detection for free-space optical communication (“FSOC”) systems. In various embodiments, a computing system might receive, either from a camera or from a database, images (and/or videos) of an optical field of view (“FOV”) of the camera, the optical FOV comprising an optical beam(s) of a first FSOC system; might autonomously analyze the captured images (and/or videos) to determine whether an object(s) is moving within proximity to an optical beam(s) of the first FSOC system, to perform at least one of reactive learning or proactive learning regarding potential interruption of the optical beam(s) of the first FSOC system, and/or to determine one or more preventative measures to prevent interruption of the optical beam(s) of the first FSOC system; and might autonomously initiate one or more first tasks and/or the one or more preventative measures, based on the analysis.

Abstract: Novel tools and techniques are provided for implementing visual impairment detection for free-space optical communication (“FSOC”) systems. In various embodiments, a computing system might receive, either from a camera or from a database, images (and/or videos) of an optical field of view (“FOV”) of the camera, the optical FOV comprising an optical beam(s) of a first FSOC system; might autonomously analyze the captured images (and/or videos) to determine whether an object(s) is moving within proximity to an optical beam(s) of the first FSOC system, to perform at least one of reactive learning or proactive learning regarding potential interruption of the optical beam(s) of the first FSOC system, and/or to determine one or more preventative measures to prevent interruption of the optical beam(s) of the first FSOC system; and might autonomously initiate one or more first tasks and/or the one or more preventative measures, based on the analysis.

Abstract: Novel tools and techniques are provided for implementing visual impairment detection for free-space optical communication (“FSOC”) systems. In various embodiments, a computing system might receive, either from a camera or from a database, images (and/or videos) of an optical field of view (“FOV”) of the camera, the optical FOV comprising an optical beam(s) of a first FSOC system; might autonomously analyze the captured images (and/or videos) to determine whether an object(s) is moving within proximity to an optical beam(s) of the first FSOC system, to perform at least one of reactive learning or proactive learning regarding potential interruption of the optical beam(s) of the first FSOC system, and/or to determine one or more preventative measures to prevent interruption of the optical beam(s) of the first FSOC system; and might autonomously initiate one or more first tasks and/or the one or more preventative measures, based on the analysis.

Abstract: Novel tools and techniques are provided for implementing visual impairment detection for free-space optical communication (“FSOC”) systems. In various embodiments, a computing system might receive, either from a camera or from a database, images (and/or videos) of an optical field of view (“FOV”) of the camera, the optical FOV comprising an optical beam(s) of a first FSOC system; might autonomously analyze the captured images (and/or videos) to determine whether an object(s) is moving within proximity to an optical beam(s) of the first FSOC system, to perform at least one of reactive learning or proactive learning regarding potential interruption of the optical beam(s) of the first FSOC system, and/or to determine one or more preventative measures to prevent interruption of the optical beam(s) of the first FSOC system; and might autonomously initiate one or more first tasks and/or the one or more preventative measures, based on the analysis.