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.

Detecting passengers traveling through a transit gate, includes transmitting a first beam from a first optical emitter on a side of the transit gate to a first plurality of optical receivers on an opposite side of the transit gate, and transmitting a second beam from a second optical emitter on the opposite side of the transit gate to a second plurality of optical receivers on the side of the transit gate in a direction opposite the direction of the first beam. Transmit intensities are adjusted based on learned patterns or drifts in the receive intensities of light beams. Detection times are reduced based on pairing additional optical receivers with a single optical emitter.

Detecting passengers traveling through a transit gate, includes transmitting a first beam from a first optical emitter on a side of the transit gate to a first plurality of optical receivers on an opposite side of the transit gate, and transmitting a second beam from a second optical emitter on the opposite side of the transit gate to a second plurality of optical receivers on the side of the transit gate in a direction opposite the direction of the first beam. Transmit intensities are adjusted based on learned patterns or drifts in the receive intensities of light beams. Detection times are reduced based on pairing additional optical receivers with a single optical emitter.

A system and method for automatically detecting unauthorized entry into a pool requiring no user involvement, and having a high degree of accuracy. The system comprises a plurality of light beam emitter devices and a plurality of light beam receiver devices positioned about the pool and a processor in communication with the plurality of light beam emitter devices and the plurality of light beam receiver devices. The plurality of light beam emitter devices emit a plurality of light beams and the plurality of light beam receiver devices receive a plurality of emitted light beams to form a grid extending across a the pool. Additionally, the processor monitors the grid, detects unauthorized entry into the pool based on an interruption of the grid, and generates and transmits an alarm message based on whether a level of the interruption of the grid exceeds a predetermined threshold.

A system for detecting an overheight and/or an over-width of a vehicle or a load carried by a vehicle includes a plurality of dimension sensors. The system also includes a controller configured to determine an object passing through the system based on the inputs received from at least one of the sensors, and determines at least one of a vertical continuous presence of the object or a horizontal continuous presence of the object. The controller determines the object as the load carried by the vehicle if at least one of the vertical continuous presence of the object or the horizontal continuous presence of the object is detected and generates an alert when a maximum height of the load is above a height limit and/or the maximum width of the load is above a width limit.

A safety detector including a detection module configured for reading a control signal at the input, the detector including two supply terminals, a first control input and a first control output, a first safety output and a second safety output, and a first free terminal and a second free terminal, the detector including: a second control input connected to the first free terminal and a second control output connected to the second free terminal, and a test module configured for notably applying a first test sequence including a disabling of the first control output and a test of a start loop connected between the second control output and the first control input.

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.

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.

Systems and methods of intrusion detection into a rack enclosure are disclosed. An example method may include, extracting a projected light terminator image from a captured image, performing image correction operations on the projected light terminator image, processing the projected light terminator image utilizing image processing operations to determine a corrected projected light terminator image, determining a collection of image segments based on the corrected projected light terminator image, establishing one or more baseline image metrics of the collection of the image segments, evaluating the one or more baseline image metrics for changes with operational image segment characteristics, and communicating any baseline image metric changes to a management device.

Detecting passengers traveling through a transit gate, includes transmitting a first beam from a first optical emitter on a side of the transit gate to a first plurality of optical receivers on an opposite side of the transit gate, and transmitting a second beam from a second optical emitter on the opposite side of the transit gate to a second plurality of optical receivers on the side of the transit gate in a direction opposite the direction of the first beam. Transmit intensities are adjusted based on learned patterns or drifts in the receive intensities of light beams. Detection times are reduced based on pairing additional optical receivers with a single optical emitter.