A system to identify incidents associated with streetlight fixtures based on sensor data from one or more smart sensor devices. Each smart sensor device is coupled to a respective streetlight fixture and captures data from one or more sensors. The data from a single smart sensor device or a plurality of smart sensor devices is aggregated to generate a current data signature of the one or more smart sensor devices. The current data signature is compared to a plurality of known signatures to determine if an incident associated with a streetlight fixture has occurred. Such incidents can include a failed light source, a failing light source, a weather incident, a geologic incident, etc. Depending on the type of incident an instruction is sent to the one or more smart sensor devices to perform one or more responsive actions.

A system to identify incidents associated with streetlight fixtures based on sensor data from one or more smart sensor devices. Each smart sensor device is coupled to a respective streetlight fixture and captures data from one or more sensors. The data from a single smart sensor device or a plurality of smart sensor devices is aggregated to generate a current data signature of the one or more smart sensor devices. The current data signature is compared to a plurality of known signatures to determine if an incident associated with a streetlight fixture has occurred. Such incidents can include a failed light source, a failing light source, a weather incident, a geologic incident, etc. Depending on the type of incident an instruction is sent to the one or more smart sensor devices to perform one or more responsive actions.

In some examples, a computing device can include a processor resource and a non-transitory memory resource storing machine-readable instructions stored thereon that, when executed, cause the processor resource to: instruct an imaging device to capture an input image, determine image properties of the input image, activate a portion of a plurality of light sources based on a physical location of the plurality of light sources and the determined image properties of the input image, and instruct the imaging device to capture an output image when the portion of the plurality of light sources are activated.

A device may be configured to detect a glare condition and may comprise a photo sensing circuit and a visible light sensing circuit. The photo sensing circuit may be configured to periodically generate an illuminance signal that indicates an illuminance value. The visible light sensing circuit may be configured to periodically record images of the space at an exposure time. The device may receive an illuminance signal from the photo sensing circuit and determine a present illuminance based on the illuminance signal. The device may adjust the frequency at which the visible light sensing circuit records images based on the present illuminance. The exposure time may be determined based on the present illuminance and a glare condition type. An image recorded at a respective exposure time may wash out pixels above a certain illuminance value. The device may detect a glare condition at the location of washed out pixels.

A device may be configured to detect a glare condition and may comprise a photo sensing circuit and a visible light sensing circuit. The photo sensing circuit may be configured to periodically generate an illuminance signal that indicates an illuminance value. The visible light sensing circuit may be configured to periodically record images of the space at an exposure time. The device may receive an illuminance signal from the photo sensing circuit and determine a present illuminance based on the illuminance signal. The device may adjust the frequency at which the visible light sensing circuit records images based on the present illuminance. The exposure time may be determined based on the present illuminance and a glare condition type. An image recorded at a respective exposure time may wash out pixels above a certain illuminance value. The device may detect a glare condition at the location of washed out pixels.

Dimmable external vehicle lighting and methods of use are provided herein. An example method includes determining environmental light intensity around a vehicle, determining a luminance of an external light of the vehicle, determining a difference in magnitude between the environmental light intensity and the luminance of the external light, and selectively adjusting the luminance of the external light based on the difference.

Dimmable external vehicle lighting and methods of use are provided herein. An example method includes determining environmental light intensity around a vehicle, determining a luminance of an external light of the vehicle, determining a difference in magnitude between the environmental light intensity and the luminance of the external light, and selectively adjusting the luminance of the external light based on the difference.

Disclosed herein are methods, systems, and devices for providing optimized simultaneous illumination for human vision and machine based navigation vision on a semi-autonomous vehicle. In one embodiment, a system includes a first control output configured to provide first illumination control information including first active cycle times for a first illumination source. The first illumination source is configured to provide a first frequency band of illumination for machine vision navigation of the semi-autonomous vehicle. The system further includes a second control output configured to provide second illumination control information including second active cycle times for a second illumination source. The second illumination source is configured to provide a second frequency band of illumination for a human driver of the semi-autonomous vehicle. The system further includes a first monitor input configured to receive ambient illumination information from a camera system.

Disclosed herein are methods, systems, and devices for providing optimized simultaneous illumination for human vision and machine based navigation vision on a semi-autonomous vehicle. In one embodiment, a system includes a first control output configured to provide first illumination control information including first active cycle times for a first illumination source. The first illumination source is configured to provide a first frequency band of illumination for machine vision navigation of the semi-autonomous vehicle. The system further includes a second control output configured to provide second illumination control information including second active cycle times for a second illumination source. The second illumination source is configured to provide a second frequency band of illumination for a human driver of the semi-autonomous vehicle. The system further includes a first monitor input configured to receive ambient illumination information from a camera system.

A processing system including at least one processor may detect at least one dark zone in a vicinity of a user, determine at least one lighting feature for an illumination of the at least one dark zone in accordance with a user profile of the user, identify at least one light source to provide the illumination of the at least one dark area in accordance with the at least one lighting feature that is determined, and transmit an instruction to the at least one light source to provide the illumination of the at least one dark zone in accordance with the at least one lighting feature that is determined.