Abstract: A system and corresponding method is disclosed for monitoring and conducting large-scale performance verification of a city's lighting infrastructure. In particular, the current invention combines measurements of lighting performance measurements along city roadways with regulatory requirements for the roadways. In various embodiments, the current invention then presents a three-dimensional visualization of the adequacy of existing roadway lighting with respect to these regulatory requirements.

Abstract: A system and method for providing object recognition using artificial neural networks. The method includes capturing a plurality of reference images with a camera associated with an edge node on a communication network. The reference images are received by a centralized server on the communication network. The reference images are analyzed with a parent neural network of the centralized server to determine a subset of objects identified by the parent neural network in the reference images. One or more filters that are responsive to the subset of objects are selected from the parent neural network. A pruned neural network is created from only the one or more filters. The pruned neural network is deployed to the edge node. Real-time images are captured with the camera of the edge node and objects in the real-time images are identified with the pruned neural network.

Abstract: A method (400) for analyzing output of lighting units (10) in a lighting system (100) includes the steps of: (i) simulating (430), based on data from a photometric database (310), the output of a lighting unit; (ii) receiving and storing (420), from a database (330) of historical information, historical observed data about the output of the lighting unit; (iii) receiving (450) observed data (36) about the output of the lighting unit; (iv) generating (440) a model of the lighting system based at least in part on the simulated output of the lighting unit and the historical observed data about the output of the lighting unit, wherein the model comprises localization information for the lighting unit; and (v) comparing (470) the received observed data about the output of the lighting unit to the generated model, wherein a fault is detected if the observed data varies from the generated model by a predetermined amount.

Abstract: A system and corresponding method is disclosed for monitoring and conducting large-scale performance verification of a city's lighting infrastructure. In particular, the current invention combines measurements of lighting performance measurements along city roadways with regulatory requirements for the roadways. In various embodiments, the current invention then presents a three-dimensional visualization of the adequacy of existing roadway lighting with respect to these regulatory requirements.

Abstract: A system and corresponding method is disclosed for monitoring and conducting large-scale performance verification of a city's lighting infrastructure. In particular, the current invention combines measurements of lighting performance measurements along city roadways with regulatory requirements for the roadways. In various embodiments, the current invention then presents a three-dimensional visualization of the 5 adequacy of existing roadway lighting with respect to these regulatory requirements.

Abstract: An object detection system (100) is disclosed herein. The system 100 includes a lighting system (50) to illuminate an object and at least one selectable light output quality, at least one image sensor (70) positioned to obtain an image of an object, and at least one processor (10) coupled to the image sensor (70) to receive the image of the object. The processor (10) includes a monitoring engine (30) configured to determine if the image has an image quality metric (IQM) value or an expected confidence value corresponding to the IQM value that meets a predetermined threshold and a light settings calculation module (40) configured to select the light output qualities of the lighting system (50) to improve the IQM value or the expected confidence value corresponding to the IQM value to meet the predetermined threshold.

Abstract: Disclosed are a system and method for improving the signal-to-noise ratio of sensors in a connected lighting system. At individual nodes of the system, sensor measurements are obtained during relatively quiescent time periods to model background noise. Collaboration between nodes is performed to yield a more accurate model of background noise. These noise models can then be used in de-noising subsequent sensor measurements.

Abstract: The described embodiments relate to systems, methods, and apparatuses for controlling a network of lights (120) according to whether people (122) who are observing the lights are visitors from a different location (108). Visitors can be identified by using network connection data (116, 208) that includes entries corresponding to personal devices of visitors to a city. The network connection data can be filtered to identify how many personal devices are associated with people visiting from a different city. If the number of visitors exceeds some threshold relative to non-visitors, a lighting arrangement in the city can be controlled to display features that would appeal to the visitors. The features can correspond to aspects of the city where the visitors are from and can therefore make the city more attractive.

Abstract: A system and method for providing object recognition using artificial neural networks. The method includes capturing a plurality of reference images with a camera associated with an edge node on a communication network. The reference images are received by a centralized server on the communication network. The reference images are analyzed with a parent neural network of the centralized server to determine a subset of objects identified by the parent neural network in the reference images. One or more filters that are responsive to the subset of objects are selected from the parent neural network. A pruned neural network is created from only the one or more filters. The pruned neural network is deployed to the edge node. Real-time images are captured with the camera of the edge node and objects in the real-time images are identified with the pruned neural network.

Abstract: The described embodiments relate to systems, methods, and apparatuses for controlling energy resources available to micro-grids of a city based on mobility patterns of people moving within the micro-grids. The mobility patterns can be identified using a network of sensors within each micro-grid for collecting data related to the movement of people within the micro-grids. The mobility patterns can be used to estimate energy demand for each micro-grid and prioritize the energy demands to determine the energy resources that would be suitable for supplying power to each micro-grid. This allows for micro-grids to dynamically and efficiently change their power sources according to predictions about the movement of people within the micro-grids.

Abstract: A system and method for maintaining a system configuration to provide desired system performance is disclosed. The system comprises a processing unit receiving sensor data associated with environmental conditions within an area, generating a map of the area based on the received sensor data, determining a change in the map of the area and determining at least one system commissioning parameter associated with the determined change in the map to compensate for or correct the change in the map. In one aspect of the invention, the sensor data is provided through a plurality of mobile devices.

Abstract: Techniques are described herein for to improving optical wireless communications based on mobility patterns. In various embodiments, one or more mobility patterns observed in an area over time may be determined (302). The area may be illuminated by one or more lighting units (102) configured to transmit information using optical wireless communications (“OWC”). An applicable mobility pattern may be selected (308) from the one or more mobility patterns. Based on the selected mobility pattern, usage in the area of a plurality of OWC-based mobile apps (230) may be predicted (310). One or more OWC resources of at least one of the one or more lighting units may be allocated (312) for transmission of data to one or more of the plurality of OWC-based mobile apps operating on one or more mobile devices operated within the area. In various embodiments, the allocating may be based at least in part on the predicted usage.

Abstract: A system and corresponding method is disclosed for monitoring and conducting large-scale performance verification of a city's lighting infrastructure. In particular, the current invention combines measurements of lighting performance measurements along city roadways with regulatory requirements for the roadways. In various embodiments, the current invention then presents a three-dimensional visualization of the 5 adequacy of existing roadway lighting with respect to these regulatory requirements.

Abstract: The described embodiments relate to systems, methods, and apparatuses for controlling lights (130) in an area of a city (200) based on demographic data and/or mobility pattern data (120). Using the demographic data and/or the mobility pattern data, the lights can be arranged to attract people (214) to the area (210) where the lights are located. The mobility pattern data can be used to identify when people are typically moving towards the area, in order that the lights can be prepared to attract people in advance of their arrival. Furthermore, an output of the lights can be measured to measure certain characteristics about the lights so that the lights can be adjusted to better appeal to the demographic of people in the area.

Abstract: A method (400) for analyzing output of lighting units (10) in a lighting system (100) includes the steps of: (i) simulating (430), based on data from a photometric database (310), the output of a lighting unit; (ii) receiving and storing (420), from a database (330) of historical information, historical observed data about the output of the lighting unit; (iii) receiving (450) observed data (36) about the output of the lighting unit; (iv) generating (440) a model of the lighting system based at least in part on the simulated output of the lighting unit and the historical observed data about the output of the lighting unit, wherein the model comprises localization information for the lighting unit; and (v) comparing (470) the received observed data about the output of the lighting unit to the generated model, wherein a fault is detected if the observed data varies from the generated model by a predetermined amount.

Abstract: The described embodiments relate to systems, methods, and apparatuses for controlling a network of lights (120) according to whether people (122) who are observing the lights are visitors from a different location (108). Visitors can be identified by using network connection data (116, 208) that includes entries corresponding to personal devices of visitors to a city. The network connection data can be filtered to identify how many personal devices are associated with people visiting from a different city. If the number of visitors exceeds some threshold relative to non-visitors, a lighting arrangement in the city can be controlled to display features that would appeal to the visitors. The features can correspond to aspects of the city where the visitors are from and can therefore make the city more attractive.

Abstract: Techniques are described herein for to improving optical wireless communications based on mobility patterns. In various embodiments, one or more mobility patterns observed in an area over time may be determined (302). The area may be illuminated by one or more lighting units (102) configured to transmit information using optical wireless communications (“OWC”). An applicable mobility pattern may be selected (308) from the one or more mobility patterns. Based on the selected mobility pattern, usage in the area of a plurality of OWC-based mobile apps (230) may be predicted (310). One or more OWC resources of at least one of the one or more lighting units may be allocated (312) for transmission of data to one or more of the plurality of OWC-based mobile apps operating on one or more mobile devices operated within the area. In various embodiments, the allocating may be based at least in part on the predicted usage.

Abstract: A lighting-system (100) for illuminating an environment, the lighting system comprising a plurality of lighting modules (111, 112, 113) and a lighting-system control device (130). The lighting modules comprise: —a light source (121) for emitting light, —a programmable controller (122) configured to control an operation of the light source, and —a network interface (123) configured to allow the lighting module to communicate via a network. The lighting-system control device (130) comprises: —a processor circuit (133) configured to determine lighting control data to change the light spectrum of the light source based on the mobility data of the at least one user, and to transmit the lighting control data to at least one lighting module of the plurality of lighting modules to program said lighting module according to the lighting control data.

Abstract: The described embodiments relate to systems, methods, and apparatuses for controlling energy resources available to micro-grids of a city based on mobility patterns of people moving within the micro-grids. The mobility patterns can be identified using a network of sensors within each micro-grid for collecting data related to the movement of people within the micro-grids. The mobility patterns can be used to estimate energy demand for each micro-grid and prioritize the energy demands to determine the energy resources that would be suitable for supplying power to each micro-grid. This allows for micro-grids to dynamically and efficiently change their power sources according to predictions about the movement of people within the micro-grids.

Abstract: The described embodiments relate to systems, methods, and apparatuses for controlling lights (130) in an area of a city (200) based on demographic data and/or mobility pattern data (120). Using the demographic data and/Gall or the mobility pattern data, the lights can be arranged to attract people (214) to the area (210) where the lights are located. The mobility pattern data can be used to identify when people are typically moving towards the area, in order that the lights can be prepared to attract people in advance of their arrival. Furthermore, an output of the lights can be measured to measure certain characteristics about the lights so that the lights can be adjusted to better appeal to the demographic of people in the area.