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: A method of assessing risk of a negotiable instrument may include receiving a deposit inquiry from a depositing financial institution. The deposit inquiry may include a first routing number of an issuing financial institution, a first account number of a check issued by the issuing financial institution, a second routing number of a deposit account, and a second account number of the deposit account. The method may include retrieving risk factors associated with the first account number using the first account number and the first routing number and risk factors associated with the second account number using the second account number and the second routing number. The method may include providing the risk factors associated with the first account number to the depositing financial institution and providing the risk factors associated with the second account number to the issuing financial institution.

Abstract: The brain control interface system comprises: a brain control interface configured to detect brain signals indicative of brain activity of a user in an environment, an input configured to obtain data indicative of a current light scene of one or more lighting devices in the environment, a memory configured to store processing methods associated with different light scenes, one or more processor configured to: select, from the processing methods stored in the memory, a processing method in accordance with the current light scene, apply the selected processing method to obtain and/or process the brain signals, derive a control command and/or a mental state of the user from the brain signals, and control the controllable device based on the derived control command and/or the derived mental state.

Abstract: A system and methods are provided for spatial analysis that involves estimating a number of occupants in a room. This may include a motion sensor configured to generate motion samples, a microphone configured to generate audio samples, and a communication interface configured to communicate with a computing system. The systems and methods involve detecting motion events from the motion samples to determine a first estimated number of occupants in the room, analyzing the audio samples to derive a second estimated number of occupants in the room, and comparing the first estimated number to the second estimated number. As a result, an output is generated that includes a number of occupants in the room in response to the comparison.

Abstract: A method for optimizing a neural network is provided, including: (1) capturing, via a first sensor group having a first field of view, a first sample set having a first sensor domain corresponding to the first field of view; (2) capturing, via a second sensor group having a second field of view, a second sample set having a second sensor domain corresponding to the second field of view; (3) generating regions of interest of the second sample set; (4) translating the regions of interest to the first sensor domain; (5) identifying nodes of the neural network which correspond to the translated regions; and (6) optimizing the neural network by at least one of (a) increasing the weight value of the nodes corresponding to the one or more translated regions and (b) decreasing the weight value of the nodes not corresponding to the one or more translated regions.

Abstract: An asset health system includes an edge-based computing device that receives high-granularity asset data for an asset from an asset data source or asset database and receives contextual data from a contextual database. The edge-based computing device processes the asset data and the contextual data with a machine-learned model. The machine-learned model includes processor-executable instructions for extracting run cycle data from the asset data to determine a run cycle of the asset, creating a feature vector based on the asset data that characterizes the run cycle, comparing the feature vector to a nominal feature vector to detect one or more anomalies, validating the one or more detected anomalies with the contextual data, determining a health index for the asset based on the one more anomalies, determining a mitigating action for mitigating the anomalies, and notifying a system operator regarding the one or more detected anomalies, health index, and mitigating actions.

Abstract: A system for determining occupancy in an environment is provided. The system includes plurality of sensor bundles, with each bundle including a presence sensor and a motion sensor. The system further includes a controller in communication with each sensor bundle. The controller is configured to designate one of the sensor bundles as presence triggered if persons are present within a field of view of the presence sensor. The controller is further configured to designate one of the sensor bundles as motion triggered if persons are moving within a field of view of the motion sensor. The controller is further configured to determine a triggered bundle count of the sensor bundles which are both presence triggered and motion triggered. The controller is further configured to determine an occupancy count for the environment based upon the triggered bundle count.

Abstract: A sensor system (100) for monitoring a storage space comprising a plurality of items, comprising sensor(s) (110) configured to register occupancy of objects (120) in a plurality of zones (130) of the storage space, wherein each zone of the plurality of zones is associated with a respective hierarchic order, A, B, C, a processor (140) configured to determine a level of occupancy of the objects in at least two zones, compare a first level of occupancy of the objects of the first zone with a second level of occupancy of the objects of the second zone, and an alarm (150) configured to generate an alarm signal if the first level of occupancy of the first zone of the first hierarchic order, A, is lower than the second level of occupancy of the second zone of the second hierarchic order, B.

Abstract: A brain control interface system for determining a baseline for detecting brain activity of a user is disclosed. The brain control interface system comprising: a brain control interface configured to detect brain signals indicative of brain activity of a user in an environment, a memory configured to store activities of the user associated with different light scenes, a processor configured to: select, from the activities stored in the memory, a first activity of the user, control one or more lighting devices according to a first light scene associated with the first activity, detect brain signals of the user while the first light scene is active, determine, based on the detected brain signals, a first baseline for the brain signals, and store an association between the first baseline and the first light scene and/or the first activity.

Abstract: The brain control interface system comprises: a brain control interface configured to detect brain signals indicative of brain activity of a user in an environment, an input configured to obtain data indicative of a current light scene of one or more lighting devices in the environment, a memory configured to store processing methods associated with different light scenes, one or more processor configured to: select, from the processing methods stored in the memory, a processing method in accordance with the current light scene, apply the selected processing method to obtain and/or process the brain signals, derive a control command and/or a mental state of the user from the brain signals, and control the controllable device based on the derived control command and/or the derived mental state.

Abstract: A method for analyzing consumer behavior within a retail space can include receiving data associated with consumers in communications signals from local devices located in the retail space, where the local devices receive some of the data in visible light communication (VLC) signals broadcast by electrical devices, where each local device is associated with one of the consumers in the retail space at a point in time, and where the data lacks information that identifies the consumers. The method can also include attributing, by the controller using a multi-stage clustering process, the data to discrete consumers for a period of time that includes each point in time. The method can further include assigning the discrete consumers to at least one of a number of groups defined by one or more characteristics measured from the data, where the discrete consumers within a group share a common characteristic.

Abstract: The present disclosure is generally directed to systems and methods for controlling lighting based on the type of written content on smart coated surfaces. A smart coated surface generates pressure data based on the written content. A feature extractor then extracts features from the pressure data describing the written content. A content classifier then feeds the features into a recurrent neural network, such as a Long Short-Term Memory network to select a content label. A lighting controller then controls luminaires based on the content label and data from additional sensors. In this way, the system controls the luminaires based on the type of the written content without evaluating or decoding the content itself. For example, the system is able to label the content as text based on written patterns without interpreting what the text actually says. Accordingly, the content written on the smart coated surface remains private and secure.

Abstract: Monitoring systems and methods are disclosed. The systems include a sensor device having a single-pixel thermopile (SPT) sensor and a controller in communication with the sensor device. The controller is configured to determine or obtain training data for detecting first and second configurations of one or more occupants in the space; receive a temperature signal from the SPT sensor; detect a step change in the temperature signal; determine first and second probabilities for at least one feature of a shape or pattern of the temperature signal, the first and second probabilities corresponding to the first and second configurations of the one or more occupants in the space based on the training data, respectively; and identify a class label for the temperature signal based on the determined first and second probabilities. The class label corresponds with the first or second configurations of the one or more occupants in the space.

Abstract: The present invention is related to an application of a Single Pixel Thermopile (SPT). The invention provides a sensor device comprising a Single Pixel Thermopile and a controller, wherein the Single Pixel Thermopile is configured to monitor a detection region and to measure over time a temperature signal of said detection region; wherein the detection region is bounded by a surface and the Single Pixel Thermopile is oriented at an angle of at least 20 degrees normal to the surface; wherein a projection of the detection region onto the surface renders an elongated detection area with a length axis and a width axis; wherein the controller is configured to: obtain the temperature signal of the detection region; determine a movement characteristic of a person moving across said surface by detecting a pattern in the temperature signal of the detection region; output an output signal configured to control an electrical device upon determining the movement characteristic.

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 present disclosure is directed to inventive systems, methods, and devices for use in an outdoor lighting network for drone detection. The drone detection system includes one or more lighting fixtures, one or more radar sensors to detect a moving object, and one or more controllers. The controllers receive data from the sensors, determine the velocity and velocity change rate of the object over a period of time, and analyze flight data pertaining to the moving object to determine if the object is a drone. The system can determine the starting location of the moving object, and send a signal indicating its starting location. The system can also track the position of the moving object in the outside environment.

Abstract: A system and method for determining a number of occupants at a location using multiple modalities. The method includes gathering a first data set with a motion sensor of the lighting system. A second data set is gathered with a transceiver of an RF subsystem. First and second estimates are calculated from the second data set using first and second algorithms. The first estimate and the second estimate are fused to create a fused occupant estimate. The first algorithm, the second algorithm, or both the first algorithm and the second algorithm are trained by inputting the second occupant estimate and/or the second set of data to recalibrate parameters of the first algorithm and/or inputting the first occupant estimate and/or the first set of data to recalibrate parameters during training of the second algorithm. A building control system can operated in response to the fused occupant estimate.

Abstract: A system for monitoring face mask wearing of a monitored person is provided. The system includes a controller communicatively coupled to one or more multipixel thermopile sensors (“MPTs”). The controller is configured to (1) detect a monitored person region within a heat map based on one or more data sets captured by the MPTs; (2) locate a head region within the monitored person region by identifying a high intensity pixel cluster within the monitored person region; (3) determine a facing-direction of the head region based on a major axis of the monitored person region or a minor axis of the monitored person region; (4) locate a mouth region within the head region based on the facing-direction; (5) determine an exhalation region of the heat map based on the mouth region; (6) determine a mask state of the monitored person based on the exhalation region and a temperature gradient classification model.

Abstract: A system for monitoring social distancing is provided. The system includes a controller communicatively coupled to sensors within an environment. The controller may be configured to (1) receive an expected sensor behavior model for each of the sensors; (2) generate an adjusted sensor behavior model for each of the sensors based on the expected sensor behavior model for each of the sensors and an environment adjustment model for each of the sensors; (3) receive a layout of the environment; (4) generate an expected layout behavior model based on the layout and the adjusted sensor behavior model; (5) capture, via the sensors, an observed behavior data set during a measurement period; and (6) determine a social distancing state of individuals in the environment as distanced or not-distanced based on the observed behavior data set and the expected layout behavior model.

Abstract: Systems and methods for controlling and interacting with plant lighting are provided. The methods include: determining or receiving location information indicative of relative locations of a plurality of sensors arranged around a portion of a plant, wherein the plurality of sensors are distributed among a plurality of lighting elements and the plurality of sensors are configured to capture sensor data for at least one parameter of the plant; measuring sensor data for the at least one parameter of the plant; annotating, by a processor, the sensor data with the location information of the plurality of sensors and timestamp information; analyzing, by the processor, the annotated sensor data; and determining a state of the plant based on the sensor data. Methods further include receiving, by a lighting controller, user input corresponding to the state of the plant and controlling the lighting elements based on the user input.