Abstract: A detection system (100) is disclosed herein. The system includes a sensor system (120) positioned to obtain image sensor data at different times of a live cannabis plant and a data storage system (130) configured to store the image sensor data. The system further includes a processor (140) coupled to the data storage system to receive the image sensor data. The processor includes a target region selection module (160) configured to determine a region of the live cannabis plant that contains a flower and generate a feature indicative of a characteristic of the flower. The processor further includes a grade estimation module (170) configured to estimate a qualitative assessment for the flower based on the feature and a temporal aggregation module (540) configured to combine the estimated qualitative assessments to output a final aggregated assessment.

Abstract: A system for autonomous monitoring and/or optimization of plant (140) growth is provided. The system may include actuation devices configured to interact with an agricultural area (120), image sensors (130) configured to capture images (170) of a plant (140) in the agricultural area (120), and a processor (150) in communication with the image sensors (130) and the actuation devices. The processor (150) may be configured to store, via a memory (160), a first image (170) of the agricultural area (120) captured prior to a first actuation of the actuation devices; and trigger, synchronously with the first actuation, the image sensors (130) to capture a second image (180) of the agricultural area (120).

Abstract: Techniques are described herein for workspace occupancy estimation using presence sensor data and a predictive model. In various embodiments, spatial distributions of workspaces (340) and presence sensors (342) may be identified (402) in an open environment and used to generate (406) a surrogate model. The surrogate model may indicate which workspaces in the open environment are within sensor range of each presence sensor in the open environment. A plurality of simulated occupancy patterns may be applied across the surrogate model to generate a corresponding plurality of triggered sensor patterns. Based on the applying, a predictive model may be generated (410) for estimating occupancy among the plurality of workspaces in the open environment based on triggered sensor patterns. A real life triggered sensor pattern may then be applied (414) across the predictive model to estimate occupancy among the plurality of workspaces in the environment.

Abstract: A method and corresponding system is disclosed in which the overall illuminance of an environment is analyzed to in order to detect and quantify the daylight component of the illuminance. The invention utilizes a combination of visual and non-visual sensors and a signal processing algorithm that filters and analyzes the sensor data.

Abstract: Lighting systems and methods for lighting fixture location mapping, for example, using a combination of photosensing readings and/or other sensors to identify a correct mapping. These systems and methods may be used to resolve ambiguities that could not be resolved using other processes, such an auto-commissioning method that identifies more than one possible mapping of the lighting fixtures to spatial locations. Such ambiguities are typically found in floor plans that are symmetrical. The systems and methods of the present invention record and utilize environmental profiles, such as ambient lighting levels and occupancy patterns, to match lighting fixtures to their respective spatial locations and provide resolution to ambiguities in an auto-commissioning method that identifies more than one possible mapping of the lighting fixtures to spatial locations.

Abstract: A system for managing workspace configurations disclosed. The system comprises a plurality of sensors, at least one of the sensors being associated with a corresponding workspace, determining changes in a current configuration of the work space with regard to a previous configuration of the space, wherein the current configuration is determined based on signals received from selected ones of the sensors and providing an indication when the a change in the configuration has been determined.

Abstract: This invention discloses a method and apparatus for managing lighting systems is disclosed. The method comprises performing a training phase for a plurality of settings wherein the training is represented by statistical parameters associated with a statistical model and then performing a monitoring phase to monitor the lighting system, determining whether characteristics of the monitored lighting system correspond to the model obtained during the training phase and determining an error exists when the monitored lighting system is not within tolerance values of the statistical parameters.

Abstract: Lighting systems and methods for lighting fixture location mapping, for example, using a combination of photosensing readings and/or other sensors to identify a correct mapping. These systems and methods may be used to resolve ambiguities that could not be resolved using other processes, such an auto-commissioning method that identifies more than one possible mapping of the lighting fixtures to spatial locations. Such ambiguities are typically found in floor plans that are symmetrical. The systems and methods of the present invention record and utilize environmental profiles, such as ambient lighting levels and occupancy patterns, to match lighting fixtures to their respective spatial locations and provide resolution to ambiguities in an auto-commissioning method that identifies more than one possible mapping of the lighting fixtures to spatial locations.

Abstract: A system for managing workspace configurations disclosed. The system comprises a plurality of sensors, at least one of the sensors being associated with a corresponding workspace, determining changes in a current configuration of the work space with regard to a previous configuration of the space, wherein the current configuration is determined based on signals received from selected ones of the sensors and providing an indication when the a change in the configuration has been determined.

Abstract: This invention discloses a method and apparatus for managing lighting systems is disclosed. The method comprises performing a training phase for a plurality of settings wherein the training is represented by statistical al parameters associated with a statistical model and then performing a monitoring oring phase to monitor the lighting system, determining whether characteristics of the monitored lighting system correspond to the model obtained during the training phase and determining an error exists when the monitored lighting system is not within tolerance values of the statistical parameters.

Abstract: Methods, systems and computer program products for monitoring and analysis of network servers and web analytics programs are disclosed. A monitoring program, for example, is configured to monitor the status of web analytics program(s) associated with one or more network servers. The monitoring program may monitor server-specific metrics such as server free disk space, server available memory, server on-line/off-line status, report processing time, difference between system time and log file time, table size details, etc. The program may be configured to present status indicators to the user that are indicative of the health of the web analytics program and/or server. A user may receive an alert generated by the monitoring program regarding a change in web analytics program status. Additionally, the monitoring program may be configured to automatically take corrective action to remedy or prevent a critical event that may cause loss of data or delay web analytics reporting.

Abstract: The invention relates to a monitoring apparatus for monitoring a physiological signal. A segmentation unit (4) determines signal segments from a physiological signal, which correspond to periods of the physiological signal, a classification unit (5) classifies the signal segments into a valid class and a non-valid class based on characteristics related to the signal segments, and a physiological information determination unit (7) determines physiological information from at least one of i)signal segments classified into the valid class and ii) signal segments classified into the non-valid class. The physiological information can therefore be determined based on the knowledge whether the respective signal segment is valid or not. For example, a physiological parameter like a breathing rate can be determined depending on valid adapted segments of the physiological signal, which are adapted to periods of the physiological signal.

Abstract: Methods, systems and computer program products for monitoring and analysis of network servers and web analytics programs are disclosed. A monitoring program, for example, is configured to monitor the status of web analytics program(s) associated with one or more network servers. The monitoring program may monitor server-specific metrics such as server free disk space, server available memory, server on-line/off-line status, report processing time, difference between system time and log file time, table size details, etc. The program may be configured to present status indicators to the user that are indicative of the health of the web analytics program and/or server. A user may receive an alert generated by the monitoring program regarding a change in web analytics program status. Additionally, the monitoring program may be configured to automatically take corrective action to remedy or prevent a critical event that may cause loss of data or delay web analytics reporting.