Abstract: A large-scale radio frequency signal information processing and analysis system that provides advanced signal analysis for telecommunication applications, including band capacity and geographical density determinations and detection, classification, identification, and geolocation of signals across a wide range of frequencies and across broad geographical areas. The system may utilize a range of novel algorithms for bin-wise processing, Rayleigh distribution analysis, telecommunication signal classification, receiver anomaly detection, transmitter density estimation, transmitter detection and location, geolocation analysis, telecommunication activity estimation, telecommunication utilization estimation, frequency utilization estimation, and data interpolation.

Abstract: A system and method for quantifying viewer engagement with a video playing on a display in a respondent household includes an agreed upon camera arrangement to monitor viewer engagement. The system and method includes the ability to determine what sources of content are being accessed by the household, and other data such as time of viewing, and source of content.

Abstract: A system accesses a plurality of ratio values for similar AOIs, each ratio value indicating a ratio between a count of device users at a similar AOI and a count of vehicles of the similar AOI. The similar AOIs are AOIs that have measurable characteristics within a range of similarity with those of the target AOI. The count of vehicles of the similar AOI is generated using aerial imagery received for the similar AOI. The count of device users at the similar AOI is extracted from third party data for the similar AOI. The system accesses a count of a number of reported device users at the target AOI, and generates an estimate of the vehicle count for the target AOI using the count of the number of reported device users at the target AOI and a combination of the plurality of ratio values for similar AOIs.

Abstract: A method for operating a power generating facility connected to a power distribution grid having an uncertain power generation condition includes predicting a probabilistic power flow forecast in a transmission line of the power distribution grid for a period of time, wherein the transmission line is electrically coupled to the power generating facility, predicting, using the probabilistic power flow forecast, a probability of congestion over the transmission line of the power distribution grid during the period of time, generating a mitigation plan, including a load adjustment on the transmission line, using the probability of congestion predicted over the transmission line and a thermal limit constraint of the transmission line, wherein the mitigation plan balances load adjustment and an overlimit line capacity on the transmission line, and controlling the power generating facility, using the mitigation plan, to achieve load modification and mitigate the probability of congestion predicted in the transmissi

Abstract: A system and method are disclosed for receiving a request to track data of an area of interest (AOI). The system receives a plurality of geolocation data records corresponding to a plurality of mobile devices. The system determines which mobile devices of the plurality of mobile devices have visited the AOI. For each mobile device determined to have visited the AOI, the system determines a path of the mobile device. The path including a prior location of the mobile device and a next location of the mobile device. The system transmits for display by a client device, a report including the path for each mobile device determined to have visited the AOI. The path indicating an identification of additional AOIs based on the prior location and the next location.

Abstract: A method comprises receiving an area of interest (AOI) selection. The method further comprises accessing an AOI device location data for the AOI, the AOI device location data indicating locations of devices over time received within the AOI. The AOI device location data is filtered to only include the device location data that match one or more characteristics. A proximity zone is determined for the for the AOI that includes the area of the AOI. A zone device location data for the proximity zone is determined, which indicates locations of devices over time reported within the proximity zone. The method further comprises normalizing the filtered AOI device location data by computing a ratio of the filtered AOI device location data and the zone device location data to generate an AOI user estimate, and transmitting the AOI user estimate to a client device of a requestor.

Abstract: A system for quantifying viewer engagement with a video playing on a display includes at least one camera to acquire image data of a viewing area in front of the display. A microphone acquires audio data emitted by a speaker coupled to the display. The system also includes a memory to store processor-executable instructions and a processor. Upon execution of the processor-executable instructions, the processor receives the image data and the audio data and determines an identity of the video displayed on the display based on the audio data. The processor also estimates a first number of people present in the viewing area and a second number of people engaged with the video. The processor further quantifies the viewer engagement of the video based on the first number of people and the second number of people.

Abstract: An example method comprises receiving historical wind turbine failure data and asset data from SCADA systems, receiving first historical sensor data, determining healthy assets of the renewable energy assets by comparing signals to known healthy operating signals, training at least one machine learning model to indicate assets that may potentially fail and to a second set of assets that are operating within a healthy threshold, receiving first current sensor data of a second time period, applying a machine learning model to the current sensor data to generate a first failure prediction a failure and generate a list of assets that are operating within a healthy threshold, comparing the first failure prediction to a trigger criteria, generating and transmitting a first alert if comparing the first failure prediction to the trigger criteria indicates a failure prediction, and updating a list of assets to perform surveillance if within a healthy threshold.

Abstract: An example method comprises receiving historical sensor data of a renewable energy asset for a first time period, identifying historical log data in one or more log sources, retrieving dates of the identified historical log data, retrieving sequences of historical sensor data using the dates, training hidden Markov models using the sequences of historical sensor data to identify probability of shifting states of one or more components of the renewable energy asset, receiving current sensor data of a second time period, identifying current log data in the one or more log sources, retrieving dates of the identified current log data, retrieving sequences of current sensor data using the dates, applying the hidden Markov models to the sequences of the current sensor data to assess likelihood of the one or more faults, creating a prediction of a future fault, and generating a report including the prediction of the future fault.

Abstract: Technical solutions are described for predicting linepack delays. An example method includes receiving temporal sensor measurements of a first fluid-delivery pipeline network and generating a causality graph of the first fluid-delivery pipeline network. The method also includes determining a topological network of the stations based on the causality graph, where the topological network identifies a temporal delay between a pair of stations. The method also includes generating a temporal delay prediction model based on the topological network and predicting the linepack delays of a second fluid-delivery pipeline network based on the temporal delay prediction model, where a compressor station of the second fluid-delivery pipeline network compresses fluid based on the predicted linepack delays to maintain a predetermined pressure.

Abstract: A method, system, and computer program product to manage a network comprising a plurality of interconnected components are described. The method includes obtaining a set of all the components that are part of the network over time, and identifying one or more repeating patterns of components among the set of all the components as corresponding lower-level definitions to generate a hierarchical set of all the components. The method also includes obtaining time-varying information regarding topology and operational values within the network, and creating a representation of the network at a set of times based on the hierarchical set of all the components and the time-varying information.

Abstract: A method may comprise storing a first service provider record associated with a first project located at a first geographic location, receiving a request for project identifiers located within a section of a geographic area, providing a subset of the first set of the one or more project identifiers to be displayed on a second map the first user device, receiving a selected project of the project identifiers, providing a project page indicating categorical identifiers associated with the first project indicating at least some work performed, a link to at least one service professional's profile page, an opinion review and an insight review, receiving a selection of the link to the at least one service professional's profile page, and providing, a profile page of the at least one service professional, the profile page including contact information of the at least one service professional.

Abstract: A method and apparatus for forecasting output power of wind turbine in a wind farm. The present invention provides a method for forecasting output power of a wind turbine in a wind farm, including: generating a corrected data set based on environmental data collected from at least one sensor in the wind farm; correcting a weather forecasting model by using the corrected data set; obtaining a forecast value of wind information at the wind turbine based on the corrected weather forecasting model; and forecasting the output power of the wind turbine based on the forecast value and a power forecasting model.

Abstract: A method, system, and computer program product for managing resources by obtaining a high spatial resolution estimate of behavior adoption are described. The method includes obtaining a low-resolution estimate with a fixed geographic scale, selecting a sample of customers based on the low-resolution estimate, implementing a statistical model to obtain relative probability of adoption of the behavior by each of the sample of customers, and generating a weighted random realization from the sample of customers, the weighted random realization being weighted based on the relative probability of adoption.

Abstract: Systems and methods for calibrating multiple electronic devices are described herein. Such methods may include obtaining, by a processor, data from a plurality of reference electronic devices, analyzing, by a processor, the data and calibrating, by the processor, the electronic device based on the analyzed data obtained from the plurality of reference electronic devices.

Abstract: A method and apparatus for forecasting output power of wind turbine in a wind farm. The present invention provides a method for forecasting output power of a wind turbine in a wind farm, including: generating a corrected data set based on environmental data collected from at least one sensor in the wind farm; correcting a weather forecasting model by using the corrected data set; obtaining a forecast value of wind information at the wind turbine based on the corrected weather forecasting model; and forecasting the output power of the wind turbine based on the forecast value and a power forecasting model.

Abstract: An example method comprises receiving event and alarm data from event logs, failure data, and asset data from SCADA system(s), retrieve patterns of events from the SCADA data, receiving historical sensor data from sensors of components of wind turbines, training a set of models to predict faults for each component using the patterns of events and historical sensor data, each model of a set having different observation time windows and lead time windows, evaluating each model of a set using standardized metrics, comparing evaluations of each model of a set to select a model with preferred lead time and accuracy, receive current sensor data from the sensors of the components, apply the selected model(s) to the current sensor data to generate a component failure prediction, compare the component failure prediction to a threshold, and generate an alert and report based on the comparison to the threshold.

Abstract: Provided is a process, including: obtaining movement transactions without having server-side access to information by which the members of the population undergoing the changes in geolocation indicated by the movement transactions can be identified, either personally or pseudonymously; obtaining for movement transactions corresponding to a designated window of time, geographic-pathogen-risk scores of starting geolocations that include the starting geographic positions; updating for the movement transactions corresponding to the designated window of time, geographic-pathogen-risk scores of the ending geolocations based on both geographic-pathogen-risk scores of the starting geolocations involved in movement transactions ending at the ending geolocations and rates of traffic at the ending geolocations indicated by movement transactions ending or starting at the ending geolocations.

Abstract: An apparatus for estimating a condition of a battery includes a mode identifying unit configured to identify a usage mode of the battery during a period of time and its corresponding attenuation curve, according to recorded data on battery usage, stored usage modes of the battery and attenuation curves corresponding to the various usage modes, the attenuation curve representing a change of a fully charged capacity of the battery with battery usage; and a condition estimating unit configured to calculate battery degradation according to the recorded data, the identified usage mode and its corresponding attenuation curve, the degradation representing a quantity of the fully charged capacity of the battery that is reduced over the battery usage. The condition of the battery is estimated so as to rationally judge the residual value of the battery in operation.