Abstract: Systems and methods dynamically adapt network policies for mobile devices by accessing context-based values to allocate or restrict capabilities on the mobile devices or within the network. Context-based values may include position or velocity as well as more general environment features such as proximity of other devices, the presence or absence of other wireless signals or network traffic, parameters measured by local or remote sensors, user credentials, or unique user or signal inputs to the device. Relevant capabilities may include access to hardware and software interfaces and related parameter sets including priority settings.

Abstract: Systems and methods dynamically adapt network policies for mobile devices by accessing context-based values to allocate or restrict capabilities on the mobile devices or within the network. Context-based values may include position or velocity as well as more general environment features such as proximity of other devices, the presence or absence of other wireless signals or network traffic, parameters measured by local or remote sensors, user credentials, or unique user or signal inputs to the device. Relevant capabilities may include access to hardware and software interfaces and related parameter sets including priority settings.

Abstract: Systems and methods dynamically adapt network policies for mobile devices by accessing context-based values to allocate or restrict capabilities on the mobile devices or within the network. Context-based values may include position or velocity as well as more general environment features such as proximity of other devices, the presence or absence of other wireless signals or network traffic, parameters measured by local or remote sensors, user credentials, or unique user or signal inputs to the device. Relevant capabilities may include access to hardware and software interfaces and related parameter sets including priority settings.

Abstract: A system and method for providing sensory analytics responses. The method comprises collecting raw data from a plurality of data sources; extracting, from the collected raw data, a subset of the raw data to be analyzed; generating, based on the extracted subset of the raw data, an analytics dataset, wherein the analytics dataset includes a performance indicator; determining, based on at least one received input, at least one query; determining, based on the generated analytics dataset, a response to the at least one query, wherein the response includes at least one sensory output; and causing projection of the determined at least one sensory output.

Abstract: A system and method for generating approximations of query results. The method includes sending a received query to a neural network, wherein the received query is executable on a target data set; receiving from the neural network a predicted result to the received query; providing the predicted result as a first output to a device having initiated the received query; determining a real result of the query from a data set stored in the database when the predicted result is insufficiently accurate; and providing the real result as a second output to a device having initiated the received query.

Abstract: A system and method for increasing the accuracy of generated approximations of query results. The method includes sending a received query to a first neural network and a second neural network; receiving from the first neural network a first predicted result to the received query; providing the first predicted result as a first output to a device having initiated the received query; receiving from the second neural network a second predicted result to the received query; and providing the second predicted result as a second output to the device having initiated the received query, wherein the first neural network requires less computational resources than the second neural network, and whereby the first output is provided before the second output.

Abstract: A system and method for efficiently responding to a query. The method comprises generating a lowest level data layer, wherein the lowest level data layer is a common dataset that can be served by a plurality of higher level data layers; generating, based on the lowest level data layer, at least one dataset, wherein each generated dataset is one of the plurality of higher level data layers, wherein each higher level data layer is accessed more rapidly than all lower level data layers; searching, in at least one of the generated data layers, for data needed to generate a response to the query; determining, based on the search, at least one data layer from which the response can be generated, wherein the determined at least one data layer includes the highest level data layer from which the response can be generated; and generating, based on data of the determined at least one data layer, a response to the query.

Abstract: An application executed on a first device presents a user interface on a device display. The application is associated with a validation system used by the device. Based on receiving a first user input, the application controls the first device to scan, using a first communication protocol, for other devices that are located within a first communication range of the first device. Based on the scan, the application discovers a second device located within the first communication range of the first device. The application receives, from the second device, an identification information that uniquely identifies a user associated with the second device on the validation system. The application validates the identification information by communicating with a validation server. Based on validating the identification information, the application displays an indication that the second device associated with the user is located within the first communication range of the first device.

Abstract: Systems and methods dynamically adapt network policies for mobile devices by accessing context-based values to allocate or restrict capabilities on the mobile devices or within the network. Context-based values may include position or velocity as well as more general environment features such as proximity of other devices, the presence or absence of other wireless signals or network traffic, parameters measured by local or remote sensors, user credentials, or unique user or signal inputs to the device. Relevant capabilities may include access to hardware and software interfaces and related parameter sets including priority settings.

Abstract: A system and method for increasing the accuracy of generated approximations of query results. The method includes sending a received query to a first neural network and a second neural network; receiving from the first neural network a first predicted result to the received query; providing the first predicted result as a first output to a device having initiated the received query; receiving from the second neural network a second predicted result to the received query; and providing the second predicted result as a second output to the device having initiated the received query, wherein the first neural network requires less computational resources than the second neural network, and whereby the first output is provided before the second output.

Abstract: A system and method for generating training sets for training neural networks. The method includes receiving a plurality of query pairs, wherein each of the plurality of query pairs includes a query and a real result previously determined for the query; determining at least one variable element of each query in the plurality of received query pairs; determining a variance for the at least determined variable element of each query in the plurality of received query pairs; and generating a training set based on the determined variable element, the determined variance, and the previously determined real result.

Abstract: A system and method for providing local approximations of query results are provided. The method includes querying a primary neural network with at least one test query, wherein the at least one test query includes a real test result derived from executing the at least one training query on a data set; receiving from the primary neural network a predicted test result in response to the at least one test query; sending, based on the predicted test result, a model of a primary neural network to a local machine; and storing the model of a local neural network of the local machine, wherein the local neural network is configured to generate a prediction in response to a user query received by the local machine.

Abstract: A system and method for generating approximations of query results. The method includes sending a received query to a neural network, wherein the received query is executable on a target data set; receiving from the neural network a predicted result to the received query; providing the predicted result as a first output to a device having initiated the received query; determining a real result of the query from a data set stored in the database when the predicted result is insufficiently accurate; and providing the real result as a second output to a device having initiated the received query.

Abstract: Systems and methods dynamically adapt network policies for mobile devices by accessing context-based values to allocate or restrict capabilities on the mobile devices or within the network. Context-based values may include position or velocity as well as more general environment features such as proximity of other devices, the presence or absence of other wireless signals or network traffic, parameters measured by local or remote sensors, user credentials, or unique user or signal inputs to the device. Relevant capabilities may include access to hardware and software interfaces and related parameter sets including priority settings.

Abstract: A system and method for efficiently responding to a query. The method comprises generating a lowest level data layer, wherein the lowest level data layer is a common dataset that can be served by a plurality of higher level data layers; generating, based on the lowest level data layer, at least one dataset, wherein each generated dataset is one of the plurality of higher level data layers, wherein each higher level data layer is accessed more rapidly than all lower level data layers; searching, in at least one of the generated data layers, for data needed to generate a response to the query; determining, based on the search, at least one data layer from which the response can be generated, wherein the determined at least one data layer includes the highest level data layer from which the response can be generated; and generating, based on data of the determined at least one data layer, a response to the query.

Abstract: A system and method for providing sensory analytics responses. The method comprises collecting raw data from a plurality of data sources; extracting, from the collected raw data, a subset of the raw data to be analyzed; generating, based on the extracted subset of the raw data, an analytics dataset, wherein the analytics dataset includes a performance indicator; determining, based on at least one received input, at least one query; determining, based on the generated analytics dataset, a response to the at least one query, wherein the response includes at least one sensory output; and causing projection of the determined at least one sensory output.

Abstract: Signals from an unidentified device at a location related to a communications network are correlated with identification patterns of managed devices to identify whether or not the unidentified device corresponds to a managed or unmanaged device in the communications network. Both managed and unmanaged devices can be tracked, and network interaction can be managed for devices that are identified as managed devices.

Abstract: Signals from an unidentified device at a location related to a communications network are correlated with identification patterns of managed devices to identify whether or not the unidentified device corresponds to a managed or unmanaged device in the communications network. Both managed and unmanaged devices can be tracked, and network interaction can be managed for devices that are identified as managed devices.

Abstract: Systems and methods dynamically adapt network policies for mobile devices by accessing context-based values to allocate or restrict capabilities on the mobile devices or within the network. Context-based values may include position or velocity as well as more general environment features such as proximity of other devices, the presence or absence of other wireless signals or network traffic, parameters measured by local or remote sensors, user credentials, or unique user or signal inputs to the device. Relevant capabilities may include access to hardware and software interfaces and related parameter sets including priority settings.

Abstract: The invention relates to automatic logging of people's lives by combining a geo-location tracking system, a data storage service and sharing services. In particular, a method and a system for location reporting using geo-location tracking devices, such as mobile communication devices, social networks and data storage and manipulation services. The data points collected from geo-location tracking receivers are then associated with information collected from various external information sources provided by the user and presented as points, milestones, or periods along the user's path, past, present and future.