Abstract: Methods, systems, computer-readable media, and apparatuses for inferring context are provided. In one potential implementation, first context information associated with a first duration is identified, second context information is accessed to determine a context segmentation boundary; and the first context information and the second context information is then aggregated to generate an inferred segmented aggregated context. In a further implementation, the first context information is used to average inferred contexts, and the context segmentation boundary is used to reset a start time for averaging the first context information.

Abstract: A model-based control system for controlling a production system is disclosed. The production system provides jobs and objectives to the model-based control system. The model-based control system includes, a planner operative to provide the production system with a plan, the planner generating the plan using a depth-first target value search. The depth-first target value search being configured to generate the plan with a failure probability most closely approximating a target value. Also provided is a system model operative to model the behavior of the production system. Another aspect of the model-based control system is a diagnosis engine operative to estimate failure probabilities for plans and provide diagnostic guidance to the planner. The model-based control system including the planner, the system model and diagnosis engine are implemented via a digital processing device.

Abstract: One or more mobile devices make measurements while moving along a path. Each measurement may comprise a specific group of identifiers of wireless transmitters, and strengths of corresponding wireless signals. A set of measurements are made in a sequence along a path, and the subsets of the measurements are identified for satisfying a test on a value of a measure of similarity of measurements included in the subset. A new place of relevance is identified, by comparing the just-described subsets of the measurements with similar subsets of additional measurements (e.g. by clustering). Alternatively, a known place of relevance (e.g. having a label) is identified, by comparing the just-described subsets of the measurements with pre-computed model of measurements. Also, the just-described subsets of the measurements may be compared with corresponding subsets of measurements of another path, e.g. to identify common portions therein.

Abstract: A method of analyzing audio signals, such as for a drive monitoring system, includes recording an audio signal from a mobile device, the audio signal including a background audio stream and a residual audio signal. Communication with an audio database is performed to obtain a reference signal. If a match between the background audio stream and the reference signal is determined, a time alignment between the background audio stream and the reference is computed. At least a portion of the recorded audio signal is aligned with the reference signal using the time alignment. The background audio stream is canceled from the recorded audio signal, to result in the residual audio stream. A computer processor is used to determine a driving behavior factor from the residual audio stream.

Abstract: A method of analyzing audio signals, such as for a drive monitoring system, includes recording an audio signal from a mobile device, the audio signal including a background audio stream and a residual audio signal. Communication with an audio database is performed to obtain a reference signal. If a match between the background audio stream and the reference signal is determined, a time alignment between the background audio stream and the reference is computed. At least a portion of the recorded audio signal is aligned with the reference signal using the time alignment. The background audio stream is canceled from the recorded audio signal, to result in the residual audio stream. A computer processor is used to determine a driving behavior factor from the residual audio stream.

Abstract: Methods, systems, computer-readable media, and apparatuses for inferring context are provided. In one potential implementation, first context information associated with a first duration is identified, second context information is accessed to determine a context segmentation boundary; and the first context information and the second context information is then aggregated to generate an inferred segmented aggregated context. In a further implementation, the first context information is used to average inferred contexts, and the context segmentation boundary is used to reset a start time for averaging the first context information.

Abstract: In an embodiment, an access terminal (AT) measures and reports location information when positioned at a user-defined place associated with a geofence to a server, and the server updates a place fingerprint configured to identify the user-defined place based on the reported location information. In another embodiment, the AT or the server obtains location information associated with a set of user-defined places that are identifiable by a set of place fingerprints, determines whether a location event has occurred and updates a behavior model for the access terminal based on the determination. In another embodiment, the AT receives a request for its location and evaluates a set of factors (e.g., the behavior model, etc.) to determine whether to acquire the AT's location with a high power-consumption positioning procedure (e.g., GPS).

Abstract: A computer based method and system for tiered inference multiple fault diagnosis is provided. The method includes using a computer processor to dissect a hypothesis space representing a production system having a plurality of production modules into tiers. Production modules in the current tier are partitioned into a group or a set of sub-groups. A fault diagnosis algorithm is applied to the group of each sub-group to identify an acceptable fault diagnosis. When no acceptable fault diagnosis is found, the process moves to the next tier to perform further investigations. The process continues to move to higher tiers until an acceptable fault diagnosis is obtained or the system instructs the process to end.

Abstract: Various arrangements for anticipating an electrical load are presented. A plurality of indications of locations of a vehicle may be received. A travel pattern of the vehicle based on the plurality of indications of locations of the vehicle may be determined. The travel pattern may indicate a destination and an expected travel time to arrive at the destination. A current location of the vehicle may be received. At least partially based on the current location of the vehicle, whether the vehicle is expected to conform to the travel pattern may be determined. An anticipated electrical load at the destination may be determined at least partially based on the travel pattern.

Abstract: One or more mobile devices make measurements while moving along a path. Each measurement may comprise a specific group of identifiers of wireless transmitters, and strengths of corresponding wireless signals. A set of measurements are made in a sequence along a path, and the subsets of the measurements are identified for satisfying a test on a value of a measure of similarity of measurements included in the subset. A new place of relevance is identified, by comparing the just-described subsets of the measurements with similar subsets of additional measurements (e.g. by clustering). Alternatively, a known place of relevance (e.g. having a label) is identified, by comparing the just-described subsets of the measurements with pre-computed model of measurements. Also, the just-described subsets of the measurements may be compared with corresponding subsets of measurements of another path, e.g. to identify common portions therein.

Abstract: Methods and systems for solving a target value search problem using a multi-interval heuristic are presented. The methods and system identity a path, or paths, in a graph, whereby a connection graph is created and range sets are generated for each vertex in the connection graph. Range sets include one or more intervals. Thereafter, a best search is performed to identify a path, or paths, from a starting vertex to a goal vertex having a path value closest to a target value.

Abstract: A method for determining a target path for a model-based control system. The model-based control system includes a directed acyclic graph, where the directed acyclic graph includes a plurality of vertices interconnected by a plurality of edges. The method includes the steps of performing a depth-first search of the directed acyclic graph for the target path. The depth-first search is operative to return an explicit solution or an implicit solution, wherein the implicit solution is determined using a heuristic. The method further includes determining if the depth-first search returned an explicit solution or an implicit solution, and if the depth-first search returned an implicit solution, constructing the target path from the implicit solution. The method may further include constructing a pattern database.

Abstract: Diagnostic systems and methods are presented for determining the current condition of a production plant and the resources thereof, in which successively more complex diagnostic abstractions are used to determine the plant condition, with a more complex abstraction being selected when the most recently selected diagnostic abstraction is logically inconsistent with the current fault status indications.

Abstract: Systems and methods for Dynamic Subsumption Inference are disclosed. For example, a method for Dynamic Subsumption Inference, may include: receiving a time signal associated with the current time; receiving a first input signal comprising data associated with a user at the current time; determining a first context based on the first input signal and the current time; comparing the first context to a database of contexts associated with the user; and determining a second context based in part on the comparison.

Abstract: A method for determining a target path for a model-based control system. The model-based control system includes a directed acyclic graph, where the directed acyclic graph includes a plurality of vertices interconnected by a plurality of edges. The method includes the steps of performing a depth-first search of the directed acyclic graph for the target path. The depth-first search is operative to return an explicit solution or an implicit solution, wherein the implicit solution is determined using a heuristic. The method further includes determining if the depth-first search returned an explicit solution or an implicit solution, and if the depth-first search returned an implicit solution, constructing the target path from the implicit solution. The method may further include constructing a pattern database.

Abstract: Target value search methods and systems are presented for solving a target value path problem to identify a path or paths in a graph in which a connection graph is created and upper and lower bound values are determined for each node in the connection graph, and a first best search is performed to identify a path or paths from a starting node to a goal node having a path value closest to the target value.

Abstract: A computer-based method and system for pervasive model adaptation are provided. The method includes providing a production plan to a production system, executing the production plan in the production system, collecting observation data produced by at least one sensor in the production system during execution of the production plan into computer memory, calculating changes to be made to a system model in the computer memory based on the collected observation data, dynamically updating the system model according to the calculated changes, creating an updated production plan based at least partially on the dynamically updated system model, and storing the updated production plan within the computer memory.

Abstract: Model-based production control systems and methods are presented for constructing plans for controlling operation of a production system with a plant having a plurality of resources to achieve one or more production goals, in which a planner constructs plans for execution in the plant based on production goals while balancing both production objectives (e.g., production cost, production time) and diagnostic objectives (e.g., diagnostic cost, information gained, repair cost), and a diagnosis engine determines a current plant condition based on a previously executed plan and corresponding observations from the plant, and provides expected information gain data to the planner, with the planner generating a plan that will achieve a given production goal and is improved for one or more diagnostic objectives and the expected information gain data.

Abstract: A computer-based method and system for pervasive model adaptation are provided. The method includes providing a production plan to a production system, executing the production plan in the production system, collecting observation data produced by at least one sensor in the production system during execution of the production plan into computer memory, calculating changes to be made to a system model in the computer memory based on the collected observation data, dynamically updating the system model according to the calculated changes, creating an updated production plan based at least partially on the dynamically updated system model, and storing the updated production plan within the computer memory.

Abstract: A method for determining a target path for a model-based control system. The model-based control system includes a directed acyclic graph, where the directed acyclic graph includes a plurality of vertices interconnected by a plurality of edges. The method includes the steps of performing a depth-first search of the directed acyclic graph for the target path. The depth-first search is operative to return an explicit solution or an implicit solution, wherein the implicit solution is determined using a heuristic. The method further includes determining if the depth-first search returned an explicit solution or an implicit solution, and if the depth-first search returned an implicit solution, constructing the target path from the implicit solution. The method may further include constructing a pattern database.