A sensor tag which in use will be affixed to a vehicle for obtaining vehicle telematics data includes a battery for powering the tag and a processor running executable code to process accelerometer data. An accelerometer measures the acceleration of the tag and thereby of the vehicle, and also controls the operation of the processor. A memory is used for storing a unique tag identifier of the tag and for storing trip data including information about trips and acceleration data. Finally, a communication module is used for short range wireless communication with a mobile communications device located in the vehicle via a short range wireless communications protocol, the communication module transmitting the tag's unique identifier and a sequence of time stamped acceleration data. The mobile communications device obtains GPS data, combines this with the acceleration date and transmits this to a server for analysis.

An information processing system, an information processing method, and a computer program capable of easily and reliably identifying a behavioral history of an infected person and extracting close contacts are provided.

According to an embodiment of the present disclosure, there is provided an information processing system including a first information processing device having a function of transmitting a signal, a second information processing device having a function of receiving the signal, and a server device capable of being connected to the second information processing device via the Internet, wherein the server device stores time information, intensity information, first identification information, and second identification information received from the second information processing device in association with each other and extracts one or more pieces of other first identification information stored in association with specific second identification information on the basis of the specific second identification information stored in association with specific first identification information when the designation of the specific first identification information of a specific first information processing device has been received.

Computer-implemented systems utilizing sensor networks for sensing temperature and motion environmental parameters, and performing at least operations of electronically establishing, based on pattern recognition criteria, correspondence of a plurality of representative features a plurality of characteristics of an occurrence, where a first instance of the occurrence occurred within a first time period of a plurality of time periods; electronically discovering, based on the correspondence, a second instance of the occurrence in an environment during a second time period of the plurality of time periods; and electronically causing, based on the discovery of the second instance of the occurrence, a change in the environment via an electronically-controlled device.

An application and network analytics platform can capture telemetry from servers and network devices operating within a network. The application and network analytics platform can determine an application dependency map (ADM) for an application executing in the network. Using the ADM, the application and network analytics platform can resolve flows into flowlets of various granularities, and determine baseline metrics for the flowlets. The baseline metrics can include transmission times, processing times, and/or data sizes for the flowlets. The application and network analytics platform can compare new flowlets against the baselines to assess availability, load, latency, and other performance metrics for the application. In some implementations, the application and network analytics platform can automate remediation of unavailability, load, latency, and other application performance issues.

Sensors within sensor node networks may communicate bio-event or other types of measurement results/decisions between each other using signal transmission variations. Each sensor node within a network and between networks may transmit and receive signals. A sensor node may scale a signal transmission power in a manner that is proportional to a confidence level of a decision or measurement about an event being detected. Each sensor node will receive transmissions from neighboring nodes, and can refine an estimate about an occurrence of the event at its location based on received signal strengths, for example.

An operation information providing apparatus that provides information regarding a repetitive operation which is synchronously performed by a first user and a second user, includes a processor that detects a deviation of a timing of an operation of the second user based on a timing of an operation of the first user by using an output of a first sensor detecting the operation of the first user and an output of a second sensor detecting the operation of the second user, and an output unit that outputs information indicating the positive or negative of the deviation of a case where the deviation is detected.

An application and network analytics platform can capture telemetry from servers and network devices operating within a network. The application and network analytics platform can determine an application dependency map (ADM) for an application executing in the network. Using the ADM, the application and network analytics platform can resolve flows into flowlets of various granularities, and determine baseline metrics for the flowlets. The baseline metrics can include transmission times, processing times, and/or data sizes for the flowlets. The application and network analytics platform can compare new flowlets against the baselines to assess availability, load, latency, and other performance metrics for the application. In some implementations, the application and network analytics platform can automate remediation of unavailability, load, latency, and other application performance issues.

A sensor tag which in use will be affixed to a vehicle for obtaining vehicle telematics data includes a battery for powering the tag and a processor running executable code to process accelerometer data. An accelerometer measures the acceleration of the tag and thereby of the vehicle, and also controls the operation of the processor. A memory is used for storing a unique tag identifier of the tag and for storing trip data including information about trips and acceleration data. Finally, a communication module is used for short range wireless communication with a mobile communications device located in the vehicle via a short range wireless communications protocol, the communication module transmitting the tag's unique identifier and a sequence of time stamped acceleration data. The mobile communications device obtains GPS data, combines this with the acceleration date and transmits this to a server for analysis.

An application and network analytics platform can capture telemetry from servers and network devices operating within a network. The application and network analytics platform can determine an application dependency map (ADM) for an application executing in the network. Using the ADM, the application and network analytics platform can resolve flows into flowlets of various granularities, and determine baseline metrics for the flowlets. The baseline metrics can include transmission times, processing times, and/or data sizes for the flowlets. The application and network analytics platform can compare new flowlets against the baselines to assess availability, load, latency, and other performance metrics for the application. In some implementations, the application and network analytics platform can automate remediation of unavailability, load, latency, and other application performance issues.

An application and network analytics platform can capture telemetry from servers and network devices operating within a network. The application and network analytics platform can determine an application dependency map (ADM) for an application executing in the network. Using the ADM, the application and network analytics platform can resolve flows into flowlets of various granularities, and determine baseline metrics for the flowlets. The baseline metrics can include transmission times, processing times, and/or data sizes for the flowlets. The application and network analytics platform can compare new flowlets against the baselines to assess availability, load, latency, and other performance metrics for the application. In some implementations, the application and network analytics platform can automate remediation of unavailability, load, latency, and other application performance issues.