In one embodiment, a method of tracking multiple objects with a probabilistic hypothesis density filter is provided. The method includes obtaining measurements corresponding to a first object with at least one sensor, the at least one sensor providing one or more first track IDs for the measurements. A T.sub.k+1 first predicted intensity is generated for the first object based on a T.sub.k first track intensity. A T.sub.k+1 measurement from a first sensor of the at least one sensors is obtained, the first sensor providing a second track ID for the T.sub.k+1 measurement. The second track ID is compared to the one or more first track IDs, and the T.sub.k+1 first predicted intensity is selectively updated with the T.sub.k+1 measurement based on whether the second track ID matches any of the one or more first track IDs to generate a T.sub.k+1 first measurement-to-track intensity for the first object.

In one embodiment, a method of tracking multiple objects with a probabilistic hypothesis density filter is provided. The method includes obtaining measurements corresponding to a first object with at least one sensor, the at least one sensor providing one or more first track IDs for the measurements. A T.sub.k+1 first predicted intensity is generated for the first object based on a T.sub.k first track intensity. A T.sub.k+1 measurement from a first sensor of the at least one sensors is obtained, the first sensor providing a second track ID for the T.sub.k+1 measurement. The second track ID is compared to the one or more first track IDs, and the T.sub.k+1 first predicted intensity is selectively updated with the T.sub.k+1 measurement based on whether the second track ID matches any of the one or more first track IDs to generate a T.sub.k+1 first measurement-to-track intensity for the first object.

First sensor data generated by a first of a plurality of sensors and at least second sensor data generated by at least a second of the plurality of sensors can be received by a sensor data broker executed by a processor. The sensor data broker can publish to at least a first virtual sensor the first sensor data as first published sensor data. The sensor data broker can publish to at least a second virtual sensor the second sensor data as second published sensor data.

A device for processing rotation-dependent measured values includes a data converter, a sequencing control, and an output interface. Series of measured values, which are a function of the rotation of a shaft and of which at least one is an angle value that indicates the angular position of the shaft, are conveyable to the data converter at constant time intervals of a measuring interval. The data converter is adapted to subdivide a rotation of the shaft into sectors and, using one of the angle values as a reference angle value, to allocate received measured values to a sector, and per rotation of the shaft, to ascertain for each series of measured values precisely one result value for each sector. The result values are able to be output to the output interface.

A device for processing rotation-dependent measured values includes a data converter, a sequencing control, and an output interface. Series of measured values, which are a function of the rotation of a shaft and of which at least one is an angle value that indicates the angular position of the shaft, are conveyable to the data converter at constant time intervals of a measuring interval. The data converter is adapted to subdivide a rotation of the shaft into sectors and, using one of the angle values as a reference angle value, to allocate received measured values to a sector, and per rotation of the shaft, to ascertain for each series of measured values precisely one result value for each sector. The result values are able to be output to the output interface.

A method and apparatus for automatically measuring and storing a various measured values of an item, or a sequence of measured values of one or more item(s) suitable for single-handed use by a user. In particular, the present invention relates to a mobile computing device with one or more sensors for determining when to measure and record a particular value of one or more items. The mobile computing device may automatically measure the values based on sensing a change in the temperature value or through using proximity as detected by one or more onboard sensors. Additionally, the mobile computing device may automatically measure the values based on coming within range of an external proximity device. In response to automatically measuring the values, the measured values are stored along with additional information for record keeping purposes.

A method and apparatus for automatically measuring and storing a various measured values of an item, or a sequence of measured values of one or more item(s) suitable for single-handed use by a user. In particular, the present invention relates to a mobile computing device with one or more sensors for determining when to measure and record a particular value of one or more items. The mobile computing device may automatically measure the values based on sensing a change in the temperature value or through using proximity as detected by one or more onboard sensors. Additionally, the mobile computing device may automatically measure the values based on coming within range of an external proximity device. In response to automatically measuring the values, the measured values are stored along with additional information for record keeping purposes.

A sensor system may be configured for continuous operation in a low resource environment and/or in extreme environmental conditions. The sensor system may have sufficient processing capabilities to provide scientific computing for pre-processing, quality control, statistical analysis, event classification, data compression and corrections (e.g., spikes in the data), autonomous decisions and actions, triggering other nodes, and information assurance functions that provide data confidentiality, data integrity, authentication, and non-repudiation. The hardware may have both mesh networking and satellite and cellular communication capability, and may be available for relatively low cost. Such a network provides the flexibility to have potentially any number of nodes be completely independent from one another. Thus, the network may scale across a diverse terrain.

A sensor system may be configured for continuous operation in a low resource environment and/or in extreme environmental conditions. The sensor system may have sufficient processing capabilities to provide scientific computing for pre-processing, quality control, statistical analysis, event classification, data compression and corrections (e.g., spikes in the data), autonomous decisions and actions, triggering other nodes, and information assurance functions that provide data confidentiality, data integrity, authentication, and non-repudiation. The hardware may have both mesh networking and satellite and cellular communication capability, and may be available for relatively low cost. Such a network provides the flexibility to have potentially any number of nodes be completely independent from one another. Thus, the network may scale across a diverse terrain.

A sensor hub includes a bit packer that receives sensor data from a plurality of sensors and bit packs the sensor data so that the sensor ID, time stamp and each axis of the measured data is stored contiguously. The bit packer may compress the sensor data by removing the sensor ID and/or the time stamp in the sensor data. The bit packed sensor data is stored in batching memory. A bit unpacker receives the sensor data from the batching memory and unpacks the sensor data, e.g., so that the sensor ID, time stamp and each axis of the measured data is stored in its own word. Additionally, the bit unpacker may decompress the bit packed sensor data by reinserting the sensor ID and/or time stamp in the sensor data.