Abstract: A method is disclosed for tracking the location of an object. The method includes assigning a unique identifier for a first communication device, associating the first communication device with an object, associating the first communication device with a destination device, and storing the unique identifier in a location server.

Abstract: A computer-implemented system and method of predictive decision-making in an ad hoc network. The computer-implemented method includes receiving a set of rules into the ad hoc network and identifying a data set for each rule. The computer-implemented method also includes selecting a first and second node from the ad hoc network to process a first and second rule as a function of the identified data set according to an optimizing algorithm. The computer-implemented method also selects a third node to receive the processed results from the first and second nodes. An indication is provided of the processed results by the third node.

Abstract: Methods and systems for tracking the location of an object. The method includes assigning a unique first device identifier, associating the first device with an object, and storing the unique identifier in a location server. The method also includes receiving, at the location server, data indicating a projected travel path for the object and data comprising spatial, temporal, and contextual data elements. The method also includes determining, based on two or more of the received spatial, temporal, and contextual data elements, the availability of second devices in the vicinity of the projected travel path for the object. The method also includes transmitting, as a function of the determined availability of the second devices in the vicinity of the projected travel path for the object, a command to modify a transmission property of the first device.

Abstract: A computer-implemented system and method of predictive decision-making in an ad hoc network. The computer-implemented method includes receiving a set of rules into the ad hoc network and identifying a data set for each rule. The computer-implemented method also includes selecting a first and second node from the ad hoc network to process a first and second rule as a function of the identified data set according to an optimizing algorithm. The computer-implemented method also selects a third node to receive the processed results from the first and second nodes. An indication is provided of the processed results by the third node.

Abstract: A computer-implemented system and method of predictive decision-making in an ad hoc network. The computer-implemented method includes receiving a set of rules into the ad hoc network and identifying a data set for each rule. The computer-implemented method also includes selecting a first and second node from the ad hoc network to process a first and second rule as a function of the identified data set according to an optimizing algorithm. The computer-implemented method also selects a third node to receive the processed results from the first and second nodes. An indication is provided of the processed results by the third node.

Abstract: A computer-implemented system and method of analyzing spatial, temporal and contextual elements of data for predictive decision-making. The computer-implemented method includes receiving a first set of rules and receiving first data and second data including spatial, temporal and contextual elements. The computer-implemented method also includes identifying each rule of the first set for which the received first data and the received second data is a respective candidate. For the identified rules for which the received first data is a candidate, and for the identified rules for which the received second data is a candidate, the respective received first data and received second data is indexed by its temporal, spatial or contextual elements as a function of the identified rules. The computer-implemented method also includes identifying an event as satisfying an identified rule in memory using the indexed first and second data.

Abstract: Methods and systems and method of tracking the location of an object. The method includes assigning a unique first device identifier, associating the first device with an object, and storing the unique identifier and an identifier for the object associated with the first device in a location server. The method also includes transmitting a first message containing the unique identifier, but not the first device location, receiving the first message at a second device, and transmitting a second message from the second device containing the unique identifier and a second device location. The method also includes, at the location server, receiving the second message, associating the location of the second device with the first device, storing the location of the second device, receiving a request for the location of the object, and in response to the request, providing the unique identifier and the second device location.

Abstract: A computer-implemented system and method of predictive decision-making in an ad hoc network. The computer-implemented method includes receiving a set of rules into the ad hoc network and identifying a data set for each rule. The computer-implemented method also includes selecting a first and second node from the ad hoc network to process a first and second rule as a function of the identified data set according to an optimizing algorithm. The computer-implemented method also selects a third node to receive the processed results from the first and second nodes. An indication is provided of the processed results by the third node.

Abstract: A computer-implemented system and method of predictive decision-making in an ad hoc network. The computer-implemented method includes receiving a set of rules into the ad hoc network and identifying a data set for each rule. The computer-implemented method also includes selecting a first and second node from the ad hoc network to process a first and second rule as a function of the identified data set according to an optimizing algorithm. The computer-implemented method also selects a third node to receive the processed results from the first and second nodes. An indication is provided of the processed results by the third node.

Abstract: A computer-implemented system and method of analyzing spatial, temporal and contextual elements of data for predictive decision-making. The computer-implemented method includes receiving a first set of rules and receiving first data and second data including spatial, temporal and contextual elements. The computer-implemented method also includes identifying each rule of the first set for which the received first data and the received second data is a respective candidate. For the identified rules for which the received first data is a candidate, and for the identified rules for which the received second data is a candidate, the respective received first data and received second data is indexed by its temporal, spatial or contextual elements as a function of the identified rules. The computer-implemented method also includes identifying an event as satisfying an identified rule in memory using the indexed first and second data.

Abstract: A computer-implemented system and method of analyzing spatial, temporal and contextual elements of data for predictive decision-making. The computer-implemented method includes receiving a first set of rules and receiving first data and second data including spatial, temporal and contextual elements. The computer-implemented method also includes identifying each rule of the first set for which the received first data and the received second data is a respective candidate. For the identified rules for which the received first data is a candidate, and for the identified rules for which the received second data is a candidate, the respective received first data and received second data is indexed by its temporal, spatial or contextual elements as a function of the identified rules. The computer-implemented method also includes identifying an event as satisfying an identified rule in memory using the indexed first and second data.