Abstract: A patient monitoring and intervention system, comprises an interface for receiving data representing multiple different parameters from multiple different sensors, comprising sensors in a patient bed and attached to a patient including, a heart rate sensor, a respiration sensor and a pressure sensor indicating bed pressure points. A learning processor determines a normal range for a set of the different received patient parameters for the patient by recording the patient parameter values over a time period and analyzing the recorded parameter values to determine their range. A data processor determines if the set of different received patient parameters exceeds the determined normal range and in response to this determination and in response to the type of parameters in the set and medical record information of the patient, initiates adjustment of a patient bed and at least one of, (a) changes medication administered to a patient and (b) alerts a worker of the patient parameter change.

Abstract: Systems and methods are provided for modeling and simulating a communication network operating under at least one communication protocol, which supports a Smart Grid electricity network. Communication performance data of the communication network are generated by a processor based on operating behavior of the Smart Grid with a plurality of assets under a first condition. Devices in the Smart grid are grouped in bins for rapid modeling. One or more different configurations of the communication network are entered into the processor and related performance data is also generated. Network configurations are compared based on the generated performance data which may include end-to-end delay and reception rate. Processor based systems to perform modeling methods are also provided.

Abstract: Systems and methods are provided for modeling and simulating a communication network operating under at least one communication protocol, which supports a Smart Grid electricity network. Communication performance data of the communication network are generated by a processor based on operating behavior of the Smart Grid with a plurality of assets under a first condition. Devices in the Smart grid are grouped in bins for rapid modeling. One or more different configurations of the communication network are entered into the processor and related performance data is also generated. Network configurations are compared based on the generated performance data which may include end-to-end delay and reception rate. Processor based systems to perform modeling methods are also provided.

Abstract: A patient monitoring and intervention system, comprises an interface for receiving data representing multiple different parameters from multiple different sensors, comprising sensors in a patient bed and attached to a patient including, a heart rate sensor, a respiration sensor and a pressure sensor indicating bed pressure points. A learning processor determines a normal range for a set of the different received patient parameters for the patient by recording the patient parameter values over a time period and analyzing the recorded parameter values to determine their range. A data processor determines if the set of different received patient parameters exceeds the determined normal range and in response to this determination and in response to the type of parameters in the set and medical record information of the patient, initiates adjustment of a patient bed and at least one of, (a) changes medication administered to a patient and (b) alerts a worker of the patient parameter change.

Abstract: Systems and methods are provided for modeling and simulating a communication network operating under at least one communication protocol, which supports a Smart Grid electricity network. Communication performance data of the communication network are generated by a processor based on operating behavior of the Smart Grid with a plurality of assets under a first condition. Devices in the Smart grid are grouped in bins for rapid modeling. One or more different configurations of the communication network are entered into the processor and related performance data is also generated. Network configurations are compared based on the generated performance data which may include end-to-end delay and reception rate. Processor based systems to perform modeling methods are also provided.

Abstract: Systems and methods are provided for modeling and simulating a communication network operating under at least one communication protocol, which supports a Smart Grid electricity network. Communication performance data of the communication network are generated by a processor based on operating behavior of the Smart Grid with a plurality of assets under a first condition. Devices in the Smart grid are grouped in bins for rapid modeling. One or more different configurations of the communication network are entered into the processor and related performance data is also generated. Network configurations are compared based on the generated performance data which may include end-to-end delay and reception rate. Processor based systems to perform modeling methods are also provided.

Abstract: Systems and methods are provided for modeling and simulating a communication network operating under at least one communication protocol, which supports a Smart Grid electricity network. Communication performance data of the communication network are generated by a processor based on operating behavior of the Smart Grid with a plurality of assets under a first condition. Devices in the Smart grid are grouped in bins for rapid modeling. One or more different configurations of the communication network are entered into the processor and related performance data is also generated. Network configurations are compared based on the generated performance data which may include end-to-end delay and reception rate. Processor based systems to perform modeling methods are also provided.