Siemens Industry, Inc.

Siemens Aktiengesellschaft

Siemens Corporation

Nazif Cihan Tas

Justinian Rosca

Michael T Loiacono

Amar H Patel

Juan Aparicio

Heiko Claussen

Claus Neubauer

Mathaeus Dejori

Christian P Schultz

Tamer M Nadeem

Ciprian Dan Raileanu

Steven A Russell

Carolyn Joiner

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.

Smart grid communication assessment and co-simulation tool

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.

Learning patient monitoring and intervention system

Network element consolidation for rapid discrete network simulations

Network traffic profile aggregation for efficient discrete event smart grid network simulations

In a framework for acquiring and analyzing data from a network of sensors, plug-in software interfaces are used to provide scalability and flexibility. Data collection set-up data is exchanged through one or more first plug-in software interfaces with data collection devices, to configure the processor to collect measurement data from the data collection devices. Analysis set-up data is exchanged through one or more second plug-in software interfaces with one or more data analysis software packages, to configure the processor to provide a predefined subset of the measurement data to the data analysis software packages and to accept analysis results from the data analysis software packages. Measurement data and analysis results are subsequently exchanged through the plug-in interfaces.

Scalable and extensible framework for storing and analyzing sensor data

Methods, systems, and devices for monitoring roadway traffic. A method includes transmitting wireless signals from a plurality of roadside equipment (RSE) devices, including from a first RSE device and from a second RSE device that are located at separated positions of an intersection. The method includes receiving responses by the first RSE device and second RSE device from a wireless device. The responses include a unique identifier corresponding to the wireless device. The method includes determining a signal strength of each of the responses by the first RSE and the second RSE and transmitting data from the first RSE device and the second RSE device to a control system. The data includes the unique identifier, the signal strength of each of the responses, and times that the responses were received. The method includes determining traffic information associated with the wireless device based on the received data.

Data collection and traffic control using multiple wireless receivers

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Lawrenceville, NJ, United States of America

Nazif Cihan Tas