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.

Abstract: Mobile monitoring systems and methods are disclosed. In accordance with one aspect of the invention, the system includes a plurality of vehicles and a base communication station that are in communication with each other. Each of the vehicles includes a camera that generates image data, a location device that generates geographic coordinates of the vehicle, a computing device that receives the image data from the camera and the geographic coordinates of the vehicle and forms a processed image signal that includes the image data, the geographic coordinates and a time stamp, and a communication device that receives the processed image signal from the computing device and wireless transmits the processed image signal to the base communication station. The base communication station receives the processed image signal.

Abstract: Own voice recognition (OVR) for hearing aids, detects time instances where the person wearing the device is speaking. Classification of the own voice is performed dependent on a fixed or adaptive detection threshold. Automatic tuning in a real-time system depends on general noise statistics in the input signals. The noise is removed from the received signal and is characterized by signal-to-noise ratio and noise color. An optimal detection threshold for own voice recognition is determined based on the noise characteristics. A noise detection model is created by smoothed Voronoi tessellation. Own voice detection is performed by a processor.

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.

Abstract: Own voice recognition (OVR) for hearing aids, detects time instances where the person wearing the device is speaking. Classification of the own voice is performed dependent on a fixed or adaptive detection threshold. Automatic tuning in a real-time system depends on general noise statistics in the input signals. The noise is removed from the received signal and is characterized by signal-to-noise ratio and noise color. An optimal detection threshold for own voice recognition is determined based on the noise characteristics. A noise detection model is created by smoothed Voronoi tessellation. Own voice detection is performed by a processor.

Abstract: A method for controlling packet flow in a packet transmission network. The method includes determining a parameter representative of packet congestion on the network, and adjusting a flow of packets onto the network in accordance with such parameter. The adjusting is a function of the time history of the parameter and the time average of such parameter relative to predetermined threshold levels. The adjusting selects one of a plurality of states, transitions between the states being a function of the time history of the parameter and the time average of such parameter relative to predetermined threshold levels.

Abstract: Mobile monitoring systems and methods are disclosed. In accordance with one aspect of the invention, the system includes a plurality of vehicles and a base communication station that are in communication with each other. Each of the vehicles includes a camera that generates image data, a location device that generates geographic coordinates of the vehicle, a computing device that receives the image data from the camera and the geographic coordinates of the vehicle and forms a processed image signal that includes the image data, the geographic coordinates and a time stamp, and a communication device that receives the processed image signal from the computing device and wireless transmits the processed image signal to the base communication station. The base communication station receives the processed image signal.

Abstract: A method for controlling congestion for real-time video transmission in a wireless network includes receiving a packet loss rate of a video camera in a wireless network, receiving an estimated maximum throughput of the video camera from the camera to a server, decrementing a bit transmission rate when the packet loss rate is greater than a first predetermined threshold, incrementing the bit transmission rate when the packet loss rate is less than a second predetermined threshold for a predetermined time period, and transmitting the bit transmission rate to a video encoder that is part of an application layer of a network communication protocol for the wireless network.

Abstract: A method for controlling packet flow in a packet transmission network. The method includes determining a parameter representative of packet congestion on the network, and adjusting a flow of packets onto the network in accordance with such parameter. The adjusting is a function of the time history of the parameter and the time average of such parameter relative to predetermined threshold levels. The adjusting selects one of a plurality of states, transitions between the states being a function of the time history of the parameter and the time average of such parameter relative to predetermined threshold levels.

Abstract: A method for controlling congestion for real-time video transmission in a wireless network includes receiving a packet loss rate of a video camera in a wireless network, receiving an estimated maximum throughput of the video camera from the camera to a server, decrementing a bit transmission rate when the packet loss rate is greater than a first predetermined threshold, incrementing the bit transmission rate when the packet loss rate is less than a second predetermined threshold for a predetermined time period, and transmitting the bit transmission rate to a video encoder that is part of an application layer of a network communication protocol for the wireless network.