Arizona State University

Wistron Aiedge Corporation

Wistron Aidge Corporation

Smartiply, Inc.

Junshan Zhang

Vijay Vittal

Xu Chen

Zhengyu Zhang

Miao He

Lei Yang

Mung Chiang

Shunge Li

William J Heilig

Christopher Coble

Trevor N Werho

Raghuram Kaushik Pillalamarri

Arsalan A Gilani

A plurality of mobile devices is provided including a first mobile device of the plurality of mobile devices that serves as a relay for communication between a second mobile device of the plurality of mobile devices and a third mobile device of the plurality of mobile devices. The first mobile device is identified as the relay based on a social trust relationship formed between the first mobile device and the second mobile device. A D2D network is formed between the first mobile device and second mobile device. A communication channel is provided to the second mobile device from a second cellular network. A portion of the communication channel is allocated to the second mobile device using the D2D network to improve cellular transmission between the second mobile device and the third mobile device.

Systems and methods for social-aware cooperative device-to-device communications

A fog data agent for a connected car includes a connector configured to couple to an on-board diagnostic port of the connected car, a microprocessor, a wireless communication interface coupled to the microprocessor, a cellular communication interface coupled to the microprocessor, a data storage device coupled to the microprocessor, and logic configured to receive data from the on-board diagnostic port, analyzes the data in real-time, and establish a bi-directional communication channel with a remote server via at least one of the wireless communication interface and the cellular communication interface to transmit a subset of the analyzed data to the remote server in response to the data analysis.

Fog data agent for connected cars

Systems and methods for forecasting power generation in a wind farm are disclosed. The systems and methods utilize an induced Markov chain model to generate a forecast of power generation of the wind farm. The forecast is at least one of a point forecast or a distributional forecast. Additionally, the systems and methods modify at least one of: (i) a generation of electricity at a power plant coupled to a common power grid as the wind farm; or (ii) a distribution of electricity in the common power grid based on the forecast of power generation of the wind farm. In an exemplary approach, utilizing the induced Markov chain model to generate the forecast may include determining a series of time adjacent power output measurements based on historical wind power measurements and calculating a time series of difference values based on the series of time adjacent power output measurements.

Induced Markov chain for wind farm generation forecasting

A companion device is provided for a primary device. The companion device have wireless connectivity that send and receive data via a communication channel established over its wireless connectivity. The companion device includes a microcontroller, a wireless communication interface, a cellular communication interface, and logic configured to connect with the primary device via the wireless communication interface and with a cellular network via the cellular communication interface to augment bandwidth of the communication channel for the primary device.

Internet of Things (IOT) companion device

A fog network gateway includes at least one wireless communication interface, at least one cellular communication interface, and at least one wireline communication interface. The fog network gateway further includes connectivity logic configured to provide connection between a remote device and at least one local device via at least one of the wireless, cellular, and wireline communication interfaces, fog networking logic configured to form a fog network with the at least one local device for transmitting data thereto, and bandwidth aggregation logic configured to aggregate available bandwidth from at least two of the wireless, cellular, and wireline communication interfaces to ensure adequate bandwidth for data transmission between the remote device and the at least one local device. The fog network gateway further includes artificial intelligence logic configured to analyze data received from the at least one local device via the wireless, cellular, and wireline communication interfaces, and take appropriate action in response to the analysis.

Intelligent multi-modal IOT gateway

Systems and methods for forecasting wind farm power generation are disclosed. Via use of a support vector machine (SVM) enhanced Markov model, short-term wind power generation forecasts may be generated. Exemplary approaches accurately account for wind ramp-up and ramp-down, as well as diurnal non-stationarity and seasonality of wind power generation. Via use of the disclosed forecasting approaches, utilities and grid managers can make improved decisions relating to electrical power generation and transmission, thus reducing costs and reducing pollution.

Support vector machine enhanced models for short-term wind farm generation forecasting

Systems and methods for managing electricity of an electrical supply grid electrically connected to a wind farm are disclosed. Some systems and methods may include identifying relationships among a plurality of turbines in the wind farm with a minimum spanning tree, calculating a power output relationship among the plurality of turbines with the minimum spanning tree, creating a finite state space Markov chain forecast model for the plurality of turbines in the wind farm, predicting a power output of the wind farm with the finite state space Markov chain forecast model, and modifying at least one of a generation of electricity and a distribution of electricity based on the predicted power output of the wind farm. Also disclosed are systems and methods for predicting the power output of a wind farm.

Growing community of inventors

Tempe, AZ, United States of America

Junshan Zhang