Intelligent System of Information Broker under a Data and Energy Storage Internet Infrastructure

    公开(公告)号:US20170257450A1

    公开(公告)日:2017-09-07

    申请号:US15057665

    申请日:2016-03-01

    CPC classification number: H04L67/22 H02J3/14 H02J13/0006 H04L67/12

    Abstract: A method implemented in a network element (NE) configured to operate as an Ensemble Information Broker (EIB) within a data and energy storage internet architecture, the method comprising collecting device data, human presence data, and human activity data; determining predicted human behaviors for the user; determining a predicted energy metric for the smart system during a future time slot; calibrating weighted objective metrics of an operating status of the devices, a human comfort level, and a human productivity level according to the predicted human behaviors and user defined preference levels defined for the smart system; generating a set of control commands for the devices within the smart system by executing the dynamic human-centric Objective Function on the predicted energy metric; and transmitting, via a transmitter, the set of control commands to corresponding devices within the smart system.

    Adaptive passenger comfort enhancement in autonomous vehicles

    公开(公告)号:US10029698B2

    公开(公告)日:2018-07-24

    申请号:US15213532

    申请日:2016-07-19

    Abstract: A system and method for performing self-learning for adaptively achieving passenger comfort enhancement in an autonomous vehicle. The system comprises a plurality of sensor inputs. Each sensor input provides data representative of voice responses and image responses from a passenger in the vehicle. A controller is coupled to the plurality of sensor inputs. The controller generates and updates a reward function that includes a plurality of driving state transitions. The reward function is updated based on destination information and the data representative of the voice and image responses. The controller further generates a goal function that determines an optimized driving state transition updates the goal function based on the updated reward function and a previous goal function. The controller also generates a vehicle speed control signal, based on the updated goal function, to control the speed of the autonomous vehicle.

    Communication Between Distributed Information Brokers Within a Data and Energy Storage Internet Architecture

    公开(公告)号:US20170176955A1

    公开(公告)日:2017-06-22

    申请号:US14970906

    申请日:2015-12-16

    CPC classification number: G05B13/026 H02J3/00 H02J2003/003 H04L43/08

    Abstract: A method implemented in a network element (NE) configured to operate as an Ensemble Information Broker (EIB) within a distributed data and energy storage internet architecture comprising collecting energy data indicating a flow of energy, an amount of energy consumed and generated by devices; collecting human presence data; collecting human activity data; predicting future energy consumption requirements and generation by employing prediction algorithms and analyzing the collected data; generating a set of control commands based on the predicted future energy consumption requirements and energy generation as applied to a cost function; transmitting the set of control commands to the corresponding devices; transmitting a broadcast message to determine an external NE to establish as a friend connection based on a user preference; transmitting a request to establish a friend connection with the determined NE; and transmitting the human presence data to the external NE when the friend connection is established.

    Integrated system for detection of driver condition

    公开(公告)号:US10592785B2

    公开(公告)日:2020-03-17

    申请号:US15647748

    申请日:2017-07-12

    Abstract: Methods, apparatus, and systems are provided for integrated driver expression recognition and vehicle interior environment classification to detect driver condition for safety. A method includes obtaining an image of a driver of a vehicle and an image of an interior environment of the vehicle. Using a machine learning method, the images are processed to classify a condition of the driver and of the interior environment of the vehicle. The machine learning method includes general convolutional neural network (CNN) and CNN with adaptive filters. The adaptive filters are determined based on influence of filters. The classification results are combined and compared with predetermined thresholds to determine if a decision can be made based on existing information. Additional information is requested by self-motivated learning if a decision cannot be made, and safety is determined based on the combined classification results. A warning is provided to the driver based on the safety determination.

    INTEGRATED SYSTEM FOR DETECTION OF DRIVER CONDITION

    公开(公告)号:US20190019068A1

    公开(公告)日:2019-01-17

    申请号:US15647748

    申请日:2017-07-12

    Abstract: Methods, apparatus, and systems are provided for integrated driver expression recognition and vehicle interior environment classification to detect driver condition for safety. A method includes obtaining an image of a driver of a vehicle and an image of an interior environment of the vehicle. Using a machine learning method, the images are processed to classify a condition of the driver and of the interior environment of the vehicle. The machine learning method includes general convolutional neural network (CNN) and CNN with adaptive filters. The adaptive filters are determined based on influence of filters. The classification results are combined and compared with predetermined thresholds to determine if a decision can be made based on existing information. Additional information is requested by self-motivated learning if a decision cannot be made, and safety is determined based on the combined classification results. A warning is provided to the driver based on the safety determination.

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