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1.发明申请公开(公告)号：US20190354644A1
公开(公告)日：2019-11-21
申请号：US15983513
申请日：2018-05-18
Applicant: HONEYWELL INTERNATIONAL INC.
Inventor： Umut Orhan , Mohammad Moghadamfalahi , Steve Johnson
Abstract: An apparatus and method for detecting under performance of a current takeoff of an aircraft by predicting at least one takeoff performance characteristic of an aircraft prior to takeoff for a current flight is provided. The apparatus includes: at least one processor deployed on the aircraft, the at least one processor being programmed, when a model of thrust based on a lookup table is unavailable, to implement a trained model of thrust of the aircraft during a takeoff having a first component based on sensor data contributed from the current flight takeoff and having a second component based on derivative data contributed from a prior flights takeoff wherein the first and second components used in the model of the thrust are based on one aircraft takeoff characteristics of: acceleration from thrust, friction from slope, and drag from friction of the aircraft during the takeoff.
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2.发明申请公开(公告)号：US20190295566A1
公开(公告)日：2019-09-26
申请号：US15926408
申请日：2018-03-20
Applicant: HONEYWELL INTERNATIONAL INC.
Inventor： Mohammad Moghadamfalahi , Umut Orhan , Michael Dillard
Abstract: Methods, systems and apparatuses are provided to perform a continuous-to-continuous mapping of neural signal data received from one or more body sensors connected to an user wherein the one or more body sensors monitors at least neural activities of the user of a sub-vocalized voice at a sensory level and sends the neural signal data to a processor. The processor receives the neural signal data in an iterative closed loop to train the processor and to generate a sufficiently large data set in the neural signal domain to link to a produced voice domain. The processor constructs a common feature space which associates the neural signal domain with the produced voice domain wherein the common feature space implicitly extracts features related to audio communications for linking neural signal domain data to the produced voice data without requiring any prior feature classification of the received neural signal data.
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公开(公告)号：US20200380875A1
公开(公告)日：2020-12-03
申请号：US16833785
申请日：2020-03-30
Applicant: HONEYWELL INTERNATIONAL INC.
Inventor： Emmanuel Letsu-Dake , Umut Orhan , Mohammad Moghadamfalahi
Abstract: Methods and systems are provided for calculating and displaying flight safety analytics for an aircraft. The method comprises first receiving historical flight data for the aircraft from a flight data quick access recorder (QAR) located onboard the aircraft. The flight data is then processed to identify safety events and store the identified safety events in an events database. The contents of the events database are analyzed to determine statistical data regarding the identified safety events. An onboard predictive model is applied that utilizes the statistical data to predict the likelihood of a safety event based on current flight data received from the aircraft. The predicted likelihood of a safety event is displayed on a flight display of the aircraft.
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公开(公告)号：US10573335B2
公开(公告)日：2020-02-25
申请号：US15926408
申请日：2018-03-20
Applicant: HONEYWELL INTERNATIONAL INC.
Inventor： Mohammad Moghadamfalahi , Umut Orhan , Michael Dillard
Abstract: Methods, systems and apparatuses are provided to perform a continuous-to-continuous mapping of neural signal data received from one or more body sensors connected to an user wherein the one or more body sensors monitors at least neural activities of the user of a sub-vocalized voice at a sensory level and sends the neural signal data to a processor. The processor receives the neural signal data in an iterative closed loop to train the processor and to generate a sufficiently large data set in the neural signal domain to link to a produced voice domain. The processor constructs a common feature space which associates the neural signal domain with the produced voice domain wherein the common feature space implicitly extracts features related to audio communications for linking neural signal domain data to the produced voice data without requiring any prior feature classification of the received neural signal data.
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