Haptic-based artificial neural network training
원문보기
IPC분류정보
국가/구분
United States(US) Patent
등록
국제특허분류(IPC7판)
G06F-015/18
G06E-001/00
G06E-003/00
G06G-007/00
G06N-003/08
G06F-003/01
출원번호
US-0132113
(2013-12-18)
등록번호
US-9230208
(2016-01-05)
발명자
/ 주소
Chatterjee, Aveek N.
Adoni, Siddique M.
Shanmugam, Dhandapani
출원인 / 주소
International Business Machines Corporation
대리인 / 주소
Wixted, III, Edward J.
인용정보
피인용 횟수 :
1인용 특허 :
14
초록▼
In a method for training an artificial neural network based algorithm designed to monitor a first device, a processor receives a first data. A processor determines a first service action recommendation for a first device using the received first data and an artificial neural network (ANN) algorithm.
In a method for training an artificial neural network based algorithm designed to monitor a first device, a processor receives a first data. A processor determines a first service action recommendation for a first device using the received first data and an artificial neural network (ANN) algorithm. A processor causes a second device to provide haptic feedback using the received first data. A processor receives a second service action recommendation for the first device based on the haptic feedback. A processor adjusts at least one parameter of the ANN algorithm such that the ANN algorithm determines a third service action recommendation for the first device using the received first data, wherein the third service action recommendation is equivalent to the second service action recommendation.
대표청구항▼
1. A computer program product for training an artificial neural network based algorithm designed to monitor a first device, the computer program product comprising: one or more computer-readable storage media and program instructions stored on the one or more computer-readable storage devices, the p
1. A computer program product for training an artificial neural network based algorithm designed to monitor a first device, the computer program product comprising: one or more computer-readable storage media and program instructions stored on the one or more computer-readable storage devices, the program instructions comprising:program instructions to receiving a first data;program instructions to determine a first service action recommendation for a first device using the received first data and an artificial neural network (ANN) algorithm;program instructions to cause a second device to provide haptic feedback using the received first data;program instructions to receive a second service action recommendation for the first device based on the haptic feedback;program instructions to determine that the second service action recommendation is different than the first service action recommendation; andprogram instructions to adjust at least one parameter of the ANN algorithm such that the ANN algorithm determines a third service action recommendation for the first device using the received first data, wherein the third service action recommendation is equivalent to the second service action recommendation. 2. The computer program product of claim 1, wherein program instructions to receive the first data comprises program instructions to receive the first data from one or more sensors operably affixed to the first device. 3. The computer program product of claim 2, wherein the one or more sensors collect amplitude and frequency data of vibrations of the first device. 4. The computer program product of claim 1, further comprising: program instructions, stored on the one or more computer-readable storage devices, to receive a previously stored data and a previously stored service action recommendation for the first device associated with the previously stored data; andwherein program instructions to adjust the at least one parameter of the ANN algorithm such that the ANN algorithm determines the third service action recommendation for the first device using the received first data, wherein the third service action recommendation is equivalent to the second service action recommendation comprises:program instructions, stored on the one or more computer-readable storage devices, to adjust the at least one parameter of the ANN algorithm such that the ANN algorithm determines a fourth service action recommendation for the first device using the previously stored data and the ANN algorithm determines the third service action recommendation for the first device using the received first data, wherein the third service action recommendation is equivalent to the second service action recommendation and wherein the fourth service action recommendation is equivalent to the previously stored service action recommendation. 5. The computer program product of claim 1, further comprising: program instructions, stored on the one or more computer-readable storage devices, to receive a video feed from one or more video recording devices depicting at least a portion of the first device; andprogram instructions, stored on the one or more computer-readable storage devices, to cause the video feed to be displayed. 6. The computer program product of claim 5, wherein program instructions to receive a second service action recommendation for the first device based on the haptic feedback comprises: program instructions to receive a second service action recommendation for the first device based on the haptic feedback and the video feed. 7. The computer program product of claim 1, wherein the haptic feedback includes generated physical properties to simulate how a surface of a component of the first device feels. 8. The computer program product of claim 1, wherein the at least one parameter includes a function and a weight. 9. A computer system for training an artificial neural network based algorithm designed to monitor a first device, the computer system comprising: one or more computer processors, one or more computer-readable storage media, and program instructions stored on the computer-readable storage media for execution by at least one of the one or more processors, the program instructions comprising:program instructions to receiving a first data;program instructions to determine a first service action recommendation for a first device using the received first data and an artificial neural network (ANN) algorithm;program instructions to cause a second device to provide haptic feedback using the received first data;program instructions to receive a second service action recommendation for the first device based on the haptic feedback;program instructions to determine that the second service action recommendation is different than the first service action recommendation; andprogram instructions to adjust at least one parameter of the ANN algorithm such that the ANN algorithm determines a third service action recommendation for the first device using the received first data, wherein the third service action recommendation is equivalent to the second service action recommendation. 10. The computer system of claim 9, wherein program instructions to receive the first data comprises program instructions to receive the first data from one or more sensors operably affixed to the first device. 11. The computer system of claim 10, wherein the one or more sensors collect amplitude and frequency data of vibrations of the first device. 12. The computer system of claim 9, further comprising: program instructions, stored on the computer-readable storage media for execution by at least one of the one or more processors, to receive a previously stored data and a previously stored service action recommendation for the first device associated with the previously stored data; andwherein program instructions to adjust the at least one parameter of the ANN algorithm such that the ANN algorithm determines the third service action recommendation for the first device using the received first data, wherein the third service action recommendation is equivalent to the second service action recommendation comprises:program instructions, stored on the computer-readable storage media for execution by at least one of the one or more processors, to adjust the at least one parameter of the ANN algorithm such that the ANN algorithm determines a fourth service action recommendation for the first device using the previously stored data and the ANN algorithm determines the third service action recommendation for the first device using the received first data, wherein the third service action recommendation is equivalent to the second service action recommendation and wherein the fourth service action recommendation is equivalent to the previously stored service action recommendation.
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이 특허에 인용된 특허 (14)
Lind, Michael A.; Priddy, Kevin L.; Morgan, Gary B.; Griffin, Jeffrey W.; Ridgway, Richard W.; Stein, Steven L., Application specific intelligent microsensors.
Cole, Alan G.; Mohammed, Siddique A.; Moore, Victor S.; Shanmugam, Dhandapani, Matching audio advertisements to items on a shopping list in a mobile device.
Matada, Sandeep K.; Moore, Victor S.; Shanmugam, Dhandapani, Supporting multiple subscriber identities in a portable device using a single transceiver.
Matada, Sandeep K.; Moore, Victor S.; Shanmugam, Dhandapani, Supporting multiple subscriber identities in a portable device using a single transceiver.
Mohammed, Siddique; Shanmugam, Dhandapani, System and method of dynamically generating a frequency pattern to realize the sense of touch in a computing device.
Mohammed, Siddique; Shanmugam, Dhandapani, System and method of dynamically generating a frequency pattern to realize the sense of touch in a computing device.
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