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A BRAIN CLONING SYSTEM AND METHOD THEREOF
专利权人:
VAISH; Diwakar
发明人:
VAISH, Diwakar
申请号:
ININ2017/050616
公开号:
WO2018/122868A1
申请日:
2017.12.27
申请国别(地区):
WO
年份:
2018
代理人:
摘要:
This invention relates to a system and method for brain cloning. The method for brain cloning comprising the steps of receiving, a plurality of data values for a subject by a plurality of input devices for a specified dynamic event with respect to a plurality of brain waves and environmental factors providing, the subject in a first course of action based on a dynamic environment employed with a user desirable interest. The first course of action is further comprising the steps of searching, about the subject in the cloud database connected to a processing unit via a cloud network colligating, about a characteristic of the subject to further categorize the subject into a preliminary provincial database by the processing unit storing, a plurality of parameters for a user desired task with the subject by the processing unit in prudence of the plurality of brain waves and environmental factor in the preliminary provincial database learning, by a machine learning interface about an interest factor of a user for the subject using the data values provided by the plurality of input devices. Further, in a second course of action, the similar subject is received via a subject recognition device, and searching for the similar subject to identify, in the cloud database via a cloud network, and for the previous results of the subject to the previous related dynamic event in addition with the value stored in preliminary provincial database The method furthermore comprised of recognizing, the subject with the previously performed results and the plurality of brain waves and environmental factors in the first course of action determining, the output by the processing unit, on the basis of previously stored data values and the results in the preliminary provincial database. Performing, again the similar user desired task with respect to the user interest dynamically, by an automaton unit which is communicatively coupled to the processing unit and the machine learning interface.La p
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