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    • 2. 发明专利
    • A SYSTEM FOR IDENTIFICATION OF PERSONALITY TRAITS AND A METHOD THEREOF
    • AU2021104218A4
    • 2021-09-09
    • AU2021104218
    • 2021-07-16
    • BAGGA JASPALCHOPRA JHARNADEWANGAN AMIT KUMARKUMAR NAGWANI NARESHKUMAR KALLEPALLI ROHITSHARMA SURAJSRIVASTAVA SUMITVERMA AMRITA
    • SHARMA SURAJSRIVASTAVA SUMITBAGGA JASPALKUMAR NAGWANI NARESHDEWANGAN AMIT KUMARKUMAR KALLEPALLI ROHITCHOPRA JHARNAVERMA AMRITA
    • G06F40/00G06K9/00G06N3/02
    • A system for identification of Personality Traits in Text, comprises of: an input module 102 for receiving a plurality of text data, wherein the plurality of text data is segregated into a plurality of datasets based on label, wherein the plurality of dataset is divided into a training and a validation dataset, an extraction module 104 for extracting the plurality of text data from the plurality of partitioned dataset, wherein the plurality of text data is pre-processed using a time efficient sentence tokenization algorithm, an encoding module 106 for encoding each word of the text using an encoding technique, wherein a document formed of the encoded text undergoes padding and shortening of the data and a training module 108 for identifying the personality traits from the encoded text using a neural network, wherein an optimization module optimizes a learning rate for obtaining a precisely identified personality trait. INPUT MODULE EXTRACTION MODULE ENCODING MODULE TRAINING MODULE receiving a plurality of text data an input module 102, wherein the plurality of text data is segregated into a plurality of datasets based on label, wherein the plurality of dlataset is divided into a training and a validation dataset 202 extracting the plurality of text data from the plurality of partitioned dataset using an extraction module 104 connected to the input module 102, wherein the plurality of text data is pre-processed using a time efficient sentence tokenization algorithm 204 encoding each word of the text using an encoding technique using an encoding module 106 connected to the extraction module 104, wherein a document formed of the encoded text undergoes padding and shortening of the data 206 identifying the personality traits from the encoded text using a neural network of a training module 108 connected to the encoding module 106, wherein an optimization module optimizes a learning rate ofthe training module 108 for obtaining a precisely identified personality trait 208
    • 4. 发明专利
    • HOME AUTOMATION BASED ON INTERNET OF THINGS AND USER DETECTION
    • AU2021106649A4
    • 2021-11-25
    • AU2021106649
    • 2021-08-23
    • SRIVASTAVA SUMITSHARMA TRIPTIATULKAR MITHILESHCHOUDHARY PRASHANT KUMARTIWARI SHRIKANTCHANDE MANOJ KUMARNAGWANSHI KAPIL KUMARTIWARI RAJESH
    • SRIVASTAVA SUMITSHARMA TRIPTIATULKAR MITHILESHCHOUDHARY PRASHANT KUMARTIWARI SHRIKANTCHANDE MANOJ KUMARNAGWANSHI KAPIL KUMARTIWARI RAJESH
    • G05B15/02
    • A system and a method for home automation based on user detection, comprising: an identification module (102) for identifying a registered user device (104) with in a connecting range; an image capturing module (106) for identifying a person, wherein face recognition module (108) for recognizing a user; a first controlling module (110) for identifying the user and generate a first control signal to adjust lighting and temperature of the premises based on pre-selected user preference, wherein if a plurality of registered users enter the premises an average of the pre-selected user preference stored on the registered user device is calculated to adjust lighting and temperature of the premises; and a second controlling module (112) for generating a second command signal for locking at least one door upon detection of a new user device with in a connecting range, wherein an alert module for notifying the user about an unknown entry. IDENTIFICATION MODULE FACE RECOGNITION MODULE USER DEVICE FIRST CONTROLLING IMAGE CAPTURING SECOND CONTROLLING MODULE MODULE identifying a registered user device with in a connecting range using an identification module (102) positioned at an entrance identifying a person at the entrance using an image capturing module (106) 202 connected to the identification module (102) upon identification of the user device (104), wherein recognizing a user using a face recognition module (108) associated "204 with the image capturing module (106); generating a first control signal to adjust lighting and temperature of the premises using a first controlling module (110) connected to the image processing module upon identifying the user based on pre-selected user preference stored on the registered user device, wherein if a plurality of registered users enter the premises an average of the pre-selected user preference stored on the registered user device is calculated to adjust lighting and temperature of the premises 206 generating a second command signal using a second controlling module for locking at least one door upon detection of a new user device with in a connecting range, wherein notifying the user about an unknown entry using an alert module is associated with the second controlling module (112).