Abstract: A method for performing an inference includes: detecting a context among at least one context associated with at least one application; triggering a model execution command to a smart agent of an electronic device, based on the detected context; loading a machine learning (ML) model into a secure storage of the electronic device, based on the detected context and the triggered model execution command; generating, using the loaded ML model, an inference, based on data associated with the detected context; and sharing the generated inference with each application of the at least one application that is registered for the detected context.

Abstract: Methods and systems for ascertaining factors contributing to the temperature of a device. A method includes monitoring a plurality of parameters that are contributing to a temperature of the device. The method also includes estimating a degree of contribution of internal factors to the temperature of the device based on the monitored plurality of parameters and a battery temperature of a battery of the device. The method further includes estimating a degree of contribution of external factors to the temperature of the device, based on the monitored plurality of parameters and a battery temperature of a battery of the device. A neural network can be used for estimating the temperature of the ambience of the device and the impacts of internal and external factors on temperature of the device.

Abstract: A method for managing memory for applications in a computing system includes receiving a selection of a preferred application. During user-controlled operation over the application, the transitions of selected application between foreground and background are monitored. A retention of the application in memory is triggered upon a transition of the application to background during the user operation. Retention of the application includes compressing memory portions of the application. Accordingly, the application is retained within the memory based on said compressed memory portions. A requirement to restore the retained application is sensed based on either a user selection or an automatically generated prediction and the application is restored from the retained state back to the foreground.

Abstract: A method for managing memory for applications in a computing system includes receiving a selection of a preferred application. During user-controlled operation over the application, the transitions of selected application between foreground and background are monitored. A retention of the application in memory is triggered upon a transition of the application to background during the user operation. Retention of the application includes compressing memory portions of the application. Accordingly, the application is retained within the memory based on said compressed memory portions. A requirement to restore the retained application is sensed based on either a user selection or an automatically generated prediction and the application is restored from the retained state back to the foreground.

Abstract: A method and an electronic device for secure training of an artificial intelligence (AI) model are provided. The method includes determining, by the electronic device, a first set of layers from a base AI model for performing training in a secure mode, and determining, by the electronic device, a second set of layers other than the first set of layers in the base AI model, simultaneously training, by the electronic device, the first set of layers in the secure mode and the second set of layers in a non-secure mode, and generating, by the electronic device, the AI model by combining the trained first set of layers and the trained second set of layers in the secure mode.

Abstract: A method for handling at least one resource operating performance configuration in an electronic device by the electronic device is provided. The method includes determining at least one event that is generated by the at least one application from a plurality of applications running in the electronic device. Further that requires acceleration of the at least one application from the plurality of applications running in the electronic device, the method includes fetching a system configuration based on the determination. Further, the method includes modifying the system configuration for each event to accelerate the execution of each event associated with the at least one application running in the electronic device. The method includes accelerate execution of the application running in the electronic device based on the modified system configuration.

Abstract: Embodiments herein provide an on-device method for enhancing user experience in an electronic device. The method includes monitoring a plurality of parameters associated with an operation of the electronic device. The method includes identifying an anomaly associated with the electronic device based on the plurality of parameters associated with the operation of the electronic device and identifying a class of anomaly to which the anomaly associated with the electronic device belongs using a first on-device model. Further, the method includes presenting at least one question associated with the identified class of anomaly to user of the electronic device using on a second on-device model and receiving at least one user input for the at least one question. Furthermore, the method includes performing at least one action for enhancing the user experience based on the at least one user input for the at least one question.

Abstract: A method for managing a boost time required for an application launch in an electronic device is provided. The method includes detecting, by the electronic device, a user input to launch the application. Further, the method includes measuring, by the electronic device, real-time system health parameters of the electronic device. Further, the method includes predicting, by the electronic device, an application launch time by inputting the real-time system health parameters to an AI-based application prediction model. Further, the method includes boosting, by the electronic device, at least one hardware of the electronic device based on the predicted application launch time.

Abstract: A method for securely sharing of data by an electronic device is provided. The method includes receiving, by the electronic device, data associated with the at least one application available at the electronic device and obtaining, by the electronic device, secured data by transforming the data associated with at least one application into an unrecognizable format using at least one conceal factor and at least one noise input. Further, the method includes extracting, by the electronic device, a plurality of features from the secured data, and sharing, by the electronic device, the plurality of features extracted from the secured data to a plurality of servers.

Abstract: Embodiments herein provide a method for securing Neural Network (NN) models. The method includes: identifying, by the first electronic device, a crucial layer of a first NN model that is to be deployed for processing in a second electronic device. The method includes extracting, by the first electronic device, the crucial layer of the first NN model. The method includes encrypting, by the first electronic device, the crucial layer. The method includes generating, by the first electronic device, a second NN model includes the encrypted crucial layer. The method includes deploying, by the first electronic device, the second NN model to the second electronic device for processing in the second electronic device.

Abstract: A method for managing memory for applications in a computing system includes receiving a selection of a preferred application. During user-controlled operation over the application, the transitions of selected application between foreground and background are monitored. A retention of the application in memory is triggered upon a transition of the application to background during the user operation. Retention of the application includes compressing memory portions of the application. Accordingly, the application is retained within the memory based on said compressed memory portions. A requirement to restore the retained application is sensed based on either a user selection or an automatically generated prediction and the application is restored from the retained state back to the foreground.

Abstract: A method for compensating for gyroscope drift on an electronic device includes receiving by a data processing unit, measurement data from a gyroscope. The method includes computing, by the data processing unit, a compensation parameter by analyzing the measurement data received from the gyroscope with respect to variations in temperature of the gyroscope. The method includes compensating, by the data processing unit, the measurement data by correcting the measurement data with the computed compensation parameter. The compensation parameter is continuously validated to correct the measurement data with the compensation parameter. Further, the received measurement data is updated continuously based on the computed compensation parameter, independent of the gyroscope on the electronic device, thereby facilitating adaptive drift compensation.

Abstract: Methods and systems for ascertaining factors contributing to the temperature of a device. A method includes monitoring a plurality of parameters that are contributing to a temperature of the device. The method also includes estimating a degree of contribution of internal factors to the temperature of the device based on the monitored plurality of parameters and a battery temperature of a battery of the device. The method further includes estimating a degree of contribution of external factors to the temperature of the device, based on the monitored plurality of parameters and a battery temperature of a battery of the device. A neural network can be used for estimating the temperature of the ambience of the device and the impacts of internal and external factors on temperature of the device.

Abstract: Embodiments herein provide an on-device method for enhancing user experience in an electronic device. The method includes monitoring a plurality of parameters associated with an operation of the electronic device. The method includes identifying an anomaly associated with the electronic device based on the plurality of parameters associated with the operation of the electronic device and identifying a class of anomaly to which the anomaly associated with the electronic device belongs using a first on-device model. Further, the method includes presenting at least one question associated with the identified class of anomaly to user of the electronic device using on a second on-device model and receiving at least one user input for the at least one question. Furthermore, the method includes performing at least one action for enhancing the user experience based on the at least one user input for the at least one question.

Abstract: A smart device and a method of operating the same are provided. The smart device includes a processor, and a sensor configured to detect movement of the smart device, generate an interrupt signal including information on a movement range corresponding to at least one movement type determined based on the detected movement, and output the interrupt signal to the processor and the processor is configured to control an action, corresponding to the interrupt signal received from the sensor, to be performed in response to the interrupt signal.

Abstract: A method for compensating for gyroscope drift on an electronic device includes receiving by a data processing unit, measurement data from a gyroscope. The method includes computing, by the data processing unit, a compensation parameter by analyzing the measurement data received from the gyroscope with respect to variations in temperature of the gyroscope. The method includes compensating, by the data processing unit, the measurement data by correcting the measurement data with the computed compensation parameter. The compensation parameter is continuously validated to correct the measurement data with the compensation parameter. Further, the received measurement data is updated continuously based on the computed compensation parameter, independent of the gyroscope on the electronic device, thereby facilitating adaptive drift compensation.

Abstract: A smart device and a method of operating the same are provided. The smart device includes a processor, and a sensor configured to detect movement of the smart device, generate an interrupt signal including information on a movement range corresponding to at least one movement type determined based on the detected movement, and output the interrupt signal to the processor and the processor is configured to control an action, corresponding to the interrupt signal received from the sensor, to be performed in response to the interrupt signal.