Abstract: A method for identifying a dynamic resolution for an application (150) of an electronic device (100) is provided. The method includes identifying, by the electronic device, a base resolution for a window of the application (150), wherein the window includes a plurality of views; identifying, by the electronic device, a plurality of resolutions respectively corresponding to the plurality of views based on the base resolution and at least one characteristic of each of the plurality of views; applying, by the electronic device, the plurality of resolutions to the plurality of views, respectively; and displaying, by the electronic device, the plurality of views in the plurality of resolutions, respectively.

Abstract: Embodiments herein disclose a method for enhancing a performance of an electronic device. The method includes detecting a plurality of hardware features of the electronic device. Further, the method includes learning a usage pattern of each of the hardware features of the electronic device over a period of time using a machine learning model. Further, the method includes predicting at least one of a remaining usage time of a battery of the electronic device and at least one application to be launched by a user of the electronic device based on the usage pattern of each of the hardware features. Further, the method includes enhancing the performance of the electronic device based on at least one of the predicted remaining usage time of the battery and the at least one predicted application to be launched by the user.

Abstract: A method for identifying a dynamic resolution for an application (150) of an electronic device (100) is provided. The method includes identifying, by the electronic device, a base resolution for a window of the application (150), wherein the window includes a plurality of views; identifying, by the electronic device, a plurality of resolutions respectively corresponding to the plurality of views based on the base resolution and at least one characteristic of each of the plurality of views; applying, by the electronic device, the plurality of resolutions to the plurality of views, respectively; and displaying, by the electronic device, the plurality of views in the plurality of resolutions, respectively.

Abstract: A method of controlling an electronic device is provided. The method includes transmitting a communication signal to a plurality of candidate devices in the vicinity of the electronic device, generating a function code including configuration information of the electronic device, receiving candidate function codes including configuration information of the plurality of candidate devices from the plurality of candidate devices based on the communication signal, and when a feature of the plurality of candidate devices is determined to be similar to a feature of the electronic device based on the candidate function condes, generating at least one of an alert signal or a setting signal based on whether the function code matches the candidate function codes.

Abstract: A method of controlling an electronic device is provided. The method includes transmitting a communication signal to a plurality of candidate devices in the vicinity of the electronic device, generating a function code including configuration information of the electronic device, receiving candidate function codes including configuration information of the plurality of candidate devices from the plurality of candidate devices based on the communication signal, and when a feature of the plurality of candidate devices is determined to be similar to a feature of the electronic device based on the candidate function condes, generating at least one of an alert signal or a setting signal based on whether the function code matches the candidate function codes.

Abstract: Embodiments herein disclose a method for enhancing a performance of an electronic device. The method includes detecting a plurality of hardware features of the electronic device. Further, the method includes learning a usage pattern of each of the hardware features of the electronic device over a period of time using a machine learning model. Further, the method includes predicting at least one of a remaining usage time of a battery of the electronic device and at least one application to be launched by a user of the electronic device based on the usage pattern of each of the hardware features. Further, the method includes enhancing the performance of the electronic device based on at least one of the predicted remaining usage time of the battery and the at least one predicted application to be launched by the user.