Abstract
The objective of the project is to design a learning application for android-based devices that will track the user’s behavior pattern and allow the user to manage his device smartly. There are a few existing apps that are already exhibiting this behavior for example App Usage Tracker . However, Smart app does provide more knowledgeable actions compared to others (for example: comparison between user’s top favorites and user’s calculated favorites, easy access to the favorite apps by creating shortcuts on the home screen etc.). App Usage tracker application is also capable of learning the user’s mobile behavioral patterns. The behavioral patterns captured would include number of things that would help the mobile users to combine statistics and provide insights into mobile device usage. For instance, Smart will tell which applications the user uses frequently on a certain period like daily, weekly and monthly by which the user will come to know which apps he/she uses regularly. That would be the user’s favorite app-“the app used most frequently”. There would also be comparison between the user’s top rated apps (wherein user gives initial rating to the apps according to his choice) v/s user’s calculated favorite rating (which would be coming from the learning done on the user’s behavior patterns). Along with this learned data of user’s behavior patterns, the application also provides an insight into the average power consumption for the apps. This app is also intended to use the data gathered from learning a user's patterns to convert them into some knowledgeable actions that would enable more effective device use. For instance, creating a shortcut of the learned favorite apps to the home screen. This list will be refreshed every time the application is run. In this way, the old favorite list would be refreshed automatically. The user will also be notified for the maximum battery using app during the course of his usage based on a certain set threshold.