In recent years, the usage of mobile phone is increasing significantly across the world. According to statistics as of 2013, 73% of internet users accessed the internet resources via a mobile device and this percentage projected to nearly 90% by 2017. Mobile phones’ number and types of integrated sensors, processing capacity, battery, and overall hardware qualities are also improving. Due to their conveniences and smartness behavior they became prevalent in our daily life and even may lead us to overuse . We are talking our phone with us everywhere anytime. Even though, the smartness of the phones are increasing they are not smart enough to operate automatically based on user’s current situation. This problem and increasing numbers of integrated sensors provides new opportunity for the development of applications that can sense user’s operating conditions and surrounding environment (we call this as context) and react accordingly[4, 5].
The understanding of users context from such raw sensor data (low level ‘context) has been an emerging research opportunity. Context encompasses where you are, who you are with, and what resources are nearby. The most significant reason for today’s smartphone revolution is their capability of providing context aware services. Mobile apps generally get access to richer context as almost all smartphones today are equipped with location sensors, motion sensors, Bluetooth, and Wi-Fi. By exploit their data, apps can achieve ‘context awareness’ that can significantly increase their capabilities and value, and can really make our phones smarter and more proactive personal assistant. Obviously, such phones are really makes our lives simple.
Context-aware mobile apps are capable of giving service without requiring user intervention and this is highly consistent with ubiquity , these are an important and valuable step down this path. They employ contextual information collected from their sensors to proactively provide the user with valuable information and they do so with minimal effort on the part of the user. They can sense and react based on the contextual data it has access to. Through trends it observes over the course of usage of the device, and/or through feedback provided by the user, such an app can actually ‘learn’ over time, thereby becoming ‘smarter’ and more useful.
One challenge of context awareness is to exploit the dynamic environment with a new class of applications that are aware of the context in which they are run. There are many different activities that can people do in their daily life. These activates are different in their location, time, surrounding environment (noise level, network connectivity, social situation and etc.) and these parameters are changing from activity to activity. Context-aware apps adapts according to such changes over time. A system with these capabilities can examine the computing environment and react to changes to the environment.
Other challenge is limited battery power of phones. Context sensing is expensive in terms of energy as involves various sensors and it’s very expensive when individual context aware apps carry on detecting context. This becomes real world problem due to increasing usage and numbers of continuous context aware apps.
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