Context in mobile computing

Running Head: CONTEXT IN MOBILE COMPUTING 1

CONTEXT IN MOBILE COMPUTING 5

Context in Mobile Computing

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Context in Mobile Computing

In recent decades, there have been rapid advances in mobile computing, such as context awareness, integrated sensor technologies and a wide range of wired and wireless practices. Most of the modern mobile computing systems can use context to provide appropriate information and services to the user, where relevance depends on the user's task (Zheng et al., 2016). The purpose of having mobile computing systems that are context-aware is to offer the various services at a reasonable development cost and with simple reconfiguration. That being said, it is important to discuss context awareness in mobile computing. This paper will discuss context as it applies to mobile computing and the various ways in which context has been used. Besides, the paper will describe sensor fusion as it applies to context and suggests new ways of using context.

Context as it applies to Mobile Computing

The concept of context has been explored by a number of researchers. Musumba and Nyongesa (2013) argue that context encompasses location, characteristics of neighboring users or objects and the consequent changes. Talipov et al. (2015) refer to context as location, environment attributes, time and the identities of neighboring users. According to Riboni (2015), context involves the user's feelings, concentration, location, date and time, and the objects in the user's environment. Based on these definitions, it is notable that the most important aspects of context are user location, the user's environment, and the objects near the user. Additionally, it can be said that context is subject to the constantly shifting execution environment. Even though the notion of context comprises the understandings of a scenario, much of the effort within the mobile computing community takes a bottom-up methodology to context.

In mobile computing, context involves the understanding of the physical environment and how the implicit input influences the behavior of an application. It encompasses three forms of the environment – computing environment, user environment and the physical environment (Vinh & Suzuki, 2013). Through the concept of context, these environments are able to interact constantly. The information in the computing and physical environments of mobile devices generates a context for interaction between users and devices. Since the current mobile devices process a wide range of data, context help in controlling the ways users interact with the ubiquitous environment based on their repetitive tasks (Zheng et al., 2016). For instance, a context-aware mobile system can detect that a user never uses his or her phone while at work, and hence all the calls or messages are directed to the user's voicemail when they are working.

Use of Context

The purpose of context-awareness is to determine what the user is attempting to do when interacting with applications and systems. Without the context, it can be challenging to determine the user's objective. The context cues are used to inform an application on the best way to enhance user-application interaction. As such, context awareness signifies a standardized framework of input, enabling almost all applications to be regarded more or less context-aware as they interact with the users (Talipov et al., 2015). There is still a contentious argument as to whether context should only encompass automatically generated information or should comprise physically acquired information. While the context would be generated automatically in an ideal setting, it depends on the user input in real-life scenarios (Schmidt et al., 1999). This means that the context can only be physically generated in a real-life scenario.

Emmanouilidis et al. (2013) advocate three basic applications of context in applications and systems. These include the presentation of information and services, implementation of services and storage of information. Context can enable the user to acquire the information and services provided by the various mobile computing systems. At the same time, it can suggest suitable options for actions to the user. For example, the context-aware mobile device can guide the user to a specific location on a map and perhaps propose neighboring objects or sites, presenting an alternative of services nearby, sensing and providing input or output information for specific users and notifying the neighboring users.

As far as the implementation of services is concerned, context is used to initiate commands or reconfigure the system on behalf of the user based on the changes in the environment. For instance, a user's desktop environment can be transferred from one workstation to another. Other examples include a scenario whereby the camera captures a picture when a biometric sensor is used or a situation where a car navigation system redirects the driver once the car makes a wrong turn. With regards to the storage and retrieval of information, context enables applications to capture the relevant information (Musumba & Nyongesa, 2013). For example, a user interface in a conference may provide the speeches or notes based on the users who were there, when the conference happened and the location of the conference. Another instance can be a scenario where a system in Zoo may tag information asked by the user based on their location and time.

Sensor Fusion as it applies to Context

Today, mobile computing applications and systems frequently use sensor fusion. As Pan and Zhu (2015) define it, sensor fusion is the combination of data from multiple sensors to acquire a more precise depiction of the sensor's environment. Through the use of multiple sensors, it is possible to gain rich data from which suitable context can be inferred with reasonably less computation. Each sensor has to contribute to generating the entire depiction, which means that pre-processing of sensor data will be more intensive. Besides, each sensor controls the information about all sensors that bring about the context information, the time used to distinguish the context information, and all actions in the system during the update of context information (Stojanovic, 2009). Further, the sensors will report its accessibility to the appropriate sensor fusion mediator.

The first sensor to report in the system may initiate the process of updating the information. However, the sensor fusion mediator will take actions as regards the time and process of updating the system (Subramanya & Yi, 2007). This is achieved by selecting some sensors that initiate the actions. Differentiating the context starts with the sensors raising an update; it then begins to request information from all available sources in the sensor list. If there is a change in the sensor configuration, it is updated in the sensor and modifies the approximated duration required to update the context information (Zheng et al., 2016). Using the information from multiple sensors, context makes applications more strong to the influence of system configuration change. The context simplifies artificial intelligence algorithms to acquire data that can generate high-level context information.