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Top1. Introduction
Context-aware computing (Ben et al., 2017) refers to a class of mobile computing capable of sensing their external conditions and adapting their behaviors to provide quality services in the demanded location and within a stipulated time frame for the customer. To show the relationship between locations based service and context awareness, one must know about context-awareness. Examples of context-aware information systems include user movement (walking or driving), current state (awake or asleep) identity, current season, date or time of day, weather conditions, physical location, etc. Significant causes of such information are mostly a server for the query response, a receiver for the global positioning system (GPS), microphone, camera, web browser, etc. Here, the entity might be an individual, application, or device. Table 1 depicts the categories of context be defined by 5 W's.
Table 1. Categories of Context: 5 W's
Category | Meaning | Type | Example |
Who | Identity | Social Context | Who are the people with whom the user is interacting, or who is nearby? Every entity has a unique id. |
What | Activity | Functional Context | What is happening in the situation (touring a museum or reading a book)? |
Where | Location | Spatial Context | Home? Work? Bathroom? Familiar coffee shop? Position, spatial relationships (latitude/longitude, with friends, near a Starbucks, in the library) |
When | Time | Temporal Context | What time is it? (current time, duration of the event, and temporal ordering) |
Why | Reason | Motivating Context | Why is the user performing a particular task? |
Location-based Service (LBS) (Park et al., 2007; Gupta & Shanker, 2018a; Gupta & Shanker, 2018b) is one of the recent advances among different information communication technologies, in which most of the applications use some context-aware information related to the mobile client. The examples of LBS based query include locating the closest hotel etc. (Xiao et al., 2010; Zheng et al. and relevant links to knowledge applications such as road charts, news and traffic reports, etc. (Calabrese et al., 2010; Jeong et al., 2016).