Context aware location based service
- 1. Topic: Context Aware Location Based Service Presented By: Saina Kumari 18352046 M.C.A 4th Sem Fundament Of Context Aware Computing Pondicherry University
- 2. Before defining what is context aware Location based service. Let’s define context first. Context: Dey’s defined context as ‘Any information that can be used to characterize the situation of an entity. An entity is a person, place or object that is considered relevant to the interaction between a user and an application, including the user and application themselves. Example: Contexts can include information such as location (e.g., of people or objects), time, execution state of applications, computational resources, network bandwidth, activity, user intentions, user emotions (Picard, 1997), and conditions of the environment (Dey, 2001).
- 3. Q.) What it means for systems to be context aware? According to Quoting from Schilit (1995): “… Context-aware software adapts according to the location of use, the collection of nearby people and objects, the accessible devices, as well as changes to those objects over time. A system with these capabilities surveys the computing environment and reacts to changes to that environment.” Context-aware pervasive computing is a study of pervasive computer systems (a combination of hardware and software) that are aware of context and can automatically adapt and respond to such context. Context awareness enables the system to take action automatically, reducing the burden of excessive user involvement and providing proactive intelligent assistance.
- 4. Now it is the time to define what is Context Aware Location Based Service. Context Aware Location Based Service: It provide new services to their customers based on the knowledge of their locations. Examples of these services are as follow: i.) ATM finder (“Find the ATM near to my location”). ii.) Location-based advertising (“Send current sale details to all people that who are within two miles of my gas station”). iii.) Show live traffic reports (“Continuously, let me know if there is congestion within five minutes of my route”).
- 5. Q.) How It works? Step 1: Users issue location-based queries (e.g., “Find the ATM near my location”) through their personal devices. Step 2: Mobile devices are connected to a database server to submit their queries along with their locations Step 3: Queries and Location retrieved through location-detection devices such as GPS. Step 4: The database server evaluates the user query based on the user location, the underlying map, and the locations of objects of interest (e.g., ATM). Step 5: The users can see the answer of their queries on the handheld devices guided by the map layout.
- 6. CareDB system: It is a context and preference-aware location-based database system. It is a complete database system, implemented in PostgreSQL. Each context can be either static (rarely changed) or dynamic (frequently changing). Static/dynamic context is depicted by solid/dotted lines and dark/light gray rectangles, respectively, in Figure 1.
- 7. CareDB Input: It is of three types as follow: i.) User Context: It is any extra information about a user. Static Context: Income, Profession, Age. Dynamic Context : Current user location or status (e.g., “at home”, “in meeting”). ii.) Database Context: It refers to application-specific data sources (e.g., restaurant, hotel, and taxi databases) that are registered with CareDB. Ex: For a restaurant database Static Context : Price, Rating, and Operating hours. Dynamic Context: Current waiting time. iii.)Environmental Context: It is any information about surrounding environment. This data is assumed to be stored at a third party and accessed by the query processor during query runtime by calling the data source through a remote API (e.g., web service Interface). Static Context: weather information (e.g., from NWS). Dynamic Context: Traffic and travel time (e.g., from Yahoo Traffic),
- 8. Query Building: It is used to personalize queries for each user such that the best answers are returned. The user submits simple queries without constraints (e.g., “Find me a It creates preference queries by augmenting the submitted query with the preferences stored in the user’s preference profile. Query Processor: The main responsibilities of this module are to embed context-awareness into existing core processing of query operators, support the integration between aware queries and a wide class of location-based queries, and provide support of environmental context as well as both the user and database context.
- 9. Application: The application we use is RestPref. Restpref: It a location-based restaurant and hotel finder application built specifically for this demonstration. A.) It comes in two versions: (i.) web-based: It displayed in a standard browser (ii.) Mobile-based : It as an iPhone application. B.) Backend database : CareDB Here it perform query processing tasks. C.) The user issues a simple query by pressing a button D.) In application three botton for the following use: (a) “Find me a restaurant”. (b) “Find me a hotel”. (c) ”Find me a hotel/restaurant pair”.
- 10. Figure 2: RestPref Demo Application
- 11. After pressing the button it will do the following step: Step i: According to the user’s preference and context constraints based on the users’s preference profile. The context and preferences constraint forwards to CareDB. Step ii: CareDB returns the personalized SQL query that was run on CareDB. Step iii: After that It displayed in RecPref using a drop-down screen as displayed in Figure 4, Step iv: After performing step iii CareDB returns the personalized query answers that are displayed on an embedded Google Maps interface.
- 12. References: • CareDB: A Context and Preference-Aware Location-Based Database System∗ Justin J. Levandoski Mohamed F. Mokbel Mohamed E. Khalefa • Context-Aware Pervasive Systems - SENG LOKE
- 13. THANK YOU