The challenge for pervasive system developers here is to detect the user intention so as to remove any ambiguity in the user’s expression of a pervasive action. Understanding user intentions can be achieved by detecting the user status and the environment status. The attention data and context data thus obtained can be connected to give us the intention data. The user intention data can be helpful in enabling PCE to provide pro-active and situation-specific user support.

1. UNDERSTANDING USER INTENTIONS
IN
PERVASIVE COMPUTING ENVIRONMENT
Karthikeyan
M.E., (Pervasive Computing
Technologies)

2. OBJECTIVE
 To understand the user intentions in Pervasive
Computing Environment (PCE)
 To provide pro-active and situation-specific services
based on the understood user intention

3. ABSTRACT
 Conventional systems are being replaced by
pervasive systems world over
 Pervasive systems contain intuitive interfaces
 To develop a successful pervasive system,
understanding user intentions has become vital
 User Intention knowledge helps us in providing
appropriate services to the user

4. INTRODUCTION
 Pervasive Computing: Embedding microprocessors
invisibly in everyday objects to make them
communicate information
 PCE features systems that blend with the human
environment
 Pervasive systems do not have separate input
interfaces
 The environment intuitively gathers input from normal
user actions

5. INTRODUCTION
 Understanding User Intention (UI) becomes the key
 UI knowledge removes any ambiguity in the user’s
expression of a pervasive action
 It can help in providing apt services in quick time
 UI can be detected from knowing either of the user
status or environment status information

6. EXISTING SYSTEM
 Most existing systems focus only on environment
status information
 Less accurate in detecting UI
 Only limited intention triggered services are supported

7. PROPOSED SYSTEM
 Gathers both the environment status and user
status information
 More accurate in detecting UI
 Supports a wide variety of intention triggered
services

8. STEPS IN DEVELOPED SYSTEM

9. CONTEXT DATA ACQUISITION
 Context Information
- used to characterize the environment of a person, place, or
object
 Context Awareness - computers sensing and reacting to
users based on their environment status
 Context Aware Systems - systems that are able to
acquire context data,
understand the context &
trigger actions based on context
 e.g.:- A mobile with inbuilt GPS sensors providing automatic call divert
facility
for the user in travel

10. ATTENTION DATA ACQUISITION
 Information Overload
- information systems providing us with too much data
than what we can process
 Attention Awareness - computers sensing and reacting
to user behaviors based on their attention status
 Attention aware systems
- cognitive systems that select the information we
process
- systems that can support the human attention
processes

11. USER INTENTION DETECTION
 Detected by connecting context data and attention data
appropriately to UI
 Based on the UI detected, a pro-active service is
selected
 Pro-active service is delivered

12. IMPLEMENTATION
 An Android mobile application can be developed using
Android Development Toolkit (ADT) in Eclipse IDE
 The application makes use of the Location Manager Class
in Android
 The Emulator Control or the Telnet Console can be use d to
simulate real time GPS sensor readings in the emulator
 Analysis of these simulated readings gives us attention and
context data

13. IMPLEMENTATION
 The user intention is detected from the attention data and
context data
 Application finds out whether an user is driving or travelling
using changes in GPS Sensor readings
 Automatically blocks the incoming calls while the mobile
user is driving
 Otherwise calls are allowed as usual

14. CONCLUSION
 Intention-aware systems combine the strengths of attention-
aware systems and context-aware systems
 Enable pro-active and situation-specific support to the users
 User satisfaction, service appropriateness and performance
level in PCE can be enhanced
 Many useful applications and systems can be developed on
the same lines

15. REFERENCES
 Anind Dey. K., and Gregory Abowd D.,
“Towards a better understanding of context and context awareness,”
1st International Symposium on Handheld and Ubiquitous Computing,
1999
 Myunggwon Hwang, Pankoo Kim, and Dongjin Choi, “Information
Retrieval Techniques to Grasp User Intention in Pervasive Computing
Environment,”
Fifth International Conference on Innovative Mobile and Internet
Services in Ubiquitous Computing, 2001
 Benedikt Schmidt, Todor Stoitsev, and Max Muhlhauser, “Task Models
for Intention-Aware Systems,” in Journal of Universal Computer Science,
June 2011.
 Claudia Roda, and Julie Thomas, “Attention aware systems: Theories,
applications, and research agenda,” in Computers in Human Behavior,
July 2006.
 http://code.google.com/p/openintents/wiki/SensorSimulator

16. THANK YOU