An Intelligent Expert System for Proactive Services Deploying Ubiquitous Computing Technologies IEEE 2005 Proceedings of the 38th Hawaii International Conference on System Sciences – IEEE BIO Lab. Mikyung Jo

1 Contents  1. Introduction  2. Related Research  3. ubiES  4. Prototype Implementation  5. Concluding remarks

2 Why?  Expert systems : generate feasible alternatives in automated manner.  Users : decisions proactively and intelligently by automatically detecting the users’ various context data.  Conventional expert systems seldom automatically refer to context data  Propose : CKDDM (Context-Knowledge- Dialogue-Data-Model).

3 Introduction  conventional Ess : when users complete all required information using dialogue-based sub- modules.  Hence, this paper describes how the problem- solving capability and context-aware computing are jointly used to establish ubiquitous computing technology-based ESs by resolving conventional ESs’ limits.  A framework of ubiES is addressed, including descriptions of the internal subsystems.

4 ISs for proactive services  DSSs were designed to automatically generate decisions based on users’ context.  Rasmy et al. (2002)-solving multi-objective decision  Muller et al. (2001)-hospital information systems (HISs), seamlessly

5 User assistance via ubiquitous computingtechnology  automatically sensing users’ various context data and smartly generating proper results.  Virtual Tour Guide - “stick-e notes”  When a user enters the area delimited by the GPS coordinates, a short note is displayed on the user’s device (Brown et al., 1997).  As a user with an enabled device moves through t he physical space, the device displays Web page s that are associated to the physical locations or o bjects (Kindberg, et al., 2000).-URL

6 Context-aware computing  Device : environmental, temperature, climate, location, time  Olivetti, Lab’s “Active Badge” (1992) start : location-awareness appliances start : location-awareness appliances  Location - GPS, RFID, Access Points  Context can be indexed by the unique pattern of agent.- sending , or browsing specific WWW pages (Prekop and Burnett, 2003)

7 Context-aware computing

8 Notion of ubiES

9  Embeddedness  Embeddedness : connected to the fixed and/or wireless network.  Mobility  Mobility : mobile and flexible network infrastructure.  Nomadicity  Nomadicity : computing, communication capabilities, services to nomads, integrated

10 Notion of ubiES  Proactive  Proactive : needs to be self-triggered to capture a priori  Invisibility  Invisibility : to be as unobtrusive as possible, enable the user to put as little data as possible.  Portability  Portability : hands-free or at least one- handed light devices.

11 Notion of ubiES

12 Notion of ubiES  three levels of services (Barkhuus and Dey, 2003). 1) Personalization 2) Passive context-aware 3) Active context-aware services

13 Notion of ubiES  Personalization - “pull” (Chevist et al., 2001)  when users want to find nearby restaurants that fit their particular preferences, users can select their cuisine preferences and their location at that time into the device  This provides better recommendations than recommendations with no context because the system has the location data.

14 Notion of ubiES  Passive context-aware- “pull” automatically captures the user’s context from the federated sensors.  automatically captures the user’s context from the federated sensors.  when a user clicks a menu in the interface, the service displays some recommendations about the restaurants.

15 Notion of ubiES  Active context-aware services -“push”  Active context-aware services - “push”  the user does not need to initiate any actions to start the service, nor is there a need to manually input personal or contextual data.  “proactive” (Brown and Jones, 2001).

16 Notion of ubiES

17 ubiES framework contextual data  ubiES acquires contextual data, as well as data from a conventional database context subsystem  added context subsystem to complement conventional ES components services  In the ubiES, identified as services.

18 ubiES framework

19 Prototype Overalls

20 Prototype Overalls  User ontology, product ontology, and service ontology are implemented with DAML+OIL, based on XML.  The ontology is accessed and interpreted with Jena API.  Agents are implemented with JATLite running on JDK version  Communication between the UA and the client is expressed with Java Servlet Pages (JSP).

21 Example Service

22 Example Service

23 Concluding remarks  Business problem-solving or decision-making is a good application area that can be benefited from ubiquitous computing technology because managers and employees are always surrounded by context when performing tasks to achieve their own goals.  Contingency theory has successfully proved that the fitness of person, task and context is a main determinant to increase individual, and/or group performance under turmoil task environment.  Fully making use of context subsystem would increase the usability and hence solution quality of ES.