ABSTRACT

OBJECTIVES

METHODS

RESULTS AND DISCUSSIONS

CONCLUSIONS

REFERENCES

iLukBA provided a solution for determining indoor symbolic (hierarchical) user location for mobile user. It works with small mobile devices such as PDAs and it is combined with the speech recognition systems on how the environment response delivered using speech recognition based on user location. It has been developed using an advanced and robust algorithm in determining user location for indoor environment which offers location precision accuracy less than a meter. iLukBA is capable to handle the unpredictability of IEEE 802.11 (WiFi) signals across perturbations in space, and in time (diurnally) by considering not only the use of WiFi’s signal strength but also WiFi’s signal quality and WiFi’s noise. iLukBA also provides direct service delivery when a user is on the move from one location to another. The environment response in delivering service is based on the speed of user. Dynamic buffer is created, the buffer size depends on the speed of the user. The faster a user moves, the smaller the buffer in delivering the speech. iLukba is proof of a concept with a low cost smart environment capability, i.e. indoor user location can be

[1] Mantoro, T., M. A. Ayu (2008). “Toward the Recognition of User Activity Based on User Location

in Ubiquitous Computing Environments”. The International Journal of Computer Science and Security, ISSN: 1985-1533, Volume 2, Issue 3. [2] Mantoro, T., W. Usino, Andriansyah (2008). “CULo: Coordinates User Location System for Indoor

Localisation”. The ISAST Transactions Journals on Communications and Networking, ISSN 1797-0989, No. 1, Vol. 2, pp 1-7. [3] Mantoro, T., M. Azizan, S. Khairuzzaman, M. A. Ayu, (2009) Multi-observers Instance-Based

Learning Approach for Indoor Symbolic User Location Determination Using IEEE 802.11

Signals,The IEEE - Symposium on Industrial Electronics and Applications (ISIEA), Kuala Lumpur.[4] Mantoro, T., C. W. Johnson (2005). “ηk-Nearest Neighbour algorithm for Estimation of

Symbolic User Location in Pervasive Computing Environments”. Proceedings of the IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), Taormina, Italy.[5] Mantoro, T., and C. W. Johnson (2003). “Location History in a Low-cost Context Awareness

Environment”, Australian Computer Science Communications, Vol. 25, No. 6, Adelaide, Australia.

• iLukBA intends to change computing paradigms: providing service directly to where the user is located. The current paradigm is delivering service without knowing the user location and the new paradigm is delivering the service directly to current user location. • The content of service delivery can be in the form of sound/speech, image/graphics (such as jpg or video) or text based (email, news, micro-blog, etc.). • The service delivery for this prototype is using scenario “where is” and “tell him” approach using speech recognition based on indoor user location.

CLOSEST RELEVANT WORK REFERENCES[1] Bahl, P. and V. N. Padmanabhan (2000). “Radar: An in-building RF-based user location and

tracking system.” Proceedings of the IEEE Infocom 2000, Vol. 2. pp. 775-784.[2] Graumann, D., Lara, W., Hightower, J., Borriello, G. (2003) Real-World Implementation of the

Location Stack: The Universal Location Framework. In Proceedings of the 5th IEEE Workshop on Mobile Computing Systems & Application (WMCSA 2003), pp. 122-128.

• To provide a real-practical solution in determining indoor user location using WiFi signals, since the signals fluctuate up to 33% in 12-hour observations• To provide a capability for smart environment to deliver a service, while the user is on the move, based on user speed, user location and location resolution on mobile devices• To provide a proof of a concept that the combination techniques, indoor user location and speech recognition, are workable in our low cost smart environment

‘Enhancing Quality Research and Innovation for Societal Development’IIUM Research, Invention and Innovation Exhibition 2010

DR. TEDDY MANTORO, AMIR BOROVACIntelligent Environtment Research Group (INTEG), Department of Computer Science, Kulliyyah of Information and Communication Technology,

International Islamic University Malaysia, P. O. Box 10, 50728, Kuala Lumpur, Malaysia

iLukBA Architecture: MyLoCA + SpeechCA

MyLoCA client-server: Web Service Delivery Based

on User Location

SpeechCA: Speech Recognition Service Delivery

Based on User Location

User Location Environment Response

Pull (WiFi)

MyLoCA SpeechCA

Symbolicindoor user-locationa

Linux:/MyLoCA/scanWiFi

/MyLoCA/WiFisignals/MyLoCA/userlocation

Windows:/SpeechCA/wisx.java /SpeechCA/record.java/SpeechCA/tellhim.java

Push (Bluetooth)“Where is” “Tell him”

Mobile User 1 Mobile User 2 Mobile User n

Small devices with WiFi,

Bluetooth or GSM enable

Patent filling in process: “iLukBa: Indoor hybrid user location method and environment response using voice for Smart Environment”, processing through Trademark2u Sdn Bhd., 10 July 2009.

PATENT PROCESSING