Hakilo Sabit

    Ph.D Candidate

    Email: hsabit@aut.ac.nz

    Phone: +64 9 921 9999 Ext. 8681

    Mobile: +64 21 0259 5310

Research Objectives

Currently Im working on embedded system design in general and intelligent wireless sensor networks (iWSN) in particular. My favorite research tools and software/hardware include; TI's Z-stack ZigBee protocol, IAR IDE workbench, CC2430/31 development kit, Daintree's sensor network analyzer and OPNET network simulator. My research focus is on energy-efficient intelligent sensors network. Applying AI (artificial intelligence) concepts to WSNs.

Journal Papers

  • Hakilo, A.S., and Rahmat, M.F. (2004). “Flow Regime Identification Using Neural Network- Based Electrodynamic Tomography System”. Jurnal Teknologi, 40(D): pp.109-118.

Conference Papers

  • S. Hakilo, A. Adnan, and G. H. Hosseini, “Distributed WSN Data Stream Mining based on Fuzzy Clustering”, The Sixth International Conference on Ubiquitous Intelligence and Computing, St Lucia, Brisbane, Australia, july 7-9, 2009.(Accepted)
  • Hakilo, A.S., and M.F. Rahmat. (2005). “Flow Regime Identification and Concentration Distribution of Solid Particles Flow in Pipelines using Electrodynamic Tomography and Artificial Neural Networks”. Proc. Of the 9th International Conference on Mechatronics Technology. Kuala Lumpur, Malaysia. December 5-8.
  • Hakilo, A.S., and M.F. Rahmat. (2004). “Use of Artificial Neural Network (ANN) in Electrical Charge Tomography as Flow Regime Identifier of Particulate Flow in Industrial Pipeline”. Proc. of 2nd International Conference on Artificial Intelligence In Engineering and Technology. Kota Kinabalu, Malaysia. August 3-5. pp.2:734-738.
  • Hakilo, A.S., and M.F. Rahmat. (2005). “ Neural Network in Electrodynamic Tomography as Flow Pattern Identifier”. Proc. International Conference on Robotics, Vision, Information and Signal Processing ROVISP2005. Penang, Malaysia. July 20-22. pp.747-751.

Presentations

  • Presentation at Sensor Network & Smart Environment Workshop, 15th Sep2008.
  • Presentation at Sensor Network & Smart Environment Group Seminar, 23rd April, 2008.

Master Research Thesis

  • Flow Regime Identification of Particles Conveying in Pneumatic Pipeline using Electric Charge Tomography and Neural Network Techniques

Tools/Software/Testbed