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