• Decrease font size
  • Default font size
  • Increase font size
  • default color
  • color1 color
  • color2 color
  • color3 color

Latest News

  • Sept 2011: Anis Koubaa received his Habilitation degree in Computer Science from the National School of Engineering in Sfax (ENIS).
  • Feb 2011: Maissa Ben Jamâa won the very prestigious Best CONET/EWSN Master Award, in EWSN 2011 conference. She was supervised by Anis Koubaa.

Recent Publications

Nouha Baccour, Anis Koubâa, Luca Mottola, Marco Zuniga, Habib Youssef, Carlo Boano, and Mário Alves “Radio Link Quality Estimation in Wireless Sensor Networks: a Survey”,  ACM Transactions on Sensor Networks, volume 8, issue 4, November 2012. (Impact factor: 2.282)

Nouha Baccour, Anis Koubâa, Maissa Ben Jamâa, Denis do Rosario, Habib Youssef, Mario Alves and Leandro Becker, "RadiaLE: a Framework for Designing and Assessing Link Quality Estimators in Wireless Sensor Networks", Ad Hoc Networks Journal, Elsevier, 2011. (Impact Factor = 1,293, 2009)

Mohsen Rouached, Shafique Chaudhry, Anis Koubaa, "Service-Oriented Architecture Meets LowPANs: a Survey", The International Journal of Ubiquitous Systems and Pervasive Networks (JUSPN), Issue 1, Volume 1, 2011 (to appear).


Next Events

COINS (Cooperative Intelligent Networking Systems) is an International Research Lab currently located at the College of Computer and Information Sciences (CCIS) of Al-Imam Mohamed bin Saud University (IMAMU), Riyadh, Saudi Arabia.
The COINS research group, officially  started in May 2010.
The research group focuses its research activity in the analysis, design and implementation of cooperative and intelligent systems.

Research Areas

  • Wireless Sensor Networks
  • Mobile Robots
  • Forensics in Cloud Computing
  • Real-World Applications





Autonomous Navigation of a Wifibot Robot using Odometery for Obstacle Avoidance

This video shows a Wifibot Lab robot navigating in the corridors of the College of Computer and Information Sciences at Al-Imam Mohamed bin Saud University. It implements a simple odometry based algorithm to avoid obstacles while navigating.

The demo shows that the robot is able to navigate freely without hitting any obstacle and efficiently deviating from approaching obstacles. There is no apriori map embedded in the robot ((blind navigation). This work is done under the R-Track project. For details are available at rtrackp.com

Click here for full video