Conference General Chair: Dr. Mohammad V. Malakooti
· Dr. KEITH ALAN TEAGUE, PhD, PE
Professor and Immediate Past School Head School of Electrical and Computer Engineering Oklahoma State University, Stillwater, Oklahoma USA
· Dr. Arash Taki:
Dr. Arash Taki is currently based in Dubai and manages Respiratory and Patient Monitoring solution and Innovation at Covidien in the region. He is also scientific advisor and lecturer in TUM and Computer/Biomedical Engineering Group at IAU University in Dubai
Wireless sensor networks have enormous potential to change the way we live, work, and play. Compressive sensing is well known as an emergent technique for under-sampling sparse signals and recovering them accurately and efficiently using a much smaller number of compressive sensed measurements than traditional Nyquist methods require.
This talk focuses on data collection in clustered wireless sensor networks employing compressive sensing. A technique consisting of the integration of compressive sensing and clustering in wireless sensor networks utilizing block diagonal measurement matrices will be introduced. The approach partitions a wireless sensor network into clusters, where each cluster head collects the sensor readings within its cluster only once and then generates compressive sensed measurements at each cluster head to be forwarded to the base station where all measurements are collected.
In this talk two methods are considered for forwarding the compressive sensed measurements from cluster heads to the base station: (i) direct transmission and (ii) multi-hop routing through intermediate cluster heads. Additional cluster-based data collection methods will be considered for comparison purposes. For further power saving, the proposed approach exploits the correlation of the sensor readings in the wireless sensor network to reduce the transmission energy cost. Expressions for total power consumption within this framework are formulated and the effects of different spars bases on the compressive sensed performance as well as the optimal number of clusters are discussed for achieving minimum energy consumption.
Total Number of Papers presented: 31
IAU Student papers: 2 Papers
1– Prediction of Stock Market Index based on Neural Networks, Genetic Algorithms, and Data Mining Using SVD
Authors: Dr. Mohammad V. Malakooti (Faculty), Amir AghaSharif (student)
2- A Two Level-Security Model for Cloud Computing based on the Biometric Features and Multi-Level Encryption
Authors: Dr. Mohammad V. Malakooti (Faculty), NilofarMansourzadeh (student)
Host Country: United Arab Emirates
Participating Countries: Austria, Japan, Brazil, Lebanon, Nigeria, Oman, Taiwan, India, Malaysia, Republic of Korea, United Arab Emirates, United States, Serbia, Bahrain, Algeria, Sudan, Islamic Republic of Iran