In order to help physically disabled persons to make their life independent, this paper proposes an autonomous eye controlled system (AECS) on wheelchairs. In this work, several OpenCV image processing algorithms are employed to track the eye motion to coordinate the wheelchair moving left, right, and straight forward. We use the Raspberry-Pi B+ board as the system center to process the images and control the motors via GPIO. Experimental results show that the ACES system can be effectively used in the prototype, and outperforms the hand gesture controlled system by 25% processing latency reduction. General TermsComputer engineering, embedded system design

As Internet of things (IoT) advances, the growth in data volume from wireless sensor networks (WSNs) is explosive and is likely to overwhelm traditional datacenters. Therefore this paper presents a field-programmable gate array (FPGA) design and simulation on a data compression algorithm as a case study. By collecting and compressing raw data from IoT network, the large amount of sensor data is dramatically reduced and translated into valuable information to the servers. Simulation results show that the compression ratio can reach 30.08% with a very low processing latency (20 ms for compressing 1 KB sensor data).