RETRACTED: Visual sensor intelligent module based image transmission in industrial manufacturing for monitoring and manipulation problems (Retracted article. See DEC, 2022) - Alhayani, Bilal S. A.; Ilhan, Haci (SPRINGER, 2021)
Due to technology advancement, smart visual sensing required in terms of data transfer capacity, energy-efficiency, security, and computational-efficiency. The high-quality image transmission in visual sensor networks (VSNs) consumes more space, energy, transmission delay which may experience the various security threats. Image compression is a key phase of visual sensing systems that needs to be effective. This motivates us to propose a fast and efficient intelligent image transmission module to achieve the energy-efficiency, minimum delay, and bandwidth utilization. Compressive sensing (CS) introduced to speedily compressed the image to reduces the consumption of energy, time minimization, and efficient bandwidth utilization. However, CS cannot achieve security against the different kinds of threats. Several methods introduced since the last decade to address the security challenges in the CS domain, but efficiency is a key requirement considering the intelligent manufacturing of VSNs. Furthermore, the random variables selected for the CS having the problem of recovering the image quality due to the accumulation of noise. Thus concerning the above challenges, this paper introduced a novel one-way image transmission module in multiple input multiple output that provides secure and energy-efficient with the CS model. The secured transmission in the CS domain proposed using the security matrix which is called a compressed secured matrix and perfect reconstruction with the random matrix measurement in the CS. Experimental results outwards that the intelligent module provides energy-efficient, secured transmission with low computational time as well as a reduced bit error rate.
Keywords: Intelligent module smart system; Data transmission; Data compression intelligent sensor; Visual sensing automation; Coding; Regression; INTERNET; Computer Science; Engineering