The objective of this work is to propose a robust watermarking method as watermarking techniques are widely used today for preventing image altering and duplication. With the growth of image-based IoT applications nowadays, the need for developing robust digital watermarking techniques is of high demand. In this work, a robust yet highly perceptible watermarking scheme is proposed. The proposed scheme is based on the Contourlet Transform (CT) and Singular Value Decomposition (SVD) as the embedding domain in which the high-frequency components are chosen for embedding. The frequency domain is selected in order to make the watermarking scheme resists image attacks as the watermark is spreaded across different frequency bands in the cover image and hence the possibility of altering all the embedded bands is not possible as it will results in destroying the cover image. On the other hand, the Arnold transformation was used to insure secure IOT communication where the Arnold transform is applied to the binary logo watermark before embedding for a more secure design. In this context, the host image has been decomposed into the first level of contourlet transform and the highest frequency sub-bands are selected for embedding after performing the SVD on those bands where the SVD matrix is chosen to be the embedding domain. Moreover, This work aims to resist the cropping attack on images where PSNR values were above 52 dB and NC values ranged from 0.8 to 0.9 under various types of cropping attacks. In addition, the proposed method demonstrates its ability to resist various geometric and noise attacks such as JPEG compression, histogram equalization, gaussian noising and image brightening. Comparisons with state-of-the-art work demonstrate the proposed scheme's efficienc

A need for a prosthetic hand device has arisen based on the fact that many people lose one of their upper limbs for various reasons. Many systems are available to control prosthetic hands, such as electromyography (EMG) and mechanomyography (MMG). These systems present many problems, including complexity, high cost, and other issues. Voice commands are among the solutions recommended to address these issues. The proliferation of the Internet, voice recognition technology built into mobile phones, and Internet of Things (IoT) technology has facilitated the use of voice commands to operate prosthetic devices. In this paper, robotic prosthetics were controlled using this technology in the context of five different movement classes. This study involved five participants and reports as accuracy rate of 97%.