Multimedia applications use image encryption algorithms extensively to safeguard and authenticate digital images. This paper presents an RGB image encryption method, which uses Chaos, DNA, pixel sum, and modified Arnold transform. The suggested algorithm is validated to be robust and resistant to visual, statistical, differential, and brute-force attacks. Additionally, the resulting encrypted images pass all tests of the NIST SP 800-22 test suite. © 2023 IEEE.

Harvesting the energy from environmental sources is a promising solution for perpetual and continuous operation of biomedical wearable devices. Although the energy harvesting technology ensures the availability of energy source, yet power management is crucial to ensure prolonged and stable operation under a stringent power budget. Thus, power-aware task scheduling can play a key role in minimizing energy consumption to improve system durability while maintaining device functionality. This chapter proposes a novel biosensor task scheduling of energy harvesting-based biomedical wearable devices

In smart metering applications, transferring and collecting data within delay constraints is crucial. IoT devices are usually resource-constrained and need reliable and energy-efficient routing protocol. Furthermore, meters deployed in lossy networks often lead to packet loss and congestion. In smart grid communication, low latency and low energy consumption are usually the main system targets. Considering these constraints, we propose an enhancement in RPL to ensure link reliability as well as low latency. We refer to the proposed new additive composite metric as Delay-Aware RPL (DA-RPL)

Protecting transmitted multimedia data such as images is a significant concern. This work proposes an encryption algorithm for greyscale images using a Pseudo-Random Number Generator (PRNG), DNA coding, and pixel sum. The proposed approach is implemented on a Genesys 2 FPGA using minimal hardware resources and can operate at a maximum frequency of 110.8 MHz. In addition, several performance evaluation tests are conducted for multiple images, including statistical analysis of the encrypted image, keyspace analysis, and differential attack analysis. The system is compared to recent works with

Water contamination with paints causes a colour agent to the water that negatively affects the environment, organisms, and humans. Different physicochemical processes are applied for wastewater treatment; however, they have many drawbacks such as high cost, generating toxic waste, and non-effective at low concentrations. Adsorption is considered a promising technique for pollutant removal from polluted wastewater. Commercial activated carbon, nano-materials, and natural biological materials are used as adsorbents in adsorption. This chapter focuses on discussing the adsorption process, the

Power management and energy conservation are crucial for medical wearable devices that rely on energy harvesting. These devices operate under strict power budgets and require prolonged and stable operation. To achieve this, Energy-aware task scheduling is proposed as a solution to minimize energy consumption while ensuring the continued operational capabilities of the device. our paper presents a task scheduling method using the Flower Pollination Algorithm (FPA). The proposed task scheduling focuses on managing the activity of key components such as the heart rate sensor, temperature sensor

Due to a wide range of applications in the biomedical industry, the need for flexible and wearable sensors is growing every day. A pressure sensor generates a signal based on the applied pressure. Sensors have become an integral component of our daily lives, from personal gadgets to industrial machinery. The identification of the low signal from the body necessitates the use of particularly sensitive sensors. The development of a pressure sensor that can transform the maximum input signal into an electrical output is critical. In this paper, zig-zag piezoresistors on a square diaphragm were

Digital Image Processing (DIP) is a growing field for various applications, such as autonomous vehicles and video surveillance. To improve the performance of DIP systems, image processing algorithms are implemented in hardware rather than software. The idea here is primarily to get a faster system than software imaging or other alternative hardware. Field-programmable gate arrays (FPGAs) have the advantages of parallel processing, low cost, and low power consumption. These semiconductor devices contain many logic blocks that can be programmed to perform everything from basic digital gate-level

This paper introduces an efficient prediction algorithm tailored for advanced and high efficiency video coding, encompassing both H.264 and H.265. The proposed approach aims at replacing the standard intra prediction methodology by employing a streamlined prediction mode, which significantly reduces computational overhead and system complexity while eliminating the requirement for mode decision. By leveraging block comparison criteria, the designed method combines neighboring blocks in a linear fashion to accurately represent the target block. Extensive comparisons are conducted with the H.264

Light trapping as a result of embedding plasmonic nanoparticles (NPs) into photovoltaics (PVs) has been recently used to achieve better optical performance compared to conventional PVs. This light trapping technique enhances the efficiency of PVs by confining incident light into hot-spot field regions around NPs, which have higher absorption, and thus more enhancement of the photocurrent. This research aims to study the impact of embedding metallic pyramidal-shaped NPs inside the PV’s active region to enhance the efficiency of plasmonic silicon PVs. The optical properties of pyramidal-shaped