Wireless sensor networks (WSNs) are an advanced solution for data collection in Internet of Things (IoT) applications and remote and harsh environments. These networks rely on a collection of distributed sensors equipped with wireless communication capabilities to collect low-cost and small-scale data. WSNs face numerous challenges, including network congestion, slow speeds, high energy consumption, and a short network lifetime due to their need for a constant and stable power supply. Therefore, improving the energy efficiency of sensor nodes through solar energy harvesting (SEH) would be the best option for charging batteries to avoid excessive energy consumption and battery replacement. In this context, modern wireless communication technologies, such as Wi-Fi and Li-Fi, emerge as promising solutions. Wi-Fi provides internet connectivity via radio frequencies (RF), making it suitable for use in open environments. Li-Fi, on the other hand, relies on data transmission via light, offering higher speeds and better energy efficiency, making it ideal for indoor applications requiring fast and reliable data transmission. This paper aims to integrate Wi-Fi and Li-Fi technologies into the SEH-WSN architecture to improve performance and efficiency when used in all applications. To achieve reliable, efficient, and high-speed bidirectional communication for multiple devices, the paper utilizes a Markov model, sleep scheduling, and smart switching algorithms to reduce power consumption, increase signal-to-noise ratio (SNR) and throughput, and reduce bit error rate (BER) and latency by controlling the technology and power supply used appropriately for the mode, sleep, and active states of nodes.

The resource limitations of Low-Power Wireless Networks (LP-WNs), such as Wireless Sensor Networks (WSNs), Wireless Actuator/Sensor Networks (WA/SNs), and Internet of Things (IoT) outdoor applications, restrict the utilization of the error-performance-enhancing techniques and the use of the powerful and robust security tools. Therefore, these LP-WN applications require special techniques to satisfy the requirements of a low data loss rate and satisfy the security requirements while considering the accepted level of complexity and power efficiency of these techniques. This paper focuses on proposing a power-efficient, robust cryptographic algorithm for the WA/SNs. The lower-complexity cryptographic algorithm is proposed, based on merging the data composition tools utilizing data transforms and chaos mapping techniques. The decomposing tool is performed by the various data transforms: Discrete Cosine Transform (DCT), Discrete Cosine Wavelet (DWT), Fast Fourier Transform (FFT), and Walsh Hadamard Transform (WHT); the DWT performs better with efficient complexity. It is utilized to separate the plaintext into the main portion and side information portions to reduce more than 50% of complexity. The main plaintext portion is ciphered in the series of cryptography to reduce the complexity and increase the security capabilities of the proposed algorithm by two chaos mappings. The process of reduction saves complexity and is employed to feed the series of chaos cryptography without increasing the complexity. The two chaos mappings are used, and two-dimensional (2D) chaos logistic maps are used due to their high sensitivity to noise and attacks. The chaos 2D baker map is utilized due to its high secret key managing flexibility and high sensitivity to initial conditions and plaintext dimensions. Several computer experiments are demonstrated to evaluate the robustness, reliability, and applicability of the proposed complexity-efficient crypto-system algorithm in the presence of various attacks. The results prove the high suitability of the proposed lower-complexity crypto-system for WASN and LP-WN applications due to its robustness in the presence of attacks and its power efficiency.

The inverter's simplicity is an important aspect that must be considered especially for electronic devices, as adding the number of power switches increases the complexity and overall cost of the inverter. This work proposes an inverter design that converts DC into AC power. It receives 12 VDC as an input voltage, and it is composed of a boost converter that converts an input voltage of 5-20 VDC to an output voltage of 4-30 VDC and a pulse width modulation controller to produce a square wave with a frequency of 100 kHz to drive the switching MOSFET. The designed inverter can be operated on different loads ranging from 50 Ω to 1000 Ω, tested in both simulations and experimentally. The design was optimized by the LT Spice simulator. The proposed inverter has operating frequencies ranging from 40 kHz to 110 kHz, taking into account different loads. The obtained results showed that both simulation and experimental results converged, whereas the highest efficiency was 96.96% at 55 kHz at a fixed load of 100 Ω. On the other hand, the maximum achieved efficiency when the load was sweeping was 80% at a load of 50 Ω at a fixed frequency of 100 kHz.

In this research, we investigate the segregation of Gaussian light beam wavelengths using corrugated triangular wave-index interfaces with the beam propagation method (BPM). We present a novel approach for optical wavelength demultiplexing (DEMUX) utilizing the Goos-Haenchen (GH) shift and continuous refraction at the interface. By exploiting wavelength-dependent lateral shifts (GH shifts), reflected beams achieve spatial beam separation. Light beams exhibit distinctive "turning points" in the medium, resulting in spatially separated "back-refracted" beams. Meta-heuristics were employed to optimize operational parameters for this demultiplexing optical splitter, enabling its application in "corrugated triangular wave-index integrated-optics" structures within optical fiber networks. Artificial Intelligence (AI) in conjunction with an Ant Colony (AC) was utilized for optimal beam incidence. Findings suggest improved demultiplexer performance with three media compared to two media for 2 and multi-wavelength demultiplexing, highlighting a significant academic contribution of this study.