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October 1, 2025Technologies6 citationsOpen Access

Improving Solar Energy-Harvesting Wireless Sensor Network (SEH-WSN) with Hybrid Li-Fi/Wi-Fi, Integrating Markov Model, Sleep Scheduling, and Smart Switching Algorithms

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HGHeba Allah GamalAEAli M. El‐RifaieAYAhmed A. F. Youssef

Key Points

  • Utilizing a hybrid of Li-Fi and Wi-Fi technologies significantly enhances energy efficiency in sensor nodes.
  • Application of the Markov model contributes to improved communication performance, specifically reducing latency.
  • Implementing sleep scheduling and smart switching algorithms leads to enhanced battery life in wireless sensor networks.
  • This approach could address existing challenges in wireless sensor networks, such as high energy consumption and short network lifetime.

Abstract

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.

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Cite This Study

Gamal et al. (2025) studied this question.

synapsesocial.com/papers/68dd89e6fe798ba2fc498258https://doi.org/10.3390/technologies13100437
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