Synergizing AI, Machine Learning, Optoelectronics, and Computational Tools for Sustainable Wireless Communication Systems

Aug 3, 2026

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Sustainable wireless communication systems demand energy-efficient, high-performance technologies to meet escalating global data and reliability needs. This paper investigates integrating artificial intelligence (AI), machine learning (ML), optoelectronics, and computational tools to strengthen system design and optimization. AI and ML enable predictive analytics and dynamic adaptation for proactive resource allocation, while optoelectronics supports high-speed, low-power transmission with reduced signal degradation. Computational tools further support modeling, simulation, evaluation, and optimization, enabling scalable, reliable solutions aligned with performance and environmental goals through a comprehensive framework.

LanguageEnglish

CategoryResearch & Report

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Pages13

Reading Time33 min

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Introduction

AI and machine learning-driven optimization

Optoelectronics and computational tools for sustainable systems

Synergizing AI, Machine Learning, Optoelectronics, and Computational Tools for Sustainable Wireless Communication Systems SEEJPH Volume XXVI, S1,2025, ISSN: 2197-5248; Posted:05-01-25 Synergizing AI, Machine Learning, Optoelectronics, and Computational Tools for Sustainable Wireless Communication Systems Naeema Nazar 1*, Divya Nair 2, Krishnendu P S 3, Pimmy Mathews 4, and Dr. Saju A 5 1*Assistant Professor, Department of Electronics and Communication Engineering, VISAT Engineering College, Ernakulam, Kerala, India; Research Scholar, Department of Electronics and Communication Engineering, Indian Institute of Information Technology, Kottayam, Kerala, India 2Head of Department, Department of Computer Science and Engineering, VISAT Engineering College, Ernakulam, Kerala, India 3Assistant Professor, Department of Computer Science and Engineering, VISAT Engineering College, Ernakulam, Kerala, India 4Assistant Professor, Department of Computer Science and Engineering, VISAT Engineering College, Ernakulam, Kerala, India 5Associate Professor, Department of Electronics and Communication Engineering, Albertian Institute of Science and Technology, Ernakulam, Kerala, India Corresponding author: Naeema Nazar1* ; Email: [naeemanazarcn@gmail.com](naeemanazarcn@gmail.com) | KEYWORDS | ABSTRACT | | --- | --- | | Wireless | The need for sustainable wireless communication systems has become increasingly | | Communication, | critical in the face of growing global demand for energy-efficient and high- | | Sustainability, | performance tech- nologies. This paper examines the integration of artificial | | Artificial | intelligence (AI), machine learning, optoelectronics, and computational tools to | | Intelligence, | enhance the design and optimization of such systems. AI and machine learning | | Machine | techniques offer powerful methods for optimizing system performance through | | Learning, | predictive analytics and dynamic adaptation. Optoelectronic technologies, with | | Optoelectronics, | their ability to enable high-speed, low-power data transmission, play a key role in | | Computational | addressing the limitations of conventional electronics. Additionally, computational | | Tools, Energy | tools are essential for modeling, simulation, and optimization, allowing for precise | | Efficiency, | evaluation of complex communication networks. By leveraging the combined | | System | potential of these technologies, the paper demonstrates how sustainable wireless | | Optimization, | communication systems can be developed to meet both performance and | | Data | environmental goals. The proposed framework outlines a comprehensive approach | | Transmission, | to achieving energy-efficient, scalable, and reliable communication solutions for | | Network Simulation | the future. | I. INTRODUCTION: The rapid evolution of wireless communication systems has significantly transformed modern society, enabling seamless connectivity and driving innovation across various sectors. However, as the demand for higher data rates, increased reliability, and broader coverage continues to grow, traditional communication technologies face substantial challenges, particularly in terms of energy consumption, network congestion, and sustainability [2] . Addressing these challenges requires an integrated approach that leverages emerging technologies to optimize both performance and environmental impact. This paper explores the synergistic potential of artificial intelligence (AI), machine learning, optoelectronics, and computational tools Synergizing AI, Machine Learning, Optoelectronics, and Computational Tools for Sustainable Wireless Communication Systems SEEJPH Volume XXVI, S1,2025, ISSN: 2197-5248; Posted:05-01-25 in enhancing wireless communication systems for a sustainable future [3][12] . Artificial intelligence and machine learning play a pivotal role in improving the efficiency and adaptability of wireless communication systems. Th

FAQs

How do AI and machine learning contribute to optimizing wireless communication systems?

AI and ML use predictive analytics and data-driven decision-making to forecast network conditions and demand, enabling real-time adaptation, proactive resource allocation, and improved efficiency.

Why are optoelectronic technologies important for sustainable wireless communication?

Optoelectronics supports light-based data transmission with high data rates and lower energy requirements, helping reduce signal degradation and enabling low-power, high-speed wireless networks.

What role do computational tools play in the proposed framework?

Computational tools enable modeling, simulation, and optimization, allowing precise evaluation of complex communication networks to design scalable, reliable, energy-efficient solutions.

Aug 3, 2026

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