Implementing Artificial Intelligence in Thermoelectric Generators: A Review of Data Science Applications in Enhancing Efficiency and Security
Authors:- Arvind Malhotra, Rohit Bedi
Abstract:- The integration of Artificial Intelligence (AI) into thermoelectric generator (TEG) technologies offers a groundbreaking approach to improving both energy efficiency and cybersecurity within the rapidly evolving Internet of Things (IoT) ecosystems. This review delves into the diverse applications of AI-driven methodologies—including machine learning, big data analytics, and predictive modeling—to enhance the operational performance of TEGs, with a particular focus on systems utilizing advanced thermoelectric materials such as bismuth telluride (Bi2Te3) and lead telluride (PbTe). By conducting an extensive examination of the existing literature, this paper identifies and analyzes key AI techniques that have been instrumental in optimizing energy conversion processes, thereby significantly boosting the efficiency of TEG systems. Moreover, it explores how AI can be leveraged to fortify the security of IoT ecosystems, addressing vulnerabilities and safeguarding interconnected devices against potential cyber threats. The review also discusses the synergistic potential of integrating AI with TEGs to create intelligent, adaptive systems capable of responding dynamically to varying conditions and threats. The findings underscore AI’s pivotal role in not only advancing TEG efficiency and IoT security but also in shaping future research trajectories aimed at overcoming persistent challenges. Ultimately, this review highlights the transformative impact of AI on developing resilient and sustainable energy solutions, emphasizing its importance in meeting the growing demands of modern energy systems and securing digital infrastructure in an increasingly interconnected world.
