Rademics Research Institute

Abstract

The rapid advancement of industrial automation and the Industrial Internet of Things (IIoT) has created an urgent need for reliable, self-sustaining power solutions that eliminate the dependency on conventional wired or battery-operated energy sources. Energy harvesting from ambient sources has emerged as a transformative approach to powering IoT-enabled power electronic systems in industrial environments. This book chapter explores cutting-edge techniques for energy harvesting from multiple ambient sources, including mechanical vibrations, thermal gradients, solar radiation, and radiofrequency energy, to develop self-powered industrial systems. A comprehensive analysis of hybrid transduction mechanisms, advanced materials for durability in harsh environments, and AI-driven power management strategies was presented to enhance energy conversion efficiency and system reliability. The integration of energy harvesting with IIoT networks for predictive maintenance and asset health monitoring was examined, demonstrating its potential to optimize industrial operations. Challenges related to long-term performance degradation, environmental sustainability, and scalability are discussed, along with emerging solutions for enhancing energy harvesting efficiency. The insights presented in this chapter provide a foundation for developing resilient and intelligent industrial automation systems that operate autonomously, reducing energy costs and promoting sustainability.

Introduction

The advancement of IIoT technologies has significantly transformed industrial automation by enabling intelligent monitoring, real-time analytics, and predictive maintenance [1]. The widespread deployment of IIoT-enabled power electronic systems was often constrained by power limitations, particularly in large-scale industrial environments where wired power infrastructure was impractical, and battery maintenance poses logistical challenges [2-4]. Energy harvesting from ambient sources has emerged as a sustainable and reliable solution to overcome these limitations, providing self-powered alternatives that enhance the operational efficiency and longevity of industrial automation systems [5]. By capturing energy from environmental sources such as mechanical vibrations, thermal gradients, solar radiation, and electromagnetic waves, energy harvesting enables continuous and maintenance-free operation of industrial IoT devices, reducing dependency on traditional energy sources [6].

Hybrid transduction mechanisms that integrate multiple energy conversion techniques have gained prominence in industrial energy harvesting applications. The combination of piezoelectric, thermoelectric, photovoltaic, and electromagnetic transduction systems enables efficient energy capture from diverse industrial environments, ensuring stable power generation under varying operational conditions [7]. Hybrid energy harvesters can adapt to dynamic energy availability by switching between different energy sources or simultaneously utilizing multiple transduction mechanisms to optimize power output [8]. The integration of power conditioning circuits and energy storage solutions, such as supercapacitors and high-efficiency batteries, further enhances the reliability of self-powered industrial IoT networks, ensuring continuous energy supply for critical operations [9-11]. The development of smart power management algorithms also plays a key role in optimizing energy utilization, allowing IIoT devices to adjust power consumption dynamically based on available harvested energy.