Energy Harvesting Systems for the Internet of Things with Applications to Smart Agriculture

Abstract

The Internet of Things is the interconnection of everyday objects to the web, with the purpose of exchanging information to enable smarter actions and potentially make a process more efficient. However, how power is provided and stored in remote sensing applications is still one of the main modern electronics challenges of such technology and can become one of the main constraints to prevent its mass adoption. Energy Harvesting is an emerging technology that can transform energy in the environment into usable energy, among such environmental energy are electromagnetic waves, thermal, solar, kinesthetic transducers, fuel cells, to name a few. Because this technology makes use of the available ambient energy, it has the potential to increase the power readiness for battery-operated electronics and more importantly, it can become the technology that fully powers the next generation of internet-enabled agricultural solutions. This dissertation centers around the design and development of high-efficient power management systems for AC and DC energy harvesting sources. The proposed architectures not only consider circuits, systems and algorithms that make a more efficient power extraction but also focuses on providing inherent sensing functionalities at no extra system complexity, which in turn not only achieves the goal of extending the battery life of proposed smart sensor applications but also proposes new charge extraction methods to permanently power an electronic device. The work presented in this dissertation demonstrates that energy harvesting, and internet of things devices can be implemented in multiple smart agriculture scenarios by proposing algorithms, circuits and systems capable of performing energy harvesting operations while providing reliable data to the end user. The analysis of the design of such proof-of-concept prototypes are provided in this dissertation along with its implementation and testing. The first part of this dissertation proposes novel algorithms for maximum power extraction and new power measurement techniques. The second part focuses on front-end circuits for AC energy harvesting sources and circuits that can provide sensing capabilities along with energy harvesting operations.