Promoting energy efficiency and longevity in energy neutral sensor systems
Creators: name: Jackson, Greg
Publisher: name: Imperial College London
Year: 2019

description: A convergence of technologies has created the notion of the Internet of Things (IoT) to rev- revolutionize areas such as home automation, environmental monitoring, hazard detection and industrial IoT applications. A major barrier to the pervasive deployment of IoT technologies is the availability of energy. Cisco predicts that there will be 50 billion devices by 2020 [1], powering this number of sensors on primary batteries creates a momentous task when they need to be replaced and there is also the subsequent environmental concerns of battery disposal. The need for a deploy and forget IoT solution has driven research into energy in Wireless Sensor Networks (WSN) over the past decade. The current state of the art, Energy Neutral Operation (ENO), utilizes techniques such as sample rate control, adaptive duty cycling and data reduction methods to balance energy generation, storage and consumption. However, despite considerable work being undertaken in this field, a systematic literature review undertaken for this thesis has highlighted gaps which remain in the state of the art. From this literature review, three keys questions are highlighted for exploration: • Energy generation, although variable, is not controllable or optimizable in-situ. If ENO WSN could dynamically adjust their energy generation to optimize the energy harvesting methods through actuation, would this produce greater energy for sensor systems? A lightweight distributed energy generation optimization algorithm has been developed for solar tracking which produced an average of 9.2% increase in energy generation across all testing. • Energy consumption in ENO WSN is controlled via adaptive duty cycling. Tasks are scheduled between a predetermined minimum and maximum duty cycle within an individual time-slot to ensure less energy is consumed than is generated. However, this adaptation is done only with consideration of the energy availability and without any knowledge of how the downstream information is used by applications. Could a network disseminate user requirements to nodes to better provision tasks in a network? Would this be more efficient and could this free up energy to be utilized for other tasks? To answer these questions, an application and energy aware tasks scheduler has been created. In particular, the Surplus Energy Task (SET) scheduler improves energy utilization by an average of 21% .Battery Health There is the proposition that WSN can now be deployed and operated in perpetuity with the evolution of energy harvesting methods. However, the nature of energy storage is such that batteries degrade over time to the point they can no longer hold charge. Can ENO WSN systems be made aware of battery degradation in node and then use this information as a parameter to be optimized to promote longevity in ENO WSN systems? In answering this question, methods created resulted in an average of 205.2% improvement in lifetime without a reduction in average performance of a sensor system across different energy harvesting source tests. In this thesis, methods, models, and algorithms are put forth to answer these questions. The themes and methods discussed are of particular interest to researchers in the areas of Internet of Things (IoT), Wireless Sensor Networks (WSN), Cyber-Physical Systems (CPS), Energy Neutral Operation (ENO), and Information and Communications Technology (ICT) for the promotion of sustainability in future cities.