A wireless imaging system for monitoring strawberry fields provides enough quality image data for computer vision algorithms to make meaningful yield predictions. This report contains a design for a wireless sensor network modified with mesh networking techniques to extend coverage range and a solar energy harvesting system to improve sensor node lifetime. A two hop system with six nodes is implemented in a laboratory environment validating the communication systems integrity over an 800’ range. Moving from a primary battery system to solar energy harvesting increases the module lifetime indefinitely.

Consider a bottom-hinged Oscillating Wave Surge Converter (OWSC): This device oscillates due to the hydrodynamic forces applied on it by the action of ocean waves. The focus of this thesis is to build upon the in-house multi-block generalized coordinate finite volume solver GenIDLEST using a collocated grid arrangement within the framework of the fractional-step method to make it compatible to simulate such systems. The first step in this process is to deploy a convection scheme which differentiates between air and water. This process is further complicated by the 1:1000 density and 1:100 viscosity ratio between the two fluids. For this purpose, a phase field method is chosen for its ease of implementation and proven boundedness and conservativeness properties. Extensive validation and verification using standard test cases, such as droplet in shear flow, Rayleigh Taylor instability, and the Dam Break Problem is carried out. This development is then coupled with the present Immersed Boundary Module which is used to simulate the presence of moving bodies and again verified against test cases, such as the Dam Break problem with a vertical obstacle and heave decay of a partially submerged buoyant cylinder. Finally, a relaxation zone technique is used to generate waves and a numerical beach technique is used to absorb them. These are then used to simulate the Oscillating Surge Wave Converter. / Master of Science / An Oscillating Wave Surge Converter can be best described as a rectangular flap, hinged at the bottom, rotating under the influence of ocean waves from which energy is harvested. The singular aim of this thesis is to model this device using Computational Fluid Dynamics (CFD). More specifically, the aim is to model this dynamic device with the full Navier Stokes Equations, which include inertial forces, arising due to the motion of the fluid, viscous forces which dissipate energy, and body forces such as gravity. This involves three key steps: 1. Modelling the air-water interface using a convection scheme. A phase field method is used to differentiate between the two fluids. This task is made more challenging because of the very large density and viscosity differences between air and water. 2. Model dynamic moving geometries in a time-dependent framework. For this, we rely on the Immersed Boundary Method. 3. Develop a numerical apparatus to generate and absorb ocean waves. For this, we rely on the Relaxation Zone and Numerical Beach Method. These developments are validated in different canonical problems and finally applied to a two-dimensional oscillating surge wave energy converter.

In the current pursuit of sustainable energy, biofuel cells are attracting considerable attention. Within biomedical engineering, the concept of harnessing energy from biological fluids, such as blood, holds significant promise, enabling both full autonomy and miniaturization. In this context, this study aims to identify the most efficient biofuel cells for miniaturised implantable biosensors and design a prototype based on the obtained results. To achieve this goal, a systematic literature review was conducted, comparing biofuel cells based on relevant parameters for powering devices, including power density and operative voltages. This categorization guided material selection, considering a cost-performance trade-off. Carbon nanotubes and Laccase were chosen to facilitate oxygen reduction at the cathode, while carbon nanotubes with Glucose Oxidase (with and without ferrocenemethanol) played a similar role at the anode—where glucose proved to be the most advantageous fuel. Electrode functionalization and assessment involved electrochemical and morphological analyses, culminating in the recording of initial results for the biofuel cell prototype. The analysis of scientific literature revealed that under physiological conditions, including pH, glucose concentration, and single-chamber biofuel cells, the maximum power density obtained was 1 mW/cm$^2$ at 0.65 V. The use of nanomaterials, such as carbon nanotubes, and enzymes proved crucial for achieving this performance by enhancing electron transfer, increasing the effective area, and introducing specificity to each electrode, enabling the biofuel cell to operate without the need for a membrane. During the design phase, the functionalisation of the cathode highlighted the critical role of oxygen, which has a limited concentration in the solution. At the anode, the attempt to achieve mediated electron transfer proved successful, in contrast to the method of direct electron transfer. Finally, the characterisation of the biofuel cell demonstrated a preliminary power generation of 0.38 $\micro$W/cm$^2$ at 0.2 V in 500 mM glucose. The preliminary development of the prototype confirms the feasibility of generating energy with the selected materials and highlights its limitations, laying the foundation for its optimization—such as through a more robust stabilization method. Furthermore, the project proves valuable in the context of active medical device development, enabling a comparison between the requirements of a hypothetical implantable sensors and cutting-edge technology.

Internet of Things (IoT) is a revolutionary paradigm approaching both industries and consumers everyday life. It refers to a network of addressable physical objects that contain embedded sensing, communication and actuating technologies, to sense and interact with the environment where being deployed. It can be considered as a modern expression of Mark Weiser's vision of ubiquitous computing where tiny networked computers become part of everyday objects, fusing together the virtual world and the physical word. Recent advances in hardware solutions have led to the emergence of powerful wireless IoT systems that are entirely energy-autonomous. These systems extract energy from their environment and operate intermittently, only as power is available. Battery-less sensors present an opportunity for the pervasive wide-spread of remote sensor deployments that require little maintenance and have low cost. As the number of IoT endpoint grows -- industry forecast trillions of connected smart devices in the next few years -- new challenges to program, manage and maintain such a huge number of connected devices are emerging. Web technologies can significantly ease this process by providing well-known patterns and tools - like cloud computing - for developers and users. However, the existing solutions are often too heavyweight or unfeasible for highly resource-constrained IoT devices. This dissertation presents a comprehensive analysis of two of the biggest problems that the IoT is currently facing: R1) How are we going to provide connectivity to all these devices? R2) How can we improve the quality of service provided by these tiny autonomous motes that rely only on limited energy scavenged from the environment? The first contribution is the study and deployment of a Low-Power Wide-Area-Network as a feasible solution to provide connectivity to all the expected IoT devices to be deployed in the following years. The proposed technology offers a novel communication paradigm to address discrete IoT applications, like long-range (i.e., kilometers) at low-power (i.e., tens of mW). Moreover, results highlight the effectiveness of the technology also in the industrial environment thanks to the high immunity to external noises. In the second contribution, we focus on smart metering presenting the design of three smart energy meters targeted to different scenarios. The first design presents an innovative, cost-effective smart meter with embedded non-intrusive load monitoring capabilities intended for the domestic sector. This system shows an innovative approach to provide useful feedback to reduce and optimize household energy consumption. We then present a battery-free non-intrusive power meter targeted for low-cost energy monitoring applications that lower both installation cost due to the non-intrusive approach and maintenance costs associated to battery replacement. Finally, we present an energy autonomous smart sensor with load recognition capability that dynamically adapts and reconfigures its processing pipeline to the sensed energy consumption. This enables the sensor to be energy neutral, while still providing power consumption information every 5 minutes. In the third contribution, we focus on the study of low-power visual edge processing and edge machine learning for the IoT. Two different implementations are presented. The first one discusses an energy-neutral IoT device for precision agriculture, while the second one presents a battery-less long-range visual IoT system, both leveraging on deep learning algorithms to avoid unnecessary wireless data communication. We show that there is a clear benefit from implementing a first layer of data processing directly in-situ where the data is acquired, providing a higher quality of service to the implemented application.

This work presents an investigation of a piezoelectric sensor based energy harvesting system, which collects energy from the surrounding environment. Increasing costs and scarcity of fossil fuels is a great concern today for supplying power to electronic devices. Furthermore, generating electricity by ordinary methods is a complicated process. Disposal of chemical batteries and cables is polluting the nature every day. Due to these reasons, research on energy harvesting from renewable resources has become mandatory in order to achieve improved methods and strategies of generating and storing electricity. Many low power devices being used in everyday life can be powered by harvesting energy from natural energy resources. Power overhead and power energy efficiency is of prime concern in electronic circuits. In this work, an energy harvester is modeled and simulated in Simscape™ for the functional analysis and comparison of achieved outcomes with previous work. Results demonstrate that the harvester produces power in the 0 μW to 100 μW range, which is an adequate amount to provide supply to low power devices. Power efficiency calculations also demonstrate that the implemented harvester is capable of generating and storing power for low power pervasive applications.

Embedding small wireless sensors into the environment allows for monitoring physical processes with high spatio-temporal resolutions. Today, these devices are equipped with a battery to supply them with power. Despite technological advances, the high maintenance cost and environmental impact of batteries prevent the widespread adoption of wireless sensors. Battery-free devices that store energy harvested from light, vibrations, and other ambient sources in a capacitor promise to overcome the drawbacks of (rechargeable) batteries, such as bulkiness, wear-out and toxicity. Because of low energy input and low storage capacity, battery-free devices operate intermittently; they are forced to remain inactive for most of the time charging their capacitor before being able to operate for a short time. While it is known how to deal with intermittency on a single device, the coordination and communication among groups of multiple battery-free devices remain largely unexplored. For the first time, the present thesis addresses this problem by proposing new methods and tools to investigate and overcome several fundamental challenges.

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Arctic Ocean monitoring with near-real-time data transfer is urgently needed. The harsh and remote conditions constraining year-round observation sites present significant logistical challenges and energy needs for sustained Arctic observations. The Arctic project group is attempting to design a mechanical structure to harvest energy from low-speed current in the Arctic Ocean. An Arctic energy harvesting system that consists of a transverse flux generator, boosted by a nozzle-diffuser-duct, and an American multiblade turbine that drives the generator, are designed in this study. The transverse flux generator is then optimized based on its design parameters and the optimization successfully improves the torque performance of the generator while maintaining the largest power output. The American turbine fits the extreme low-speed current condition (<0.2m/s) well and could support the rotation of the generator. Finally, the article compares the energy harvesting system is compared with the existing ones in the market and demonstrates its superior performance. / Master of Science / Arctic area has great potential and it is beneficial to monitor and do research in the Arctic area. The continuous energy could be a problem. The challenging and isolated conditions that limit the establishment of year-round observation stations pose significant logistical hurdles and energy requirements for continuous Arctic data collection. To address this, the Arctic project team is endeavoring to create a mechanical structure capable of harnessing energy from low-speed currents in the Arctic Ocean.