Aggregate Farming in the Cloud: The AFarCloud ECSEL project

Farming is facing many economic challenges in terms of productivity and cost-effectiveness. Labor shortage partly due to depopulation of rural areas, especially in Europe, is another challenge. Domain specific problems such as accurate monitoring of soil and crop properties and animal health are key factors for minimizing economical risks, and not risking human health. The ECSEL AFarCloud (Aggregate Farming in the Cloud) project will provide a distributed platform for autonomous farming that will allow the integration and cooperation of agriculture Cyber Physical Systems in real-time in order to increase efficiency, productivity, animal health, food quality and reduce farm labor costs. Moreover, such a platform can be integrated with farm management software to support monitoring and decision-making solutions based on big data and real-time data mining techniques.publishedVersio

Energy harvesting technologies for structural health monitoring of airplane components - a review

With the aim of increasing the efficiency of maintenance and fuel usage in airplanes, structural health monitoring (SHM) of critical composite structures is increasingly expected and required. The optimized usage of this concept is subject of intensive work in the framework of the EU COST Action CA18203 "Optimising Design for Inspection" (ODIN). In this context, a thorough review of a broad range of energy harvesting (EH) technologies to be potentially used as power sources for the acoustic emission and guided wave propagation sensors of the considered SHM systems, as well as for the respective data elaboration and wireless communication modules, is provided in this work. EH devices based on the usage of kinetic energy, thermal gradients, solar radiation, airflow, and other viable energy sources, proposed so far in the literature, are thus described with a critical review of the respective specific power levels, of their potential placement on airplanes, as well as the consequently necessary power management architectures. The guidelines provided for the selection of the most appropriate EH and power management technologies create the preconditions to develop a new class of autonomous sensor nodes for the in-process, non-destructive SHM of airplane components.The work of S. Zelenika, P. Gljušcic, E. Kamenar and Ž. Vrcan is partly enabled by using the equipment funded via the EU European Regional Development Fund (ERDF) project no. RC.2.2.06-0001: “Research Infrastructure for Campus-based Laboratories at the University of Rijeka (RISK)” and partly supported by the University of Rijeka, Croatia, project uniri-tehnic-18-32 „Advanced mechatronics devices for smart technological solutions“. Z. Hadas, P. Tofel and O. Ševecek acknowledge the support provided via the Czech Science Foundation project GA19-17457S „Manufacturing and analysis of flexible piezoelectric layers for smart engineering”. J. Hlinka, F. Ksica and O. Rubes gratefully acknowledge the financial support provided by the ESIF, EU Operational Programme Research, Development and Education within the research project Center of Advanced Aerospace Technology (Reg. No.: CZ.02.1.01/0.0/0.0/16_019/0000826) at the Faculty of Mechanical Engineering, Brno University of Technology. V. Pakrashi would like to acknowledge UCD Energy Institute, Marine and Renewable Energy Ireland (MaREI) centre Ireland, Strengthening Infrastructure Risk Assessment in the Atlantic Area (SIRMA) Grant No. EAPA\826/2018, EU INTERREG Atlantic Area and Aquaculture Operations with Reliable Flexible Shielding Technologies for Prevention of Infestation in Offshore and Coastal Areas (FLEXAQUA), MarTera Era-Net cofund PBA/BIO/18/02 projects. The work of J.P.B. Silva is partially supported by the Portuguese Foundation for Science and Technology (FCT) in the framework of the Strategic Funding UIDB/FIS/04650/2020. M. Mrlik gratefully acknowledges the support of the Ministry of Education, Youth and Sports of the Czech Republic-DKRVO (RP/CPS/2020/003

A Hybrid Technique of Energy Harvesting from Mechanical Vibration and Ambient Illumination

Hybrid energy harvesting is a concept applied for improving the performance of the conventional stand-alone energy harvesters. The thesis presents the analytical formulations and characterization of a hybrid energy harvester that incorporates photovoltaic, piezoelectric, electromagnetic, and electrostatic mechanisms. The initial voltage required for electrostatic mechanism is obtained by the photovoltaic technique. Other mechanisms are embedded into a bimorph piezoelectric cantilever beam having a tip magnet and two sets of comb electrodes on two sides of its substructure. All the segments are interconnected by an electric circuit to generate combined output when subjected to vibration and solar illumination. Results for power output have been obtained at resonance frequency using an optimum load resistance. As the power transduced by each of the mechanisms is combined, more power is generated than those obtained by stand-alone mechanisms. The synergistic feature of this research is further promoted by adding fatigue analysis using finite element method

Autonomous and Controllable Systems of Sensors and Methods of Using such Systems

An autonomous and controllable system of sensors and methods for using such a system of sensors are described

Power Gain Estimation of an Event-driven Wake-Up Controller dedicated to WSN's Microcontroller

Abstract-To deal with Wireless Sensor Node's energy constraints, new architectural solutions have to be found. This paper proposes to analyze a WSN microcontroller sub-system power consumption to extract the main power contributors according to different applicative execution phases. The objective is to come out with the energy reduction potentiality offered by an additional module called Wake-Up Controller. This block is able to substitute to the main CPU for current tasks like data transfers between sensors, memories or radio and fine grain power/frequency management of the entire node's sub-modules. Power simulations of a microcontroller sub-system based on FDSOI28 technology, with and without the Wake-Up Controller use, are proposed. Results are presented for applicative scenarios ranging from very low to high activity rates. This study exhibits power gains from 14.5% to 76% in the full range attesting the future design of this new module

Fast-waking and low-voltage thermoelectric and photovoltaic CMOS chargers for energy-harvesting wireless microsensors

The small size of wireless microsystems allows them to be deployed within larger systems to sense and monitor various indicators throughout many applications. However, their small size restricts the amount of energy that can be stored in the system. Current microscale battery technologies do not store enough energy to power the microsystems for more than a few months without recharging. Harvesting ambient energy to replenish the on-board battery extend the lifetime of the microsystem. Although light and thermal energy are more practical in some applications than other forms of ambient energy, they nevertheless suffer from long energy droughts. Additionally, due to the very limited space available in the microsystem, the system cannot store enough energy to continue operation throughout these energy droughts. Therefore, the microsystem must reliably wake from these energy droughts, even if the on-board battery has been depleted. The challenge here is waking a microsystem directly from an ambient source transducer whose voltage and power levels are limited due to their small size. Starter circuits must be used to ensure the system wakes regardless of the state of charge of the energy storage device. The purpose of the presented research is to develop, design, simulate, fabricate, test and evaluate CMOS integrated circuits that can reliably wake from no energy conditions and quickly recharge a depleted battery. Since the battery is depleted during startup, the system must use the low voltage produced by the energy harvesting transducer to transfer energy. The presented system has the fastest normalized wake time while reusing the inductor already present in the battery charger for startup, therefore, minimizing the overall footprint of the system.Ph.D

AN INTEGRATED ELECTROMAGNETIC MICRO-TURBO-GENERATOR SUPPORTED ON ENCAPSULATED MICROBALL BEARINGS

This dissertation presents the development of an integrated electromagnetic micro-turbo-generator supported on encapsulated microball bearings for electromechanical power conversion in MEMS (Microelectromechanical Systems) scale. The device is composed of a silicon turbine rotor with magnetic materials that is supported by microballs over a stator with planar, multi-turn, three-phase copper coils. The micro-turbo-generator design exhibits a novel integration of three key technologies and components, namely encapsulated microball bearings, incorporated thick magnetic materials, and wafer-thick stator coils. Encapsulated microball bearings provide a robust supporting mechanism that enables a simple operation and actuation scheme with high mechanical stability. The integration of thick magnetic materials allows for a high magnetic flux density within the stator. The wafer-thick coil design optimizes the flux linkage and decreases the internal impedance of the stator for a higher output power. Geometrical design and device parameters are optimized based on theoretical analysis and finite element simulations. A microfabrication process flow was designed using 15 optical masks and 110 process steps to fabricate the micro-turbo-generators, which demonstrates the complexity in device manufacturing. Two 10 pole devices with 2 and 3 turns per pole were fabricated. Single phase resistances of 46Ω and 220Ω were measured for the two stators, respectively. The device was actuated using pressurized nitrogen flowing through a silicon plumbing layer. A test setup was built to simultaneously measure the gas flow rate, pressure, rotor speed, and output voltage and power. Friction torques in the range of 5.5-33µNm were measured over a speed range of 0-16krpm (kilo rotations per minute) within the microball bearings using spin-down testing methodology. A maximum per-phase sinusoidal open circuit voltage of 0.1V was measured at 23krpm, and a maximum per-phase AC power of 10µW was delivered on a matched load at 10krpm, which are in full-agreement with the estimations based on theoretical analysis and simulations. The micro-turbo-generator presented in this work is capable of converting gas flow into electricity, and can potentially be coupled to a same-scale combustion engine to convert high-density hydrocarbon energy into electrical power to realize a high-density power source for portable electronic systems

Design for energy-efficient and reliable fog-assisted healthcare IoT systems

Cardiovascular disease and diabetes are two of the most dangerous diseases as they are the leading causes of death in all ages. Unfortunately, they cannot be completely cured with the current knowledge and existing technologies. However, they can be effectively managed by applying methods of continuous health monitoring. Nonetheless, it is difficult to achieve a high quality of healthcare with the current health monitoring systems which often have several limitations such as non-mobility support, energy inefficiency, and an insufficiency of advanced services. Therefore, this thesis presents a Fog computing approach focusing on four main tracks, and proposes it as a solution to the existing limitations. In the first track, the main goal is to introduce Fog computing and Fog services into remote health monitoring systems in order to enhance the quality of healthcare. In the second track, a Fog approach providing mobility support in a real-time health monitoring IoT system is proposed. The handover mechanism run by Fog-assisted smart gateways helps to maintain the connection between sensor nodes and the gateways with a minimized latency. Results show that the handover latency of the proposed Fog approach is 10%-50% less than other state-of-the-art mobility support approaches. In the third track, the designs of four energy-efficient health monitoring IoT systems are discussed and developed. Each energy-efficient system and its sensor nodes are designed to serve a specific purpose such as glucose monitoring, ECG monitoring, or fall detection; with the exception of the fourth system which is an advanced and combined system for simultaneously monitoring many diseases such as diabetes and cardiovascular disease. Results show that these sensor nodes can continuously work, depending on the application, up to 70-155 hours when using a 1000 mAh lithium battery. The fourth track mentioned above, provides a Fog-assisted remote health monitoring IoT system for diabetic patients with cardiovascular disease. Via several proposed algorithms such as QT interval extraction, activity status categorization, and fall detection algorithms, the system can process data and detect abnormalities in real-time. Results show that the proposed system using Fog services is a promising approach for improving the treatment of diabetic patients with cardiovascular disease