Electroactive poly(vinylidene fluoride) based materials: recent progress, challenges and opportunities

A poly(vinylidene fluoride) (PVDF) and its copolymers are polymers that, in specific crystalline phases, show high dielectric and piezoelectric values, excellent mechanical behavior and good thermal and chemical stability, suitable for many applications from the biomedical area to energy devices. This chapter introduces the main properties, processability and polymorphism of PVDF. Further, the recent advances in the applications based on those materials are presented and discussed. Thus, it shown the key role of PVDF and its copolymers as smart and multifunctional material, expanding the limits of polymer-based technologies.FCT (Fundação para a Ciência e Tecnologia) for financial support under the framework of Strategic Funding grants UID/FIS/04650/2019, and UID/QUI/0686/2019 and project PTDC/FIS-MAC/28157/2017, PTDC/BTMMAT/28237/2017, PTDC/EMD-EMD/28159/2017. The author also thanks the FCT for financial support under grant SFRH/BPD/112547/2015 (C.M.C.), SFRH/BPD/98109/2013 (V.F.C.), SFRH/BD/140698/2018 (R.B.P.), SFRH/BPD/96227/2013 (P.M.), SFRH/BPD/121526/2016 (D.M.C.), SFRH/BPD/97739/2013 (V. C.), SFRH/BPD/90870/2012 (C.R.). Financial support from the Spanish Ministry of Economy and Competitiveness (MINECO) through project MAT2016-76039-C4-3-R (AEI/FEDER, UE) (including FEDER financial support) and from the Basque Government Industry and Education Departments under the ELKARTEK, HAZITEK and PIBA (PIBA-2018-06)

Sensitive and Makeable Computational Materials for the Creation of Smart Everyday Objects

The vision of computational materials is to create smart everyday objects using the materi- als that have sensing and computational capabilities embedded into them. However, today’s development of computational materials is limited because its interfaces (i.e. sensors) are unable to support wide ranges of human interactions , and withstand the fabrication meth- ods of everyday objects (e.g. cutting and assembling). These barriers hinder citizens from creating smart every day objects using computational materials on a large scale. To overcome the barriers, this dissertation presents the approaches to develop compu- tational materials to be 1) sensitive to a wide variety of user interactions, including explicit interactions (e.g. user inputs) and implicit interactions (e.g. user contexts), and 2) makeable against a wide range of fabrication operations, such cutting and assembling. I exemplify the approaches through five research projects on two common materials, textile and wood. For each project, I explore how a material interface can be made to sense user inputs or activities, and how it can be optimized to balance sensitivity and fabrication complexity. I discuss the sensing algorithms and machine learning model to interpret the sensor data as high-level abstraction and interaction. I show the practical applications of developed computational materials. I demonstrate the evaluation study to validate their performance and robustness. In the end of this dissertation, I summarize the contributions of my thesis and discuss future directions for the vision of computational materials

Roadmap on energy harvesting materials

Ambient energy harvesting has great potential to contribute to sustainable development and address growing environmental challenges. Converting waste energy from energy-intensive processes and systems (e.g. combustion engines and furnaces) is crucial to reducing their environmental impact and achieving net-zero emissions. Compact energy harvesters will also be key to powering the exponentially growing smart devices ecosystem that is part of the Internet of Things, thus enabling futuristic applications that can improve our quality of life (e.g. smart homes, smart cities, smart manufacturing, and smart healthcare). To achieve these goals, innovative materials are needed to efficiently convert ambient energy into electricity through various physical mechanisms, such as the photovoltaic effect, thermoelectricity, piezoelectricity, triboelectricity, and radiofrequency wireless power transfer. By bringing together the perspectives of experts in various types of energy harvesting materials, this Roadmap provides extensive insights into recent advances and present challenges in the field. Additionally, the Roadmap analyses the key performance metrics of these technologies in relation to their ultimate energy conversion limits. Building on these insights, the Roadmap outlines promising directions for future research to fully harness the potential of energy harvesting materials for green energy anytime, anywhere

Wearable Energy Harvesting for Charging Portable Electronic Devices by Walking

Wearable energy harvesting technologies will become an everyday part of future portable electronic devices. By generating the energy where the energy is needed and not relying on a main power source to recharge the portable devices battery, wearable energy harvesters will enable future generations to have even more freedoms, travel further, and never run low on battery again. This will reduce the energy consumption of the mains grid and thus in turn reduce CO² emissions generated by this traditional power source making this research important for the whole plant. This research project aims to take another step towards in helping the development of future technologies by investigating novel wearable energy harvesting designs and showing ability to charge current portable electronic devices such as smart phones and tables. This required research into a broad range of topics including, energies from humans, energy conversion mechanisms, the movement of people and the power demands for charging current portable electronic devices. Background research in the human energy levels and how research to date had gone about exacting different energy sources in different ways was the starting point for this research. This leads on to a more detailed look into the exaction methods and optimization of footfall energy harvester designs. Looking into the human gait cycle gave the information required to replicate human footfall motion for use in scientific experiments. From this background research, two bespoke designs of wearable energy harvester have been created. The first novel design showed a promising way of extracting footfall energy and converting it into useable electrical energy producing Watt-Level of power. The second design is an evolution of the first design but expands the extraction method to both feet and relocated the main harvester unit into a backpack worn by the user. The improved design incorporates a novel approach to energy conversion method by introducing a mechanical energy storage system before transduction into electrical energy. This is shown to increased electrical power output from footfall energy, reduced energy consumption of the wearer and is shown to truly be able to charge current portable electronics. The improved design is shown to produce 2.6 Watts average power from normal walking. The experimental set ups, procedures, and their results are shown throughout this thesis. These experimental results are confirmed by using the wearable energy harvesters on a treadmill at the three main walking speeds showing their real-world capabilities. To demonstrate the wearable energy harvester deigns shown in this research project were truly able to charge current portable technologies, endurance testing was also performed. This confirms the harvesters were able to work for longer periods of time. This longer time frame is needed for the charging times of the current portable devices. After researching into wearable energy harvesting from over the last 20 years it was a struggle to compare all the different forms, designs, types and power outputs. It became clear that the existing methods were unable to provide a clear picture of harvester’s scalability, changeability and useability for future design ideas. This is why a new form of comparison was created and is shown to have strong benefits over the existing methods

Driving Monitoring System Application With Stretchable Conductive Inks: A Review

Nowadays the automotive industry is moving towards developing system connected vehicle parameters which can monitor the driver’s behaviour before driving. Most drivers lose focus and are emotionally distracted while driving owing to fatigue, drowsiness and alcohol consumption, that can result in a traffic accidents. The device or equipment used to detect the driver’s health before driving has always posed a problem in terms of the efficiency of the system especially concerning the cable connecting the equipment. Stretchable conductive ink (SCI) via electronic devices have been widely applied in various industries such as fabric, health, automotive, communications, etc. The flexibility allows a circuit to be placed on an uneven or constantly changing surface. However, till to-date, the effective use of the stretchable conductive ink has yet to be proven in the automotive industry. The current driver monitoring system cannot integrate with many of the driver's health level tracking features at one time. A combination of the driver’s monitoring system methods with stretchable conductive ink (SCI) sensors layout design can be used to prevent road accidents as a result of a driver’s behavior and will make the driving monitoring system more effective with soft substrates technology that has the advantage of geometric deformation based on appropriate shapes

Compute-proximal Energy Harvesting for Mobile Environments: Fundamentals, Applications, and Tools

Over the past two decades, we have witnessed remarkable achievements in computing, sensing, actuating, and communications capabilities of ubiquitous computing applications. However, due to the limitations in stable energy supply, it is difficult to make the applications ubiquitous. Batteries have been considered a promising technology for this problem, but their low energy density and sluggish innovation have constrained the utility and expansion of ubiquitous computing. Two key techniques—energy harvesting and power management—have been studied as alternatives to overcome the battery limitations. Compared to static environments such as homes or buildings, there are more energy harvesting opportunities in mobile environments since ubiquitous systems can generate various forms of energy as they move. Most of the previous studies in this regard have been focused on human movements for wearable computing, while other mobile environments (e.g., cars, motorcycles, and bikes) have received limited attention. In this thesis, I present a class of energy harvesting approaches called compute-proximal energy harvesting, which allows us to develop energy harvesting technology where computing, sensing, and actuating are needed in vehicles. Computing includes sensing phenomena, executing instructions, actuating components, storing information, and communication. Proximal considers the harvesting of energy available around the specific location where computation is needed, reducing the need for excessive wiring. A primary goal of this new approach is to mitigate the effort associated with the installation and field deployment of self-sustained computing and lower the entry barriers to developing self-sustainable systems for vehicles. In this thesis, I first select an automobile as a promising case study and discuss the opportunities, challenges, and design guidelines of compute-proximal energy harvesting with practical yet advanced examples in the automotive domain. Second, I present research in the design of small-scale wind energy harvesters and the implementation and evaluation of two advanced safety sensing systems—a blind spot monitoring system and a lane detection system—with the harvested power from wind. Finally, I conduct a study to democratize the lessons learned from the automotive case studies for makers and people with no prior experience in energy harvesting technology. In this study, I seek to understand what problems they have encountered and what possible solutions they have considered while dealing with energy harvesting technology. Based on the findings, I develop a comprehensive energy harvesting toolkit and examine its utility, usability, and creativity through a series of workshops.Ph.D

IoT and Sensor Networks in Industry and Society

The exponential progress of Information and Communication Technology (ICT) is one of the main elements that fueled the acceleration of the globalization pace. Internet of Things (IoT), Artificial Intelligence (AI) and big data analytics are some of the key players of the digital transformation that is affecting every aspect of human's daily life, from environmental monitoring to healthcare systems, from production processes to social interactions. In less than 20 years, people's everyday life has been revolutionized, and concepts such as Smart Home, Smart Grid and Smart City have become familiar also to non-technical users. The integration of embedded systems, ubiquitous Internet access, and Machine-to-Machine (M2M) communications have paved the way for paradigms such as IoT and Cyber Physical Systems (CPS) to be also introduced in high-requirement environments such as those related to industrial processes, under the forms of Industrial Internet of Things (IIoT or I2oT) and Cyber-Physical Production Systems (CPPS). As a consequence, in 2011 the German High-Tech Strategy 2020 Action Plan for Germany first envisioned the concept of Industry 4.0, which is rapidly reshaping traditional industrial processes. The term refers to the promise to be the fourth industrial revolution. Indeed, the first industrial revolution was triggered by water and steam power. Electricity and assembly lines enabled mass production in the second industrial revolution. In the third industrial revolution, the introduction of control automation and Programmable Logic Controllers (PLCs) gave a boost to factory production. As opposed to the previous revolutions, Industry 4.0 takes advantage of Internet access, M2M communications, and deep learning not only to improve production efficiency but also to enable the so-called mass customization, i.e. the mass production of personalized products by means of modularized product design and flexible processes. Less than five years later, in January 2016, the Japanese 5th Science and Technology Basic Plan took a further step by introducing the concept of Super Smart Society or Society 5.0. According to this vision, in the upcoming future, scientific and technological innovation will guide our society into the next social revolution after the hunter-gatherer, agrarian, industrial, and information eras, which respectively represented the previous social revolutions. Society 5.0 is a human-centered society that fosters the simultaneous achievement of economic, environmental and social objectives, to ensure a high quality of life to all citizens. This information-enabled revolution aims to tackle today’s major challenges such as an ageing population, social inequalities, depopulation and constraints related to energy and the environment. Accordingly, the citizens will be experiencing impressive transformations into every aspect of their daily lives. This book offers an insight into the key technologies that are going to shape the future of industry and society. It is subdivided into five parts: the I Part presents a horizontal view of the main enabling technologies, whereas the II-V Parts offer a vertical perspective on four different environments. The I Part, dedicated to IoT and Sensor Network architectures, encompasses three Chapters. In Chapter 1, Peruzzi and Pozzebon analyse the literature on the subject of energy harvesting solutions for IoT monitoring systems and architectures based on Low-Power Wireless Area Networks (LPWAN). The Chapter does not limit the discussion to Long Range Wise Area Network (LoRaWAN), SigFox and Narrowband-IoT (NB-IoT) communication protocols, but it also includes other relevant solutions such as DASH7 and Long Term Evolution MAchine Type Communication (LTE-M). In Chapter 2, Hussein et al. discuss the development of an Internet of Things message protocol that supports multi-topic messaging. The Chapter further presents the implementation of a platform, which integrates the proposed communication protocol, based on Real Time Operating System. In Chapter 3, Li et al. investigate the heterogeneous task scheduling problem for data-intensive scenarios, to reduce the global task execution time, and consequently reducing data centers' energy consumption. The proposed approach aims to maximize the efficiency by comparing the cost between remote task execution and data migration. The II Part is dedicated to Industry 4.0, and includes two Chapters. In Chapter 4, Grecuccio et al. propose a solution to integrate IoT devices by leveraging a blockchain-enabled gateway based on Ethereum, so that they do not need to rely on centralized intermediaries and third-party services. As it is better explained in the paper, where the performance is evaluated in a food-chain traceability application, this solution is particularly beneficial in Industry 4.0 domains. Chapter 5, by De Fazio et al., addresses the issue of safety in workplaces by presenting a smart garment that integrates several low-power sensors to monitor environmental and biophysical parameters. This enables the detection of dangerous situations, so as to prevent or at least reduce the consequences of workers accidents. The III Part is made of two Chapters based on the topic of Smart Buildings. In Chapter 6, Petroșanu et al. review the literature about recent developments in the smart building sector, related to the use of supervised and unsupervised machine learning models of sensory data. The Chapter poses particular attention on enhanced sensing, energy efficiency, and optimal building management. In Chapter 7, Oh examines how much the education of prosumers about their energy consumption habits affects power consumption reduction and encourages energy conservation, sustainable living, and behavioral change, in residential environments. In this Chapter, energy consumption monitoring is made possible thanks to the use of smart plugs. Smart Transport is the subject of the IV Part, including three Chapters. In Chapter 8, Roveri et al. propose an approach that leverages the small world theory to control swarms of vehicles connected through Vehicle-to-Vehicle (V2V) communication protocols. Indeed, considering a queue dominated by short-range car-following dynamics, the Chapter demonstrates that safety and security are increased by the introduction of a few selected random long-range communications. In Chapter 9, Nitti et al. present a real time system to observe and analyze public transport passengers' mobility by tracking them throughout their journey on public transport vehicles. The system is based on the detection of the active Wi-Fi interfaces, through the analysis of Wi-Fi probe requests. In Chapter 10, Miler et al. discuss the development of a tool for the analysis and comparison of efficiency indicated by the integrated IT systems in the operational activities undertaken by Road Transport Enterprises (RTEs). The authors of this Chapter further provide a holistic evaluation of efficiency of telematics systems in RTE operational management. The book ends with the two Chapters of the V Part on Smart Environmental Monitoring. In Chapter 11, He et al. propose a Sea Surface Temperature Prediction (SSTP) model based on time-series similarity measure, multiple pattern learning and parameter optimization. In this strategy, the optimal parameters are determined by means of an improved Particle Swarm Optimization method. In Chapter 12, Tsipis et al. present a low-cost, WSN-based IoT system that seamlessly embeds a three-layered cloud/fog computing architecture, suitable for facilitating smart agricultural applications, especially those related to wildfire monitoring. We wish to thank all the authors that contributed to this book for their efforts. We express our gratitude to all reviewers for the volunteering support and precious feedback during the review process. We hope that this book provides valuable information and spurs meaningful discussion among researchers, engineers, businesspeople, and other experts about the role of new technologies into industry and society

Biosensors for Diagnosis and Monitoring

Biosensor technologies have received a great amount of interest in recent decades, and this has especially been the case in recent years due to the health alert caused by the COVID-19 pandemic. The sensor platform market has grown in recent decades, and the COVID-19 outbreak has led to an increase in the demand for home diagnostics and point-of-care systems. With the evolution of biosensor technology towards portable platforms with a lower cost on-site analysis and a rapid selective and sensitive response, a larger market has opened up for this technology. The evolution of biosensor systems has the opportunity to change classic analysis towards real-time and in situ detection systems, with platforms such as point-of-care and wearables as well as implantable sensors to decentralize chemical and biological analysis, thus reducing industrial and medical costs. This book is dedicated to all the research related to biosensor technologies. Reviews, perspective articles, and research articles in different biosensing areas such as wearable sensors, point-of-care platforms, and pathogen detection for biomedical applications as well as environmental monitoring will introduce the reader to these relevant topics. This book is aimed at scientists and professionals working in the field of biosensors and also provides essential knowledge for students who want to enter the field