1,468 research outputs found

    IoT Transmission Technologies for Distributed Measurement Systems in Critical Environments

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    Distributed measurement systems are spread in the most diverse application scenarios, and Internet of Things (IoT) transmission equipment is usually the enabling technologies for such measurement systems that need to feature wireless connectivity to ensure pervasiveness. Because wireless measurement systems have been deployed for the last years even in critical environments, assessing transmission technologies performances in such contexts is fundamental. Indeed, they are the most challenging ones for wireless data transmission due to their intrinsic attenuation capabilities. Several scenarios in which measurement systems can be deployed are analysed. Firstly, marine contexts are treated by considering above-the-sea wireless links. Such setting can be experienced in whichever application requiring remote monitoring of facilities and assets that are offshore installed. Some instances are offshore sea farming plants, or remote video monitoring systems installed on seamark buoys. Secondly, wireless communications taking place from the underground to the aboveground are covered. This scenario is typical of precision agriculture applications, where the accurate measurement of underground physical parameters is needed to be remotely sent to optimise crops reducing the wastefulness of fundamental resources (e.g., irrigation water). Thirdly, wireless communications occurring from the underwater to the abovewater are addressed. Such situation is inevitable for all those infrastructures monitoring conservation status of underwater species like algae, seaweeds and reef. Then, wireless links happening traversing metal surfaces and structures are tackled. Such context is commonly encountered in asset tracking and monitoring (e.g., containers), or in smart metering applications (e.g., utility meters). Lastly, sundry harsh environments that are typical of industrial monitoring (e.g., vibrating machineries, harsh temperature and humidity rooms, corrosive atmospheres) are tested to validate pervasive measurement infrastructures even in such contexts that are usually experienced in Industrial Internet of Things (IIoT) applications. The performances of wireless measurement systems in such scenarios are tested by sorting out ad-hoc measurement campaigns. Finally, IoT measurement infrastructures respectively deployed in above-the-sea and underground-to-aboveground settings are described to provide real applications in which such facilities can be effectively installed. Nonetheless, the aforementioned application scenarios are only some amid their sundry variety. Indeed, nowadays distributed pervasive measurement systems have to be thought in a broad way, resulting in countless instances: predictive maintenance, smart healthcare, smart cities, industrial monitoring, or smart agriculture, etc. This Thesis aims at showing distributed measurement systems in critical environments to set up pervasive monitoring infrastructures that are enabled by IoT transmission technologies. At first, they are presented, and then the harsh environments are introduced, along with the relative theoretical analysis modelling path loss in such conditions. It must be underlined that this Thesis aims neither at finding better path loss models with respect to the existing ones, nor at improving them. Indeed, path loss models are exploited as they are, in order to derive estimates of losses to understand the effectiveness of the deployed infrastructure. In fact, some transmission tests in those contexts are described, along with providing examples of these types of applications in the field, showing the measurement infrastructures and the relative critical environments serving as deployment sites. The scientific relevance of this Thesis is evident since, at the moment, the literature lacks a comparative study like this, showing both transmission performances in critical environments, and the deployment of real IoT distributed wireless measurement systems in such contexts

    Key Perspectives in Power Aware Ad-hoc Internet of Things with Advanced Networks and Real Time Scenarios

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    Smart gadgets with integrated power optimization segments are the key perspectives that use Internet of Things (IoT) enabled technology to promote lifestyle advancements. It has an influence on a number of sectors in academia and/or business thanks to its strong integration with the current Cloud architecture. Recently, the Internet of Things has been acknowledged as a disruptive technology for the aerial ad hoc network. IoT may be thought of as a network inside a network. IoT-based networks rely heavily on the so-called self-organizing capability working in a dispersed manner in ad hoc networks, with users travelling at speeds ranging from walking pace to automobile, rail, or airline speed. IoT applications that assist logistics and the administration of ad hoc networks may be found in a broad variety. Utility companies are under pressure now to produce ever more enormous amounts of electricity. In megacities, there is an exponential rise in the number of people and energy users. Thus, the need for energy conservation is growing significantly on a global scale. The best way to optimise the rising energy demands and consumptions is as a consequence of the development of energy-monitoring systems. These solutions can cut current utilisation levels, stop energy waste, and make better use of our resources

    Cooperative Self-Scheduling Secure Routing Protocol for Efficient Communication in MANET

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    In wireless transmission, a Mobile Ad-hoc Network (MANET) contains many mobile nodes that can communicate without needing base stations. Due to the highly dynamic nature of wireless, MANETs face several issues, like malicious nodes making packet loss, high energy consumption, and security. Key challenges include efficient clustering and routing with optimal energy efficiency for Quality of Service (QoS) performance. To combat these issues, this novel presents Cooperative Self-Scheduling Secure Routing Protocol (CoS3RP) for efficient scheduling for proficient packet transmission in MANET. Initially, we used Elite Sparrow Search Algorithm (ESSA) for identifies the Cluster Head (CH) and form clusters. The Multipath Optimal Distance Selection (MODS) technique is used to find the multiple routes for data transmission. Afterward, the proposed CoS3RP transmits the packets based on each node authentication. The proposed method for evaluating and selecting efficient routing and data transfer paths is implemented using the Network simulator (NS2) tool, and the results are compared with other methods. Furthermore, the proposed well performs in routing performance, security, latency and throughput

    Harnessing energy for wearables: a review of radio frequency energy harvesting technologies

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    Wireless energy harvesting enables the conversion of ambient energy into electrical power for small wireless electronic devices. This technology offers numerous advantages, including availability, ease of implementation, wireless functionality, and cost-effectiveness. Radio frequency energy harvesting (RFEH) is a specific type of wireless energy harvesting that enables wireless power transfer by utilizing RF signals. RFEH holds immense potential for extending the lifespan of wireless sensors and wearable electronics that require low-power operation. However, despite significant advancements in RFEH technology for self-sustainable wearable devices, numerous challenges persist. This literature review focuses on three key areas: materials, antenna design, and power management, to delve into the research challenges of RFEH comprehensively. By providing an up-to-date review of research findings on RFEH, this review aims to shed light on the critical challenges, potential opportunities, and existing limitations. Moreover, it emphasizes the importance of further research and development in RFEH to advance its state-of-the-art and offer a vision for future trends in this technology

    Spatial-temporal domain charging optimization and charging scenario iteration for EV

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    Environmental problems have become increasingly serious around the world. With lower carbon emissions, Electric Vehicles (EVs) have been utilized on a large scale over the past few years. However, EVs are limited by battery capacity and require frequent charging. Currently, EVs suffer from long charging time and charging congestion. Therefore, EV charging optimization is vital to ensure drivers’ mobility. This study first presents a literature analysis of the current charging modes taxonomy to elucidate the advantages and disadvantages of different charging modes. In specific optimization, under plug-in charging mode, an Urgency First Charging (UFC) scheduling policy is proposed with collaborative optimization of the spatialtemporal domain. The UFC policy allows those EVs with charging urgency to get preempted charging services. As conventional plug-in charging mode is limited by the deployment of Charging Stations (CSs), this study further introduces and optimizes Vehicle-to-Vehicle (V2V) charging. This is aim to maximize the utilization of charging infrastructures and to balance the grid load. This proposed reservation-based V2V charging scheme optimizes pair matching of EVs based on minimized distance. Meanwhile, this V2V scheme allows more EVs get fully charged via minimized waiting time based parking lot allocation. Constrained by shortcomings (rigid location of CSs and slow charging power under V2V converters), a single charging mode can hardly meet a large number of parallel charging requests. Thus, this study further proposes a hybrid charging mode. This mode is to utilize the advantages of plug-in and V2V modes to alleviate the pressure on the grid. Finally, this study addresses the potential problems of EV charging with a view to further optimizing EV charging in subsequent studies

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

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    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

    Economic and Social Consequences of the COVID-19 Pandemic in Energy Sector

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    The purpose of the Special Issue was to collect the results of research and experience on the consequences of the COVID-19 pandemic for the energy sector and the energy market, broadly understood, that were visible after a year. In particular, the impact of COVID-19 on the energy sector in the EU, including Poland, and the US was examined. The topics concerned various issues, e.g., the situation of energy companies, including those listed on the stock exchange, mining companies, and those dealing with renewable energy. The topics related to the development of electromobility, managerial competences, energy expenditure of local government units, sustainable development of energy, and energy poverty during a pandemic were also discussed
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