341 research outputs found

    Vibration-powered sensing system for engine condition monitoring

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    Condition monitoring is becoming an established technique for managing the maintenance of machinery in transport applications. Vibration energy harvesting allows wireless systems to be powered without batteries, but most traditional generators have been designed to operate at fixed frequencies. The variety of engine speeds (and hence vibration frequencies) in transport applications therefore means that these are not usable. This paper describes the application-driven specification, design and implementation of a novel vibration-powered sensing system for condition monitoring of engines. This demonstrates that, through careful holistic design of the entire system, condition monitoring systems can be powered solely from machine vibration, managing their energy resources and transmitting sensed data wirelessly

    Towards self-powered wireless sensor networks

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    Ubiquitous computing aims at creating smart environments in which computational and communication capabilities permeate the word at all scales, improving the human experience and quality of life in a totally unobtrusive yet completely reliable manner. According to this vision, an huge variety of smart devices and products (e.g., wireless sensor nodes, mobile phones, cameras, sensors, home appliances and industrial machines) are interconnected to realize a network of distributed agents that continuously collect, process, share and transport information. The impact of such technologies in our everyday life is expected to be massive, as it will enable innovative applications that will profoundly change the world around us. Remotely monitoring the conditions of patients and elderly people inside hospitals and at home, preventing catastrophic failures of buildings and critical structures, realizing smart cities with sustainable management of traffic and automatic monitoring of pollution levels, early detecting earthquake and forest fires, monitoring water quality and detecting water leakages, preventing landslides and avalanches are just some examples of life-enhancing applications made possible by smart ubiquitous computing systems. To turn this vision into a reality, however, new raising challenges have to be addressed, overcoming the limits that currently prevent the pervasive deployment of smart devices that are long lasting, trusted, and fully autonomous. In particular, the most critical factor currently limiting the realization of ubiquitous computing is energy provisioning. In fact, embedded devices are typically powered by short-lived batteries that severely affect their lifespan and reliability, often requiring expensive and invasive maintenance. In this PhD thesis, we investigate the use of energy-harvesting techniques to overcome the energy bottleneck problem suffered by embedded devices, particularly focusing on Wireless Sensor Networks (WSNs), which are one of the key enablers of pervasive computing systems. Energy harvesting allows to use energy readily available from the environment (e.g., from solar light, wind, body movements, etc.) to significantly extend the typical lifetime of low-power devices, enabling ubiquitous computing systems that can last virtually forever. However, the design challenges posed both at the hardware and at the software levels by the design of energy-autonomous devices are many. This thesis addresses some of the most challenging problems of this emerging research area, such as devising mechanisms for energy prediction and management, improving the efficiency of the energy scavenging process, developing protocols for harvesting-aware resource allocation, and providing solutions that enable robust and reliable security support. %, including the design of mechanisms for energy prediction and management, improving the efficiency of the energy harvesting process, the develop of protocols for harvesting-aware resource allocation, and providing solutions that enable robust and reliable security support

    Model-based design for self-sustainable sensor nodes

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    Long-term and maintenance-free operation is a critical feature for large-scale deployed battery-operated sensor nodes. Energy harvesting (EH) is the most promising technology to overcome the energy bottleneck of today’s sensors and to enable the vision of perpetual operation. However, relying on fluctuating environmental energy requires an application-specific analysis of the energy statistics combined with an in-depth characterization of circuits and algorithms, making design and verification complex. This article presents a model-based design (MBD) approach for EH-enabled devices accounting for the dynamic behavior of components in the power generation, conversion, storage, and discharge paths. The extension of existing compact models combined with data-driven statistical modeling of harvesting circuits allows accurate offline analysis, verification, and validation. The presented approach facilitates application-specific optimization during the development phase and reliable long-term evaluation combined with environmental datasets. Experimental results demonstrate the accuracy and flexibility of this approach: the model verification of a solar-powered wireless sensor node shows a determination coefficient () of 0.992, resulting in an energy error of only -1.57 % between measurement and simulation. Compared to state-of-practice methods, the MBD approach attains a reduction of the estimated state-of-charge error of up to 10.2 % in a real-world scenario. MBD offers non-trivial insights on critical design choices: the analysis of the storage element selection reveals a 2–3 times too high self-discharge per capacity ratio for supercapacitors and a peak current constrain for lithium-ion polymer batteries

    Autonomous electrical current monitoring system for aircraft

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    Aircraft monitoring systems offer enhanced safety, reliability, reduced maintenance cost and improved overall flight efficiency. Advancements in wireless sensor networks (WSN) are enabling unprecedented data acquisition functionalities, but their applicability is restricted by power limitations, as batteries require replacement or recharging and wired power adds weight and detracts from the benefits of wireless technology. In this paper, an energy autonomous WSN is presented for monitoring the structural current in aircraft structures. A hybrid inductive/hall sensing concept is introduced demonstrating 0.5 A resolution, < 2% accuracy and frequency independence, for a 5 A – 100 A RMS, DC-800 Hz current and frequency range, with 35 mW active power consumption. An inductive energy harvesting power supply with magnetic flux funnelling, reactance compensation and supercapacitor storage is demonstrated to provide 0.16 mW of continuous power from the 65 μT RMS field of a 20 A RMS, 360 Hz structural current. A low-power sensor node platform with a custom multi-mode duty cycling network protocol is developed, offering cold starting network association and data acquisition/transmission functionality at 50 μW and 70 μW average power respectively. WSN level operation for 1 minute for every 8 minutes of energy harvesting is demonstrated. The proposed system offers a unique energy autonomous WSN platform for aircraft monitoring

    Low-Power Pıc-Based Sensor Node Devıce Desıgn And Theoretıcal Analysıs Of Energy Consumptıon In Wıreless Sensor Networks

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    Teknolojinin ilerlemesi, daha enerji verimli ve daha ucuz elektronik bileşenlerinin daha küçük üretilmesini sağlamıştır. Bu nedenle, daha önce mevcut birçok bilgisayar ve elektronik bilim-mühendislik fikirleri uygulanabilir hale gelmiştir. Bunlardan birisi de kablosuz sensör ağları teknolojisidir. Kablosuz algılayıcı ağlar, düşük enerji tüketimi ve gerekli teknik gereksinimlerin gerçekleşmesi ile uygulanabilir hale gelmiştir. Ayrıca, Kablosuz algılayıcı ağlarının tasarımında iletişim algoritmaları, enerji tasarruf protokolleri ve yenilenebilir enerji teknolojileri gibi diğer bilimsel çalışmalar zorunlu hale gelmiştir. Bu tez, mikroelektronik sistemler, kablosuz iletişim ve dijital elektronik teknolojisinin ilerlemesiyle uygulanabilir hale gelmiş sensör ağları teknolojisini kapsamaktadır. Birincisi, algılama görevleri ve potansiyel algılayıcı ağ uygulamaları araştırılmış ve algılayıcı ağlarının tasarımını etkileyen faktörlerin gözden geçirilmesi sağlanmıştır. Ardından sensör ağları için iletişim mimarisi ana hatlarıyla belirtilmiştir. Ayrıca, tek bir düğümün WLAN ile iletişim kurabilmesi için yeni donanım mimarisi tasarlanmış ve düğümlerde yenilenebilir enerji kaynakları kullanılmıştır. Bu tezde WSN, analitik bilim ve uygulamalı bilim açısından incelenmiştir. Düşük enerji tüketimi ve iletişim protokolleri arasındaki ilişki değerlendirilmiş ve bilimsel sonuçlara varılmıştır. Teorik analizler bilimsel uygulamalarla desteklenmiştir. Çalışmalar, düşük enerji ve maksimum verimlilik prensibinin gerçekleştirilmesine dayalı kablosuz sensör ağları üzerinde gerçekleştirilmiştir. Kablosuz sensör ağlari sistemi tasarlandıktan sonra; sensör düğümlerinin enerji tüketimi ve kablosuz ağdaki davranışları test ve analiz edilmiştir. Düşük enerji tüketimi ile sensör düğümleri arasındaki ilişki detaylı olarak değerlendirilmiştir. PIC Tabanlı mikro denetleyiciler sensör düğümlerinin tasarımında kullanılmış ve çok düşük maliyetli tasarım için ultra düşük güçte, nanoWatt teknolojisi ile desteklenen sensör düğümleri tasarlanmıştır. İşleme birimi, bellek birimi ve kablosuz iletişim birimi sensör viii düğümlerine entegre edilmiştir. Tasarlanan sensör düğümünün işletim sistemi PIC C dili ile yazılmıştır ve PIC işletim sistemi nem, sıcaklık, ışığa duyarlılık ve duman sensörü gibi farklı özelliklerin ölçülmesine izin vermiştir. Sensörlerden gelen verilerin merkezi bir konumdan kaydedilmesi ve izlenebilmesi için, C# programlama dili ile bilgisayar yazılımı geliştirilmiştir. Gelişmiş algılayıcı düğümler tarafından alınan kararların uygulanması için yazılım algoritması ve donanım modüllerini içeren karar verme sistemi tasarlanmıştır. Gelişmiş PIC Tabanlı sensör düğümleri, enerji üretimi ve enerji tasarrufu için, güneş enerjisi paneli, şarj edilebilir pil ve süper kapasitör gibi yenilenebilir enerji kaynakları ile benzersiz bir PIC Kontrollü voltaj birimi ile desteklenmiştir. Geliştirilmiş kablosuz sensör ağları sistemi, endüstri uygulamaları, akıllı fabrikalar ve akıllı evler gibi günlük hayat uygulamaları için de kullanılabilecektir. Kablosuz algılayıcı ağlar geniş bir aralıkta kullanılmak üzere tasarlanmıştır. Tezin sonuçları, özellikle yenilenebilir enerji kaynakları ile WSN'nin geliştirilmesine yardımcı olmayı amaçlamaktadır

    High-efficient energy harvesting architecture for self-powered thermal-monitoring wireless sensor node based on a single thermoelectric generator

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    In recent years, research on transducers and system architectures for self-powered devices has gained attention for their direct impact on the Internet of Things in terms of cost, power consumption, and environmental impact. The concept of a wireless sensor node that uses a single thermoelectric generator as a power source and as a temperature gradient sensor in an efficient and controlled manner is investigated. The purpose of the device is to collect temperature gradient data in data centres to enable the application of thermal-aware server load management algorithms. By using a maximum power point tracking algorithm, the operating point of the thermoelectric generator is kept under control while using its power-temperature transfer function to measure the temperature gradient. In this way, a more accurate measurement of the temperature gradient is achieved while harvesting energy with maximum efficiency. The results show the operation of the system through its different phases as well as demonstrate its ability to efficiently harvest energy from a temperature gradient while measuring it. With this system architecture, temperature gradients can be measured with a maximum error of 0.14 ∘ C and an efficiency of over 92% for values above 13 ∘ C and a single transducer.This work was supported by the research Grant PID2019-110142RB-C22 funded by MCIN/ AEI/10.13039/501100011033

    Adaptive Algorithms for Batteryless LoRa-Based Sensors

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    Ambient energy-powered sensors are becoming increasingly crucial for the sustainability of the Internet-of-Things (IoT). In particular, batteryless sensors are a cost-effective solution that require no battery maintenance, last longer and have greater weatherproofing properties due to the lack of a battery access panel. In this work, we study adaptive transmission algorithms to improve the performance of batteryless IoT sensors based on the LoRa protocol. First, we characterize the device power consumption during sensor measurement and/or transmission events. Then, we consider different scenarios and dynamically tune the most critical network parameters, such as inter-packet transmission time, data redundancy and packet size, to optimize the operation of the device. We design appropriate capacity-based storage, considering a renewable energy source (e.g., photovoltaic panel), and we analyze the probability of energy failures by exploiting both theoretical models and real energy traces. The results can be used as feedback to re-design the device to have an appropriate amount energy storage and meet certain reliability constraints. Finally, a cost analysis is also provided for the energy characteristics of our system, taking into account the dimensioning of both the capacitor and solar panel

    Real-time scheduling for energy harvesting sensor nodes

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    Energy harvesting has recently emerged as a feasible option to increase the operating time of sensor networks. If each node of the network, however, is powered by a fluctuating energy source, common power management solutions have to be reconceived. This holds in particular if real-time responsiveness of a given application has to be guaranteed. Task scheduling at the single nodes should account for the properties of the energy source, capacity of the energy storage as well as deadlines of the single tasks. We show that conventional scheduling algorithms (like e.g. EDF) are not suitable for this scenario. Based on this motivation, we have constructed optimal scheduling algorithms that jointly handle constraints from both energy and time domain. Further we present an admittance test that decides for arbitrary task sets, whether they can be scheduled without deadline violations. To this end, we introduce the concept of energy variability characterization curves (EVCC) which nicely captures the dynamics of various energy sources. Simulation results show that our algorithms allow significant reductions of the battery size compared to Earliest Deadline First schedulin

    Energy Neutral Activity Monitoring:Wearables Powered by Smart Inductive Charging Surfaces

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    Wearable technologies play a key role in the shift of traditional healthcare services towards eHealth and self-monitoring. Maintenance overheads, such as regular battery recharging, impose a limitation on the applicability of such technologies in some groups of the population. In this paper, we propose an activity monitoring system that is based on wearable sensors that are powered by textile inductive charging surfaces. By strategically positioning these surfaces on pieces of furniture that are routinely used, the system passively charges the wearable sensor whilst the user is present. As a proof-of-concept example, experiments conducted on a prototype implementation of the system suggest that 36 minutes of daily desktop computer usage are on average sufficient to maintain a wearable sensor energy neutral
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