33 research outputs found

    A low power IoT sensor node architecture for waste management within smart cities context

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    This paper focuses on the realization of an Internet of Things (IoT) architecture to optimize waste management in the context of Smart Cities. In particular, a novel typology of sensor node based on the use of low cost and low power components is described. This node is provided with a single-chip microcontroller, a sensor able to measure the filling level of trash bins using ultrasounds and a data transmission module based on the LoRa LPWAN (Low Power Wide Area Network) technology. Together with the node, a minimal network architecture was designed, based on a LoRa gateway, with the purpose of testing the IoT node performances. Especially, the paper analyzes in detail the node architecture, focusing on the energy saving technologies and policies, with the purpose of extending the batteries lifetime by reducing power consumption, through hardware and software optimization. Tests on sensor and radio module effectiveness are also presented

    A field-measurements-based LoRa network planning tool

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    Long range (LoRa) transmission technology enables energy-constrained devices such as the tiny sensor systems used in internet-of-things applications that are distributed over wide areas while still being able to establish appropriate connectivity. This has resulted in the development of an exponentially increasing number of different solutions and services based on LoRa, be they dedicated to the long-term monitoring of distributed plants and infrastructures or to human-centred applications such as safety-oriented sensor systems for use in the workplace. In dense LoRa networks, predicting the number of supported nodes in relation to their position and the propagation environment is essential for ensuring reliable and stable communication and minimising costs. In this paper, after comparing different path loss models based on a field measurement campaign for LoRa received signal strength indicator values within a university campus, two main modifications of the LoRa simulator tool were implemented. These were aimed at improving the accuracy of the prediction of the number of sustainable nodes in relation to the target data extraction rate set. The simulations based on field measurements demonstrated that through an improved path loss evaluation and the use of three gateways, the number of nodes could be increased theoretically from around 100 to around 6,000

    Route planning using wireless sensor network for garbage collection in COVID-19 pandemic

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    Garbage collection is a responsibility faced by all cities and, if not properly carried out, can generate greater costs or sanitary problems. Considering the sanitary situation due to the COVID-19 pandemic, it is necessary to take sanitary safety measures to prevent its spread. The challenge of the present work is to provide an efficient and effective solution that guarantees a garbage collection that optimizes the use of resources and prioritizes the attention to garbage containers located in or near contagion risk zones. To this end, this research proposes the integration of a basic garbage monitoring system, consisting of a wireless sensor network, and a route planning system that implements the decomposition of the Vehicle Routing problem into the subproblems of clustering and sequencing of containers using the K-Means and Ant Colony algorithms. For the monitoring of garbage, a significant reduction in the measurement error of waste level in the containers was achieved compared to other authors. About route planning, adequate error ranges were obtained in the calculation of the optimal values of distance traveled and travel time indicators with respect to an exhaustive enumeration of routes

    Smart textile waste collection system – Dynamic route optimization with IoT

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    Increasing textile production is associated with an environmental burden which can be decreased with an improved recycling system by digitalization. The collection of textiles is done with so-called curbside bins. Sensor technologies support dynamic-informed decisions during route planning, helping predict waste accumulation in bins, which is often irregular and difficult to predict. Therefore, dynamic route-optimization decreases the costs of textile collection and its environmental load. The existing research on the optimization of waste collection is not based on real-world data and is not carried out in the context of textile waste. The lack of real-world data can be attributed to the limited availability of tools for long-term data collection. Consequently, a system for data collection with flexible, low-cost, and open-source tools is developed. The viability and reliability of such tools are tested in practice to collect real-world data. This research demonstrates how smart bins solution for textile waste collection can be linked to a dynamic route-optimization system to improve overall system performance. The developed Arduino-based low-cost sensors collected actual data in Finnish outdoor conditions for over twelve months. The viability of the smart waste collection system was complemented with a case study evaluating the collection cost of the conventional and dynamic scheme of discarded textiles. The results of this study show how a sensor-enhanced dynamic collection system reduced the cost 7.4% compared with the conventional one. We demonstrate a time efficiency of −7.3% and that a reduction of 10.2% in CO2 emissions is achievable only considering the presented case study.publishedVersionPeer reviewe

    The things network e infraestrutura de iluminação pública : gestão energética e monitorização ambiental

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    A procura continua de soluções cada vez mais sustentáveis em todas as áreas de uma cidade chegou até à iluminação pública. A evolução envolve a mudança para tecnologia mais eficiente, como aquela baseada em LED, em combinação com luminárias inteligentes que, para além de serem mais eficientes, possibilitam o seu controlo com muito mais precisão do que era possível anteriormente. Este documento é o relatório de trabalho de projeto para a obtenção do grau de Mestre em Informática e Sistemas pelo Instituto Superior de Engenharia de Coimbra e considera a oportunidade de usar estas luminárias para mais do que apenas a iluminação: gerir o consumo energético, monitorizar o ambiente e até controlar outros equipamentos. Este trabalho foca-se na problemática da monitorização da poluição sonora e como a internet das coisas (IoT) pode ajudar a atualizar informação de forma muito mais rápida do que as metodologias usadas atualmente: de uma atualização medida em anos para uma atualização medida em minutos. Para além disso vai um pouco mais além mantendo os custos da proposta infraestrutura e das comunicações o mais baixos possível. Este projeto começou por pesquisar sobre os conceitos envolvidos e tecnologias disponíveis, estudado o fenómeno da pressão sonora, avaliadas as soluções existentes bem como as suas vantagens e desvantagens. Em seguida avaliou-se a performance de vários microfones de baixo custo comummente encontrados no mercado. A ligação à The Things Network (TTN) foi descrita e testada e, finalmente, proposto um modelo de base de dados, uma REST API (Application Programming Interface) e uma interface de utilizador baseada em páginas web. Com esta solução proposta neste trabalho, é possível criar uma solução de monitorização da poluição sonora que permite a atualização em quase tempo real, que resulta num serviço de utilidade pública, uma ferramenta para otimizar a gestão das cidades. Salienta se que a solução assim proposta é modular e, portanto, pode integrar o sistema de gestão da iluminação pública, outros sensores ambientais, ou mesmo atuadores, possibilitando assim benefícios ambientais e financeiros. Permite ainda a disponibilização da informação recolhida aos seus cidadãos

    Design, analysis and remote monitoring of a solar powered orphan oil well pumping system in Nigeria

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    This thesis explores the issue of orphaned wells, which are abandoned oil and gas wells left uncapped, leading to the release of greenhouse gases, including methane and hydrogen sulphide gas H₂S, which is lethal to humans into the atmosphere. These wells contribute significantly to global warming, as methane is a potent greenhouse gas with a high heat-trapping capability, unfortunately due to it cost an average of 100,000CAD per well for oil well plugging, most oil industry abandon these wells. The research identifies cost-effective strategies to mitigate the impact of abandoned wells using renewable technology, specifically focusing on a comprehensive system sizing approach for Olobiri oil well 17. To address the problem, the study recommends the use of solar-powered pumps to remove the remnants of oil from the wells. PVsyst software is employed to determine the appropriate pump size if the system ran continuously or solar peak hours of the location. The results demonstrate that a 5-hour running time yields higher system efficiency compared to continuous running time. Based on HOMERpro optimization result, a 50kW PV unit and 54.9kW batteries are recommended for the system setup, resulting in improved efficiency and cost-effective option during the 5-hour operation with an overall efficiency of 11.4% and pump efficiency was 37.9% compared to a continuous flow system efficiency of 5%, and the pump efficiency of 11%. For monitoring and data logging purposes, the addition of PLX DAQ aids in real-time monitoring system for the design characteristics such as PV voltage and current, inverter AC output, oil level and temperature. This low-cost data logging system allows for easy maintenance and provides valuable data for further analysis since the PLX DAQ is a Microsoft Excel’s add-on. Also, due to the site location and the specification describing the location, Lora Technology is implemented for real time monitoring, which is independent on the internet network. In conclusion, this research highlights the importance of addressing orphaned wells' environmental impact and proposes a viable solution for capping using renewable technology, particularly solar-powered pumps, to mitigate greenhouse gas emissions and the potential hazards posed by abandoned wells

    Energy-Sustainable IoT Connectivity: Vision, Technological Enablers, Challenges, and Future Directions

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    Technology solutions must effectively balance economic growth, social equity, and environmental integrity to achieve a sustainable society. Notably, although the Internet of Things (IoT) paradigm constitutes a key sustainability enabler, critical issues such as the increasing maintenance operations, energy consumption, and manufacturing/disposal of IoT devices have long-term negative economic, societal, and environmental impacts and must be efficiently addressed. This calls for self-sustainable IoT ecosystems requiring minimal external resources and intervention, effectively utilizing renewable energy sources, and recycling materials whenever possible, thus encompassing energy sustainability. In this work, we focus on energy-sustainable IoT during the operation phase, although our discussions sometimes extend to other sustainability aspects and IoT lifecycle phases. Specifically, we provide a fresh look at energy-sustainable IoT and identify energy provision, transfer, and energy efficiency as the three main energy-related processes whose harmonious coexistence pushes toward realizing self-sustainable IoT systems. Their main related technologies, recent advances, challenges, and research directions are also discussed. Moreover, we overview relevant performance metrics to assess the energy-sustainability potential of a certain technique, technology, device, or network and list some target values for the next generation of wireless systems. Overall, this paper offers insights that are valuable for advancing sustainability goals for present and future generations.Comment: 25 figures, 12 tables, submitted to IEEE Open Journal of the Communications Societ

    Tecnologias IoT para pastoreio e controlo de postura animal

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    The unwanted and adverse weeds that are constantly growing in vineyards, force wine producers to repeatedly remove them through the use of mechanical and chemical methods. These methods include machinery such as plows and brushcutters, and chemicals as herbicides to remove and prevent the growth of weeds both in the inter-row and under-vine areas. Nonetheless, such methods are considered very aggressive for vines, and, in the second case, harmful for the public health, since chemicals may remain in the environment and hence contaminate water lines. Moreover, such processes have to be repeated over the year, making it extremely expensive and toilsome. Using animals, usually ovines, is an ancient practice used around the world. Animals, grazing in vineyards, feed from the unwanted weeds and fertilize the soil, in an inexpensive, ecological and sustainable way. However, sheep may be dangerous to vines since they tend to feed on grapes and on the lower branches of the vines, which causes enormous production losses. To overcome that issue, sheep were traditionally used to weed vineyards only before the beginning of the growth cycle of grapevines, thus still requiring the use of mechanical and/or chemical methods during the remainder of the production cycle. To mitigate the problems above, a new technological solution was investigated under the scope of the SheepIT project and developed in the scope of this thesis. The system monitors sheep during grazing periods on vineyards and implements a posture control mechanism to instruct them to feed only from the undesired weeds. This mechanism is based on an IoT architecture, being designed to be compact and energy efficient, allowing it to be carried by sheep while attaining an autonomy of weeks. In this context, the thesis herein sustained states that it is possible to design an IoT-based system capable of monitoring and conditioning sheep’s posture, enabling a safe weeding process in vineyards. Moreover, we support such thesis in three main pillars that match the main contributions of this work and that are duly explored and validated, namely: the IoT architecture design and required communications, a posture control mechanism and the support for a low-cost and low-power localization mechanism. The system architecture is validated mainly in simulation context while the posture control mechanism is validated both in simulations and field experiments. Furthermore, we demonstrate the feasibility of the system and the contribution of this work towards the first commercial version of the system.O constante crescimento de ervas infestantes obriga os produtores a manter um processo contínuo de remoção das mesmas com recurso a mecanismos mecânicos e/ou químicos. Entre os mais populares, destacam-se o uso de arados e roçadores no primeiro grupo, e o uso de herbicidas no segundo grupo. No entanto, estes mecanismos são considerados agressivos para as videiras, assim como no segundo caso perigosos para a saúde pública, visto que os químicos podem permanecer no ambiente, contaminando frutos e linhas de água. Adicionalmente, estes processos são caros e exigem mão de obra que escasseia nos dias de hoje, agravado pela necessidade destes processos necessitarem de serem repetidos mais do que uma vez ao longo do ano. O uso de animais, particularmente ovelhas, para controlar o crescimento de infestantes é uma prática ancestral usada em todo o mundo. As ovelhas, enquanto pastam, controlam o crescimento das ervas infestantes, ao mesmo tempo que fertilizam o solo de forma gratuita, ecológica e sustentável. Não obstante, este método foi sendo abandonado visto que os animais também se alimentam da rama, rebentos e frutos da videira, provocando naturais estragos e prejuízos produtivos. Para mitigar este problema, uma nova solução baseada em tecnologias de Internet das Coisas é proposta no âmbito do projeto SheepIT, cuja espinha dorsal foi construída no âmbito desta tese. O sistema monitoriza as ovelhas enquanto estas pastoreiam nas vinhas, e implementam um mecanismo de controlo de postura que condiciona o seu comportamento de forma a que se alimentem apenas das ervas infestantes. O sistema foi incorporado numa infraestrutura de Internet das Coisas com comunicações sem fios de baixo consumo para recolha de dados e que permite semanas de autonomia, mantendo os dispositivos com um tamanho adequado aos animais. Neste contexto, a tese suportada neste trabalho defende que é possível projetar uma sistema baseado em tecnologias de Internet das Coisas, capaz de monitorizar e condicionar a postura de ovelhas, permitindo que estas pastem em vinhas sem comprometer as videiras e as uvas. A tese é suportada em três pilares fundamentais que se refletem nos principais contributos do trabalho, particularmente: a arquitetura do sistema e respetivo sistema de comunicações; o mecanismo de controlo de postura; e o suporte para implementação de um sistema de localização de baixo custo e baixo consumo energético. A arquitetura é validada em contexto de simulação, e o mecanismo de controlo de postura em contexto de simulação e de experiências em campo. É também demonstrado o funcionamento do sistema e o contributo deste trabalho para a conceção da primeira versão comercial do sistema.Programa Doutoral em Informátic

    IoT Applications Computing

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    The evolution of emerging and innovative technologies based on Industry 4.0 concepts are transforming society and industry into a fully digitized and networked globe. Sensing, communications, and computing embedded with ambient intelligence are at the heart of the Internet of Things (IoT), the Industrial Internet of Things (IIoT), and Industry 4.0 technologies with expanding applications in manufacturing, transportation, health, building automation, agriculture, and the environment. It is expected that the emerging technology clusters of ambient intelligence computing will not only transform modern industry but also advance societal health and wellness, as well as and make the environment more sustainable. This book uses an interdisciplinary approach to explain the complex issue of scientific and technological innovations largely based on intelligent computing
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