Smart city development: applying european and international experience to the mediterranean region

Urban development has become a key priority for the countries of the Mediterranean region, both at the national and international level, and within the EIB via its FEMIP prog ramme. The “Smart City” concept (originally defined as the “considered” application of ICT to facilitate efficient, inclusive and integrated urban development, but more broadly to include sustainability, innovation and governance, as well as investments i n public transport, energy efficiency and research facilities) is potentially an important dimension. However, there is a need to forge a framework to connect the technology and public policy aspects with the realities of city management, municipal financi ng and investment programming in the region

Emerging smart meters in electrical distribution systems: Opportunities and challenges

© 2016 IEEE. High penetration of variable and non-programmable distributed generation has brought new challenges to the power system operation and is highlighting the need of a smarter grid. One of the key requirements in this regard is developing and deploying smart metering systems in distribution networks. In this paper we present the actual situation in the Italian distribution networks and we discuss the opportunities and challenges of applying new metering systems and introducing a flexible, multi-utility, multi-service metering architecture. Some off-the-shelf or prototype smart meters, selected to be tested in an ongoing European project, named FLEXMETER, are presented

Emerging Smart Meters in Electrical Distribution Systems: Opportunities and Challenges

High penetration of variable and non-programmable distributed generation has brought new challenges to the power system operation and is highlighting the need of a smarter grid. One of the key requirements in this regard is developing and deploying smart metering systems in distribution networks. In this paper we present the actual situation in the Italian distribution networks and we discuss the opportunities and challenges of applying new metering systems and introducing a flexible, multi-utility, multi-service metering architecture. Some off-the-shelf or prototype smart meters, selected to be tested in an ongoing European project, named FLEXMETER, are presented

Towards green scientific data compression through high-level I/O interfaces

Every HPC system today has to cope with a deluge of data generated by scientific applications, simulations or large- scale experiments. The upscaling of supercomputer systems and infrastructures, generally results in a dramatic increase of their energy consumption. In this paper, we argue that techniques like data compression can lead to significant gains in terms of power efficiency by reducing both network and storage requirements. To that end, we propose a novel methodology for achieving on-the-fly intelligent determination of energy efficient data reduction for a given data set by leveraging state-of-the-art compression algorithms and meta data at application-level I/O. We motivate our work by analyzing the energy and storage saving needs of real-life scientific HPC applications, and review the various compression techniques that can be applied. We find that the resulting data reduction can decrease the data volume transferred and stored by as much as 80% in some cases, consequently leading to significant savings in storage and networking costs

Machine learning for smart building applications: Review and taxonomy

© 2019 Association for Computing Machinery. The use of machine learning (ML) in smart building applications is reviewed in this article. We split existing solutions into two main classes: occupant-centric versus energy/devices-centric. The first class groups solutions that use ML for aspects related to the occupants, including (1) occupancy estimation and identification, (2) activity recognition, and (3) estimating preferences and behavior. The second class groups solutions that use ML to estimate aspects related either to energy or devices. They are divided into three categories: (1) energy profiling and demand estimation, (2) appliances profiling and fault detection, and (3) inference on sensors. Solutions in each category are presented, discussed, and compared; open perspectives and research trends are discussed as well. Compared to related state-of-the-art survey papers, the contribution herein is to provide a comprehensive and holistic review from the ML perspectives rather than architectural and technical aspects of existing building management systems. This is by considering all types of ML tools, buildings, and several categories of applications, and by structuring the taxonomy accordingly. The article ends with a summary discussion of the presented works, with focus on lessons learned, challenges, open and future directions of research in this field

Smart City Dimensions and Associated Risks: Review of literature

Countries have been working on implementing smart city concepts in different regions. The need for the use of information and communication technology in various forms is needed in such cities. There are different dimensions that are to be considered for smart city planning and implementation. This complexity of the dimension, the use of technology, and their integration bring the risk perspectives into the implementation of the smart city concept. If such risks are not adequately understood and addressed, they can create issues in terms of privacy and security and, therefore, the functioning of smart cities. In this review, the identification of dimensions, smart city assessment tools, the available technologies, and the technical and non-technical risk parameters related to smart cities implementation are discussed. The current methods of risk assessment and the possible enhancements are highlighted. The findings of the literature review illustrate that not all smart cities adapt all of the smart city dimensions. The dominant technology used in smart cities' applications is found to be the Internet of Things, Artificial Intelligence, and blockchain. The paper also provides some research directions for the design, implementation, and operation of smart cities. 2021 The Author(s)N\A, There is no funding recived to complete this review paper.Scopus2-s2.0-8511950365

A GIS Open-Data Co-Simulation Platform for Photovoltaic Integration in Residential Urban Areas

The rising awareness of environmental issues and the increase of renewable energy sources (RES) has led to a shift in energy production toward RES, such as photovoltaic (PV) systems, and toward a distributed generation (DG) model of energy production that requires systems in which energy is generated, stored, and consumed locally. In this work, we present a methodology that integrates geographic information system (GIS)-based PV potential assessment procedures with models for the estimation of both energy generation and consumption profiles. In particular, we have created an innovative infrastructure that co-simulates PV integration on building rooftops together with an analysis of households’ electricity demand. Our model relies on high spatiotemporal resolution and considers both shadowing effects and real-sky conditions for solar radiation estimation. It integrates methodologies to estimate energy demand with a high temporal resolution, accounting for realistic populations with realistic consumption profiles. Such a solution enables concrete recommendations to be drawn in order to promote an understanding of urban energy systems and the integration of RES in the context of future smart cities. The proposed methodology is tested and validated within the municipality of Turin, Italy. For the whole municipality, we estimate both the electricity absorbed from the residential sector (simulating a realistic population) and the electrical energy that could be produced by installing PV systems on buildings’ rooftops (considering two different scenarios, with the former using only the rooftops of residential buildings and the latter using all available rooftops). The capabilities of the platform are explored through an in-depth analysis of the obtained results. Generated power and energy profiles are presented, emphasizing the flexibility of the resolution of the spatial and temporal results. Additional energy indicators are presented for the self-consumption of produced energy and the avoidance of CO2 emission

Sustainable modular IoT solution for smart cities applications supported by machine learning algorithms

The Internet of Things (IoT) and Smart Cities are nowadays a big trend, but with the proliferation of these systems several challenges start to appear and put in jeopardy the acceptance by the population, mainly in terms of sustainability and environmental issues. This Thesis introduces a new system composed by a modular IoT smart node that is self-configurable and sustainable with the support of machine learning techniques, as well as the research and development to achieve a innovative solution considering data analysis, wireless communications and hardware and software development. For all these, concepts are introduced, research methodologies, tests and results are presented and discussed as well as the development and implementation. The developed research and methodology shows that Random Forest was the best choice for the data analysis in the self-configuration of the hardware and communication systems and that Edge Computing has an advantage in terms of energy efficiency and latency. The autonomous communication system was able to create a 65% more sustainable node, in terms of energy consumption, with only a 13% decrease in quality of service. The modular approach for the smart node presented advantages in the integration, scalability and implementation of smart cities projects when facing traditional implementations, reducing up to 45% the energy consumption of the overall system and 60% of messages exchanged, without compromising the system performance. The deployment of this new system will help Smart Cities, in a worldwide fashion, to decrease their environmental issues and comply with rules and regulations to reduce CO2 emission.A Internet das Coisas (IoT) e as Cidades Inteligentes são hoje uma grande tendência, mas com a rápida evolução destes sistemas são vários os desafios que põem em causa a sua aceitação por parte das populações, maioritariamente devido a problemas ambientais e de sustentabilidade. Esta Tese introduz um novo sistema composto por nós de IoT inteligentes que são auto-configuáveis e sustentáveis suportados por de aprendizagem automática, e o trabalho de investigação e desenvolvimento para se obter uma solução inovadora que considera a análise de dados, comunicações sem fios e o desenvolvimento do hardware e software. Para todos estes, os conceitos chave são introduzidos, as metodologias de investigação, testes e resultados são apresentados e discutidos, bem como todo o desenvolvimento e implementação. Através do trabalho desenvolvido mostra-se que as Árvores Aleatórias são a melhor escolha para análise de dados em termos da autoconfiguração do hardware e sistema de comunicações e que a computação nos nós tem uma vantagem em termos de eficiência energética e latência. O sistema de configuração autónoma de comunicações foi capaz de criar um nós 65% mais sustentável, em termos en- ergéticos, comprometendo apenas em 13% a qualidade do servi ̧co. A solução modular do nó inteligente apresentou vantagens na integração, escalabilidade e implementação de projectos para Cidades Inteligentes quando comparado com soluções tradicionais, reduzindo em 45% o consumo energético e 60% a troca de mensagens, sem comprometer a qualidade do sistema. A implementação deste novo sistema irá ajudar as cidades inteligentes, em todo o mundo, a diminuir os seus problemas ambientais e a cumprir com as normas e regulamentos para reduzir as emissões de CO2

Educational Technology and Related Education Conferences for June to December 2015

The 33rd edition of the conference list covers selected events that primarily focus on the use of technology in educational settings and on teaching, learning, and educational administration. Only listings until December 2015 are complete as dates, locations, or Internet addresses (URLs) were not available for a number of events held from January 2016 onward. In order to protect the privacy of individuals, only URLs are used in the listing as this enables readers of the list to obtain event information without submitting their e-mail addresses to anyone. A significant challenge during the assembly of this list is incomplete or conflicting information on websites and the lack of a link between conference websites from one year to the next