Big data analytics:Computational intelligence techniques and application areas

Big Data has significant impact in developing functional smart cities and supporting modern societies. In this paper, we investigate the importance of Big Data in modern life and economy, and discuss challenges arising from Big Data utilization. Different computational intelligence techniques have been considered as tools for Big Data analytics. We also explore the powerful combination of Big Data and Computational Intelligence (CI) and identify a number of areas, where novel applications in real world smart city problems can be developed by utilizing these powerful tools and techniques. We present a case study for intelligent transportation in the context of a smart city, and a novel data modelling methodology based on a biologically inspired universal generative modelling approach called Hierarchical Spatial-Temporal State Machine (HSTSM). We further discuss various implications of policy, protection, valuation and commercialization related to Big Data, its applications and deployment

O uso da análise de dados para resolver problemas de habitação em Lagos, Nigéria

The constant growth in population has made a significant impact on housing and accommodation in Lagos Nigeria and the shortage and the problem of distribution of housing for both homes and offices and urban planning, in general, has been a challenge in African cities in general. Housing a fast-developing city with a population in record speed increase like that constated in Lagos needs to be reviewed most especially with the fast rate of digital development and internet access. The United Nations (UN) has ranked Nigeria among the countries that will drive the growth of cities over the next four decades, posing challenging challenges in terms of job creation, energy consumption and infrastructure, as well as housing. This thesis aims to explore a maximum of data on housing, the development of the internet of things and how these perspectives envisaged by the government. One of the main sources of information of our century is big data, this element is extracted from the opinions of the inhabitants of Lagos on housing problems, their practice and information available in public services. The goal of using data is to improve practices, anticipate problems, etc. But to do this, it is necessary to digitally collect useful information to help public policies to the deployment of housing using these datasets. The results of the thesis and the prospects for research or the deployment of applications, software or models could be useful to the Lagos government to manage the challenges of the future related to the expansion of the population, the disappearance of surfaces to urbanize and more global issues such as climate change and its effects on the population.O crescimento constante da população cosou um impacto significativo nas moradias e acomodações em Lagos, na Nigéria, e a escases e o problema da distribuição de moradias para residências e escritórios, e o planetamento urbano, em general, tem sido um desafio nas cidades africanas em general. Viver dentro de uma cidade em rápido desenvolvimento, com uma população em aumento recorde de velocidade como a constatada em Lagos, precisa ser revisado principalmente com a rápida taxa de desenvolvimento digital e acesso o Internet. As Nações Unidas (ONU) classificaram a Nigéria entre os país que impulsionarão o crescimento das cidades nas próximas quatro décadas, apresentando desafios desafiadores em termos de criação de empregos, consumo de energia e infraestrutura, além de moradias. Esta tese visa explorar o máximo de dados sobre habitação, o desenvolvimento da Internet das coisas e como essas perspectivas são vistas pelo governo. Uma das principais fontes de informação do nosso século é o big data, esse elemento é extraído das opiniões dos habitantes de Lagos sobre problemas habitacionais, sua prática e informações disponíveis nos serviços públicos. O objetivo do uso dos dados é melhorar práticas, antecipar problemas etc. Mas, para isso, é necessário coletar digitalmente informações úteis para ajudar políticas públicas a implantação de moradias usando os conjuntos de dados. Os resultados da tese e as perspectivas de pesquisa o implantação de aplicativos, software o modelos podem ser úteis ao governo de Lagos para gerenciar os desafios do futuro relacionados a expansão da população, ao desaparecimento de superfícies a serem urbanizadas e mais globais questões como as mudanças climáticas e seus efeitos sobre a população

A novel Big Data analytics and intelligent technique to predict driver's intent

Modern age offers a great potential for automatically predicting the driver's intent through the increasing miniaturization of computing technologies, rapid advancements in communication technologies and continuous connectivity of heterogeneous smart objects. Inside the cabin and engine of modern cars, dedicated computer systems need to possess the ability to exploit the wealth of information generated by heterogeneous data sources with different contextual and conceptual representations. Processing and utilizing this diverse and voluminous data, involves many challenges concerning the design of the computational technique used to perform this task. In this paper, we investigate the various data sources available in the car and the surrounding environment, which can be utilized as inputs in order to predict driver's intent and behavior. As part of investigating these potential data sources, we conducted experiments on e-calendars for a large number of employees, and have reviewed a number of available geo referencing systems. Through the results of a statistical analysis and by computing location recognition accuracy results, we explored in detail the potential utilization of calendar location data to detect the driver's intentions. In order to exploit the numerous diverse data inputs available in modern vehicles, we investigate the suitability of different Computational Intelligence (CI) techniques, and propose a novel fuzzy computational modelling methodology. Finally, we outline the impact of applying advanced CI and Big Data analytics techniques in modern vehicles on the driver and society in general, and discuss ethical and legal issues arising from the deployment of intelligent self-learning cars

Smart Grid Communications: Overview of Research Challenges, Solutions, and Standardization Activities

Optimization of energy consumption in future intelligent energy networks (or Smart Grids) will be based on grid-integrated near-real-time communications between various grid elements in generation, transmission, distribution and loads. This paper discusses some of the challenges and opportunities of communications research in the areas of smart grid and smart metering. In particular, we focus on some of the key communications challenges for realizing interoperable and future-proof smart grid/metering networks, smart grid security and privacy, and how some of the existing networking technologies can be applied to energy management. Finally, we also discuss the coordinated standardization efforts in Europe to harmonize communications standards and protocols.Comment: To be published in IEEE Communications Surveys and Tutorial

AI and digitalization as enablers of flexible power system

Abstract. The Paris climate agreement obligate energy and power sector to reduce greenhouse gasses even though at the same time the global power demand increases. This leads to need to increase emission-free power generation with renewable energy sources (RES). Wind- and solar power technologies have developed significantly and price of power generated by them has decreased clearly in recent years. These factors have led to large-scale installations globally. However transitioning towards RES, such as wind and solar power, poses a challenge, since supply and demand in the electric power system must be equal at all times, but wind- and solar power are non-adjustable. These factors leads to need of finding flexibility from elsewhere e.g. from demand side, but also from storage systems. Purpose of this thesis is to analyze electric power system’s flexibility and how it can be increased by employing digital technologies including artificial intelligence (AI). This research was done by using qualitative conceptual research method, where data is collected until saturation point is reached. Data was collected from scientific journals and relevant sources to form conceptual understanding of current state and future possibilities. With digital technologies and artificial intelligence, companies can create new types of products, services and business models, which create more value for the customer. At the same time, these new solutions can improve the electric power system and create needed flexibility. The thesis studied these novel solutions and discussed practical implementation of three example cases in more detail. Digital solutions are rising into more significant role and they act as enablers for greener electric power system.Tekoäly ja digitalisaatio joustavan sähköjärjestelmän mahdollistajana. Tiivistelmä. Pariisin ilmastosopimus velvoittaa energia- ja sähkösektorit rajoittamaan kasvihuonepäästöjä, vaikka samaan aikaan sähkön kysyntä globaalisti kasvaa. Tämä johtaa tarpeeseen lisätä päästötöntä sähköntuotantoa uusiutuvilla energialähteillä. Tuuli- ja aurinkovoimateknologiat ovat kehittyneet ja niillä tuotetun sähkön hinta on laskenut selvästi viime vuosina. Nämä seikat ovat johtaneet niiden laajamittaiseen käyttöönottoon maailmanlaajuisesti. Siirtyminen näihin energiamuotoihin tuottaa haasteita sähköjärjestelmälle, sillä sähköjärjestelmässä tuotannon ja kulutuksen tulee olla tasapainossa koko ajan, mutta tuuli- aurinkovoiman sähköntuotantoa ei pystytä säätämään. Nämä seikat ovat johtaneet tarpeeseen löytää joustavuutta sähköjärjestelmän muista osista mm. kysynnästä, mutta myös varastoinnista. Tämän tutkimuksen tavoitteena on tutkia ja analysoida, miten sähköjärjestelmän joustavuutta voidaan lisätä digitaalisten teknologioiden, erityisesti tekoälyn avulla. Tutkimus on tehty laadullisella konseptuaalisella tutkimusmenetelmällä, jossa datan keräystä on jatkettu saturaatiopisteen saavuttamiseen asti. Data on kerätty tiedejulkaisuista ja muista tutkimuksen kannalta merkityksellisistä lähteistä, joiden pohjalta on voitu muodostaa konseptuaalinen ymmärrys tämän hetken tilasta ja tulevaisuuden mahdollisuuksista. Digitaalisten teknologioiden ja tekoälyn avulla yritykset voivat luoda uudenlaisia tuotteita, palveluita ja liiketoimintamalleja, jotka tuottavat aikaisempaa enemmän arvoa asiakkaalle. Samalla nämä uudet ratkaisut pystyvät parantamaan sähköjärjestelmää ja luomaan tarvittavaa joustavuutta. Tässä työssä tutustuttiin näihin uusiin ratkaisuihin ja tutkittiin myös niiden käytännön toimivuutta analysoimalla kolmea esimerkkitapausta tarkemmin. Digitaaliset ratkaisut ovat nousemassa merkittävään osaan sähköjärjestelmää ja niillä, kuten monella muullakin digitaalisiin teknologioihin pohjautuvilla ratkaisuilla voidaan mahdollistaa ympäristöystävällisempi sähköjärjestelmä

A Taxonomy for Management and Optimization of Multiple Resources in Edge Computing

Edge computing is promoted to meet increasing performance needs of data-driven services using computational and storage resources close to the end devices, at the edge of the current network. To achieve higher performance in this new paradigm one has to consider how to combine the efficiency of resource usage at all three layers of architecture: end devices, edge devices, and the cloud. While cloud capacity is elastically extendable, end devices and edge devices are to various degrees resource-constrained. Hence, an efficient resource management is essential to make edge computing a reality. In this work, we first present terminology and architectures to characterize current works within the field of edge computing. Then, we review a wide range of recent articles and categorize relevant aspects in terms of 4 perspectives: resource type, resource management objective, resource location, and resource use. This taxonomy and the ensuing analysis is used to identify some gaps in the existing research. Among several research gaps, we found that research is less prevalent on data, storage, and energy as a resource, and less extensive towards the estimation, discovery and sharing objectives. As for resource types, the most well-studied resources are computation and communication resources. Our analysis shows that resource management at the edge requires a deeper understanding of how methods applied at different levels and geared towards different resource types interact. Specifically, the impact of mobility and collaboration schemes requiring incentives are expected to be different in edge architectures compared to the classic cloud solutions. Finally, we find that fewer works are dedicated to the study of non-functional properties or to quantifying the footprint of resource management techniques, including edge-specific means of migrating data and services.Comment: Accepted in the Special Issue Mobile Edge Computing of the Wireless Communications and Mobile Computing journa

Industry 4.0 as a strategy related to the United Nations Sustainable Development Goals in Norwegian Industries

The new industrial revolution, known as Industry 4.0, is becoming increasingly important within Norwegian companies. Industry 4.0 is a future-oriented strategy and could be significant for maintaining and improving companies’ competitiveness. Further, the importance of sustainability has increased in the last few years, which resulted in the United Nations (UN) Sustainable Development Goals (SDGs) and associated subgoals. Additionally, the triple bottom line (TBL) has been developed based on the term sustainability. This thesis aims to research how Industry 4.0 as a strategy is related to the UN SDGs within Norwegian industries. As there exist limited studies related to Industry 4.0 combining Sustainability within Norwegian industries, a qualitative method is conducted. A literature study is executed based on a comprehensive literature search to acquire relevant data. This thesis consists of Industry 4.0 technologies provided by Bai, Dallasega, Orzes, and Sarkis (2020), and Oztemel and Gursev (2020), which evaluate Industry 4.0 technologies from a sustainable perspective. Further, the thesis analyzes the UN subgoals based on their relevance within Norwegian companies utilizing Industry 4.0 technologies. The relevant subgoals and Industry 4.0 technologies are linked with the TBL to generate the finding of this thesis. Industry 4.0 allows for automated processes and decreased human interaction. Conclusively, it decreases the cost of human labor, increases production efficiency, and reduces waste. Additionally, rural companies in Norway could experience the demand for workforce exceeding the supply due to rural flight. Thus, Industry 4.0 is related to economic sustainability and SDG8.2. Further, automated processes reduce employee’s exposure to dangerous work tasks and are therefore related to social sustainability and SDG3.d. Industry 4.0 increases the demand for a qualified workforce, indicating reskilling of employees. Social sustainability and SDG4.4 are thus correlated. The technologies’ facilitation for local production results in shorter transportation routes, thus, reducing gas emissions. This is related to environmental sustainability and SDG9.4. Industry 4.0 also correlates with SDG12.5 and environmental sustainability, as it allows Norwegian companies to forecast demand and reduce overproduction