Recommender systems for smart cities

Among other conceptualizations, smart cities have been defined as functional urban areas articulated by the use of Information and Communication Technologies (ICT) and modern infrastructures to face city problems in efficient and sustainable ways. Within ICT, recommender systems are strong tools that filter relevant information, upgrading the relations between stakeholders in the polity and civil society, and assisting in decision making tasks through technological platforms. There are scientific articles covering recommendation approaches in smart city applications, and there are recommendation solutions implemented in real world smart city initiatives. However, to the best of our knowledge, there is not a comprehensive review of the state of the art on recommender systems for smart cities. For this reason, in this paper we present a taxonomy of smart city features, dimensions, actions and goals, and, according to these variables, we survey the existing literature on recommender systems. As a result of our survey, we do not only identify and analyze main research trends, but also show current opportunities and challenges where personalized recommendations could be exploited as solutions for citizens, firms and public administrations.     

Adaptive and context-aware service composition for IoT-based smart cities

Smart Cities are advancing towards an instrumented, integrated, and intelligent living space, where Internet of Things (IoT), mobile technologies and next generation networks are expected to play a key role. In smart cities, numerous IoT-based services are likely to be available and a key challenge is to allow mobile users perform their daily tasks dynamically, by integrating the services available in their vicinity. Semantic Service Oriented Architectures (SSOA) abstract the environment’s services and their functionalities as Semantic Web Services (SWS). However, existing service composition approaches based on SSOA do not support dynamic reasoning on user tasks and service behaviours to deal with the heterogeneity of IoT domains. In this paper, we present an adaptive service composition framework that supports such dynamic reasoning. The framework is based on wEASEL, an abstract service model representing services and user tasks in terms of their signature, specification (i.e., context-aware pre-conditions, post-conditions and effects) and conversation (i.e., behaviour with related data-flow and context-flow constraints). To evaluate our composition framework, we develop a novel OWLS-TC4-based testbed by combining simple and composite services. The evaluation shows that our wEASEL-based system performs more accurate composition and allows end-users to discover and investigate more composition opportunities than other approaches.     

Serious gaming as a means of facilitating truly smart cities: a narrative review

ABSTRACT

The term ‘smart cities’ is contested: its interpretation is becoming ever broader, often to accommodate commercial interests. Since cities are made up of individuals, all of whom are guided by their own world views and attitudes, the residual question is not ‘what should we do?’ but ‘how should we do it and how should we encourage and enable everyone to join in?’ By exploring the ways that gamification can be used to understand the effects of ‘smart initiatives’ on cities and their operation, it was concluded that gaming has considerable potential to affect individual and societal practices by profoundly influencing the gamers themselves, while technology and the game design itself play a central role to how gamification is implemented and used. This paper proposes one way of both creating cities to which citizens aspire and delivering a beneficial change in attitudes and behaviours to make such cities work. We propose that way-finding games should be developed as the most appropriate tools for participation. Designing such serious games with sustainability, resilience and liveability agendas in mind, encouraging widespread citizen participation as gamers, and taking cognisance of the outcomes would lead to both smarter citizens and smarter cities.     

Deep learning for pedestrian collective behavior analysis in smart cities: A model of group trajectory outlier detection

This paper introduces a new model to identify collective abnormal human behaviors from large pedestrian data in smart cities. To accurately solve the problem, several algorithms have been proposed in this paper. These can be split into two categories. First, algorithms based on data mining and knowledge discovery, which study the different correlation among human behavioral data, and identify the collective abnormal human behavior from knowledge extracted. Secondly, algorithms exploring convolution deep neural networks, which learn different features of historical data to determine the collective abnormal human behaviors. Experiments on an actual human behaviors database have been carried out to demonstrate the usefulness of the proposed algorithms. The results show that the deep learning solution outperforms both data mining as well as the state-of-the-art solutions in terms of runtime and accuracy performance. In particular, for large datasets, the accuracy of the deep learning solution reaches 88%, however other solutions do not exceed 81%. Additionally, the runtime of the deep learning solution is below 50 seconds, whereas other solutions need more than 80 seconds for analyzing the same database.     

Emerging ICT concepts for smart,safe and sustainable industrial systems

This editorial introduces the special issue on Emerging Information and Communication Technology (ICT) concepts for smart, safe and sustainable industrial systems in the Elsevier journal Computers in Industry. The 13 papers in this special issue were selected because of their high quality and also because they propose emerging ICT solutions that address at least one of the three dimensions we suggest as basic requirements to design usable future Industrial Systems that must be safe, smart and sustainable. Previous global discussions about the state of the art with regard to the topic of this special issue are provided, as well as exploratory guidelines for future research in this area.     

A structural service innovation approach for designing smart product service systems: Case study of smart beauty service

Smart Product-service systems (PSS) are the emerging type of PSS that offer market value and dynamic intelligence combining products and services as solutions to consumers based on digital technology. To design a smart PSS with an effective way, a structural design approach is required. Nevertheless, only a few existing researchers discussed this topic. Aiming to bridge this gap, an integrated way is proposed for smart PSS design. This study refines a generic approach for structural service innovation approach which integrates the advantage of PSS engineering and service engineering for designing smart product service systems. The structural design approach is based on the Theory of Inventive Problem Solving (TRIZ) incorporating with service blueprint named PRR method. Three design phases are demonstrated as verification of the PRR method by an elaborated case study of the smart beauty service. Based on PRR, three key design phases are integrated, i.e., (1) problem definition, (2) resolution generation, and (3) resolution design. Empirical results and implications are collected and discussed to obtain valuable insights for value creation.     

The HORSE framework: A reference architecture for cyber-physical systems in hybrid smart manufacturing

In the Industry 4.0 era, manufacturers strive to remain competitive by using advanced technologies such as collaborative robots, automated guided vehicles, augmented reality support and smart devices. However, only if these technological advancements are integrated into their system context in a seamless way, they can deliver their full potential to a manufacturing organization. This integration requires a system architecture as a blueprint for positioning and interconnection of the technologies. For this purpose, the HORSE framework, resulting from the HORSE EU H2020 project, has been developed to act as a reference architecture of a cyber-physical system to integrate various Industry 4.0 technologies and support hybrid manufacturing processes, i.e., processes in which human and robotic workers collaborate. The architecture has been created using design science research, based on well-known software engineering frameworks, established manufacturing domain standards and practical industry requirements. The value of a reference architecture is mainly established by application in practice. For this purpose, this paper presents the application and evaluation of the HORSE framework in 10 manufacturing plants across Europe, each with its own characteristics. Through the physical deployment and demonstration, the framework proved its goal to be basis for the well-structured design of an operational smart manufacturing cyber-physical system that provides horizontal, cross-functional management of manufacturing processes and vertical control of heterogeneous technologies in work cells. We report on valuable insights on the difficulties to realize such systems in specific situations. The experiences form the basis for improved adoption, further improvement and extension of the framework. In sum, this paper shows how a reference architecture framework supports the structured application of Industry 4.0 technologies in manufacturing environments that so far have relied on more traditional digital technology.     

Mutual authentication scheme for smart devices in IoT-enabled smart home systems

The emergence of Internet of Things (IoT) technology has yielded a firm technical basis for the construction of a smart home. A smart home system offers occupants the convenience of remote control and automation of household systems. However, there are also potential security risks associated with smart home technologies. The security of users in a smart home environment is related to their life and possessions. A significant amount of research has been devoted to studying the security risks associated with IoT-enabled smart home systems. The increasing intelligence of devices has led to a trend of independent authentication between devices in smart homes. Therefore, mutual authentication for smart devices is essential in smart home systems. In this paper, a mutual authentication scheme is proposed for smart devices in IoT-enabled smart home systems. Signature updates are provided for each device. In addition, with the assistance of a home gateway, the proposed scheme can enable devices to verify the identity of each other. According to the analysis, the proposed scheme is secure against a forged SD or a semi-trusted HG. The computational cost of the proposed scheme in the simulation is acceptable for the application in smart home systems.     

Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments

Steadily increasing urbanization is causing significant economic and social transformations in urban areas, posing several challenges related to city management and services. In particular, in cities with higher crime rates, effectively providing for public safety is an increasingly complex undertaking. To handle this complexity, new technologies are enabling police departments to access growing volumes of crime-related data that can be analyzed to understand patterns and trends. These technologies have potentially to increase the efficient deployment of police resources within a given territory and ultimately support more effective crime prevention. This paper presents a predictive approach based on spatial analysis and auto-regressive models to automatically detect high-risk crime regions in urban areas and to reliably forecast crime trends in each region. The algorithm result is a spatio-temporal crime forecasting model, composed of a set of crime-dense regions with associated crime predictors, each one representing a predictive model for estimating the number of crimes likely to occur in its associated region. The experimental evaluation was performed on two real-world datasets collected in the cities of Chicago and New York City. This evaluation shows that the proposed approach achieves good accuracy in spatial and temporal crime forecasting over rolling time horizons.     

Attacking smart card systems: Theory and practice

Smart card technology has evolved over the last few years following notable improvements in the underlying hardware and software platforms. Advanced smart card microprocessors, along with robust smart card operating systems and platforms, contribute towards a broader acceptance of the technology. These improvements have eliminated some of the traditional smart card security concerns. However, researchers and hackers are constantly looking for new issues and vulnerabilities. In this article we provide a brief overview of the main smart card attack categories and their corresponding countermeasures. We also provide examples of well-documented attacks on systems that use smart card technology (e.g. satellite TV, EMV, proximity identification) in an attempt to highlight the importance of the security of the overall system rather than just the smart card.     

Multi-density urban hotspots detection in smart cities: A data-driven approach and experiments

The detection of city hotspots from geo-referenced urban data is a valuable knowledge support for planners, scientists, and policymakers. However, the application of classic density-based clustering algorithms on multi-density data can produce inaccurate results. Since metropolitan cities are heavily characterized by variable densities, multi-density clustering seems to be more appropriate to discover city hotspots. This paper presents CHD (City Hotspot Detector), a multi-density approach to discover urban hotspots in a city, by reporting an extensive comparative analysis with three classic density-based clustering algorithms, on both state-of-the-art and real-world datasets. The comparative experimental evaluation in an urban scenario shows that the proposed multi-density algorithm, enhanced by an additional rolling moving average technique, detects higher quality city hotspots than other classic density-based approaches proposed in literature.     

The role of communication systems in smart grids: Architectures,technical solutions and research challenges

The purpose of this survey is to present a critical overview of smart grid concepts, with a special focus on the role that communication, networking and middleware technologies will have in the transformation of existing electric power systems into smart grids. First of all we elaborate on the key technological, economical and societal drivers for the development of smart grids. By adopting a data-centric perspective we present a conceptual model of communication systems for smart grids, and we identify functional components, technologies, network topologies and communication services that are needed to support smart grid communications. Then, we introduce the fundamental research challenges in this field including communication reliability and timeliness, QoS support, data management services, and autonomic behaviors. Finally, we discuss the main solutions proposed in the literature for each of them, and we identify possible future research directions.     

Smarter universities: A vision for the fast changing digital era

In this paper we analyze the current situation of education in universities, with particular reference to the European scenario. Specifically, we observe that recent evolutions, such as pervasive networking and other enabling technologies, have been dramatically changing human life, knowledge acquisition, and the way works are performed and people learn. In this societal change, universities must maintain their leading role. Historically, they set trends primarily in education but now they are called to drive the change in other aspects too, such as management, safety, and environment protection. The availability of newer and newer technology reflects on how the relevant processes should be performed in the current fast changing digital era. This leads to the adoption of a variety of smart solutions in university environments to enhance the quality of life and to improve the performances of both teachers and students. Nevertheless, we argue that being smart is not enough for a modern university. In fact, universities should better become smarter. By “smarter university” we mean a place where knowledge is shared between employees, teachers, students, and all stakeholders in a seamless way. In this paper we propose, and discuss a smarter university model, derived from the one designed for the development of smart cities.     

Red Swarm: Reducing travel times in smart cities by using bio-inspired algorithms

This article presents an innovative approach to solve one of the most relevant problems related to smart mobility: the reduction of vehicles’ travel time. Our original approach, called Red Swarm, suggests a potentially customized route to each vehicle by using several spots located at traffic lights in order to avoid traffic jams by using V2I communications. That is quite different from other existing proposals, as it deals with real maps and actual streets, as well as several road traffic distributions. We propose an evolutionary algorithm (later efficiently parallelized) to optimize our case studies which have been imported from OpenStreetMap into SUMO as they belong to a real city. We have also developed a Rerouting Algorithm which accesses the configuration of the Red Swarm and communicates the route chosen to vehicles, using the spots (via WiFi link). Moreover, we have developed three competing algorithms in order to compare their results to those of Red Swarm and have observed that Red Swarm not only achieved the best results, but also outperformed the experts’ solutions in a total of 60 scenarios tested, with up to 19% shorter travel times.     

Recommender system for privacy-preserving solutions in smart metering

Nowadays, Smart Grid is envisaged to provide several benefits to both customers and grid operators. However, Smart Meters introduce many privacy issues if consumption data is analysed. In this paper we analyse the main techniques that address privacy when collecting electricity readings. In addition to privacy, it is equally important to preserve efficiency to carry on with monitoring operations, so further control requirements and communication protocols are also studied. Our aim is to provide guidance to installers who intend to integrate such mechanisms on the grid, presenting an expert system to recommend an appropriate deployment strategy.     

Special section: Smart water systems

The purpose of this Special Section is to provide an account of the state-of-the-art and perspectives for future research in the design and analysis of monitoring and control methods for smart water systems. This paper provides an overview of the six articles in the special section. Specifically, the special section consists of four review articles, as well as one vision and one tutorial article. These articles provide a review of leakage detection and isolation, a review of contamination event diagnosis, a review of state- space modelling of multiple reacting species in drinking water systems, a review of the application of model predictive control in Water Systems, a vision of optimizing pressure management and self-cleaning, as well as a tutorial for leakage detection and mitigation of potential contamination risk.     

Developing future human-centered smart cities: Critical analysis of smart city security,Data management,and Ethical challenges

As the globally increasing population drives rapid urbanization in various parts of the world, there is a great need to deliberate on the future of the cities worth living. In particular, as modern smart cities embrace more and more data-driven artificial intelligence services, it is worth remembering that (1) technology can facilitate prosperity, wellbeing, urban livability, or social justice, but only when it has the right analog complements (such as well-thought out policies, mature institutions, responsible governance); and (2) the ultimate objective of these smart cities is to facilitate and enhance human welfare and social flourishing. Researchers have shown that various technological business models and features can in fact contribute to social problems such as extremism, polarization, misinformation, and Internet addiction. In the light of these observations, addressing the philosophical and ethical questions involved in ensuring the security, safety, and interpretability of such AI algorithms that will form the technological bedrock of future cities assumes paramount importance. Globally there are calls for technology to be made more humane and human-centered. In this paper, we analyze and explore key challenges including security, robustness, interpretability, and ethical (data and algorithmic) challenges to a successful deployment of AI in human-centric applications, with a particular emphasis on the convergence of these concepts/challenges. We provide a detailed review of existing literature on these key challenges and analyze how one of these challenges may lead to others or help in solving other challenges. The paper also advises on the current limitations, pitfalls, and future directions of research in these domains, and how it can fill the current gaps and lead to better solutions. We believe such rigorous analysis will provide a baseline for future research in the domain.