Smart City and IoT

The new Internet of Things (IoT) applications are enabling Smart City initiatives worldwide. It provides the ability to remotely monitor, manage and control devices, and to create new insights and actionable information from massive streams of real-time data. The main features of a smart city include a high degree of information technology integration and a comprehensive application of information resources. The essential components of urban development for a smart city should include smart technology, smart industry, smart services, smart management and smart life. The Internet of Things is about installing sensors (RFID, IR, GPS, laser scanners, etc.) for everything, and connecting them to the internet through specific protocols for information exchange and communications, in order to achieve intelligent recognition, location, tracking, monitoring and management. With the technical support from IoT, smart city need to have three features of being instrumented, interconnected and intelligent. Only then a Smart City can be formed by integrating all these intelligent features at its advanced stage of IOT development. The explosive growth of Smart City and Internet of Things applications creates many scientific and engineering challenges that call for ingenious research efforts from both academia and industry, especially for the development of efficient, scalable, and reliable Smart City based on IoT. New protocols, architectures, and services are in dire needs to respond for these challenges. The goal of the special issue is to bring together scholars, professors, researchers, engineers and administrators resorting to the state-of-the-art technologies and ideas to significantly improve the field of Smart City based on IoT.     

Smart Spaces for Adaptive Information Integration in Bioinformatics

Bioinformatics is reaping the benefits of advances in Semantic Web technology thanks to the growing number of available biomedical web resources and portals. Although positive in general, this abundance poses practical challenges to researchers who must be skilled in techniques for retrieving and integrating sparse and complex contents, and thereof calls for more “intelligent” and user friendly ways of interaction to easily get information. With the aim of making available the intelligent functionality of smart systems, this paper presents SSAIIB (Smart Spaces for Adaptive Information Integration in Bioinformatics), a reference framework for designing bioinformatics smart applications that support discovering, aggregating and delivering contents from web resources according to user’s goals, tasks and concerns. The “Smart Spaces” are software environments whose smartness lies in their ability to adaptively accomplish specific user’s activities such as the exploiting content from biomedical resources, integrating data captured from different sources, supporting data analytics, etc. SSAIIB is structured around two main technologies: service oriented architectures and software agents. In particular, it relies on mechanisms for dynamically assembling suitable services and the use of agents as a natural metaphor for both modelling user’s activities and accessing web resources. A case study is presented that shows the application of SSAIIB to the design and the implementation of a smart space for annotating biomedical texts.     

Km4City ontology building vs data harvesting and cleaning for smart-city services

Presently, a very large number of public and private data sets are available from local governments. In most cases, they are not semantically interoperable and a huge human effort would be needed to create integrated ontologies and knowledge base for smart city. Smart City ontology is not yet standardized, and a lot of research work is needed to identify models that can easily support the data reconciliation, the management of the complexity, to allow the data reasoning. In this paper, a system for data ingestion and reconciliation of smart cities related aspects as road graph, services available on the roads, traffic sensors etc., is proposed. The system allows managing a big data volume of data coming from a variety of sources considering both static and dynamic data. These data are mapped to a smart-city ontology, called KM4City (Knowledge Model for City), and stored into an RDF-Store where they are available for applications via SPARQL queries to provide new services to the users via specific applications of public administration and enterprises. The paper presents the process adopted to produce the ontology and the big data architecture for the knowledge base feeding on the basis of open and private data, and the mechanisms adopted for the data verification, reconciliation and validation. Some examples about the possible usage of the coherent big data knowledge base produced are also offered and are accessible from the RDF-store and related services. The article also presented the work performed about reconciliation algorithms and their comparative assessment and selection.     

Smart urban planning using Big Data analytics to contend with the interoperability in Internet of Things

The recent growth and expansion in the field of Internet of Things (IoT) is providing a great business prospective in the direction of the new era of smart urban. The insight of the smart urban is extensively preferred, as it improves the excellence of life of citizens, connecting several regulations, that is, smart transportation, smart parking, smart environment, smart healthcare, and so forth. Continuous intensification of the multifaceted urban set-up is extensively challenged by real-time processing of data and smart decision capabilities. Consequently, in this paper, we propose a smart city architecture which is based on Big Data analytics. The proposed scheme is comprised of three modules: (1) data acquisition and aggregation module collects varied and diverse data interrelated to city services, (2) data computation and processing module performs normalization, filtration, processing and data analysis, and (3) application and decision module formulates decisions and initiates events. The proposed architecture is a generic solution for the smart urban planning and variety of datasets is analyzed to validate this architecture. In addition, we tested reliable datasets on Hadoop server to verify the threshold limit value (TLV) and the investigation demonstrates that the proposed scheme offer valuable imminent into the community development systems to get better the existing smart urban architecture. Moreover, the efficiency of proposed architecture in terms of throughput is also shown.     

Elastic Smart Contracts in Blockchains

In this paper, we deal with questions related to blockchains in complex Internet of Things (IoT)-based ecosystems. Such ecosystems are typically composed of IoT devices, edge devices, cloud computing software services, as well as people, who are decision makers in scenarios such as smart cities. Many decisions related to analytics can be based on data coming from IoT sensors, software services, and people. However, they are typically based on different levels of abstraction and granularity. This poses a number of challenges when multiple blockchains are used together with smart contracts. This work proposes to apply our concept of elasticity to smart contracts and thereby enabling analytics in and between multiple blockchains in the context of IoT. We propose a reference architecture for Elastic Smart Contracts and evaluate the approach in a smart city scenario, discussing the benefits in terms of performance and self-adaptability of our solution.      

An edge-based platform for dynamic Smart City applications

A Smart City is a cyber–physical system improving urban behavior and capabilities by providing ICT-based functionalities. An infrastructure for Smart City has to be geographically and functionally extensible, as it requires both to grow up with the physical environment and to meet the increasing in needs and demands of city users/inhabitants. In this paper, we propose iSapiens, an IoT-based platform for the development of general cyber–physical systems suitable for the design and implementation of smart city services and applications. As distinguishing features, the iSapiens platform implements the edge computing paradigm through both the exploitation of the agent metaphor and a distributed network of computing nodes directly scattered in the urban environment. The platform promotes the dynamic deployment of new computing nodes as well as software agents for addressing geographical and functional extensibility. iSapiens provides a set of abstractions suitable to hide the heterogeneity of the physical sensing/actuator devices embedded in the system, and to support the development of complex applications. The paper also furnishes a set of methodological guidelines exploitable for the design and implementation of smart city applications by properly using iSapiens. As a significant case study, the design and implementation of a real Smart Street in the city of Cosenza (Italy) are shown, which provides decentralized urban intelligence services to citizens.     

Intelligent services for Big Data science

Cities are areas where Big Data is having a real impact. Town planners and administration bodies just need the right tools at their fingertips to consume all the data points that a town or city generates and then be able to turn that into actions that improve peoples’ lives. In this case, Big Data is definitely a phenomenon that has a direct impact on the quality of life for those of us that choose to live in a town or city. Smart Cities of tomorrow will rely not only on sensors within the city infrastructure, but also on a large number of devices that will willingly sense and integrate their data into technological platforms used for introspection into the habits and situations of individuals and city-large communities. Predictions say that cities will generate over 4.1 terabytes per day per square kilometer of urbanized land area by 2016. Handling efficiently such amounts of data is already a challenge. In this paper we present our solutions designed to support next-generation Big Data applications. We first present CAPIM, a platform designed to automate the process of collecting and aggregating context information on a large scale. It integrates services designed to collect context data (location, user’s profile and characteristics, as well as the environment). Later on, we present a concrete implementation of an Intelligent Transportation System designed on top of CAPIM. The application is designed to assist users and city officials better understand traffic problems in large cities. Finally, we present a solution to handle efficient storage of context data on a large scale. The combination of these services provides support for intelligent Smart City applications, for actively and autonomously adaptation and smart provision of services and content, using the advantages of contextual information.     

Smart city image landscape design based on wireless sensors

Smart City is a city environment that advanced sensors combine to manage the city's assets the information technology virtually. Data they have collected, because it is the foundation of these services, the sensor network is an integral part of the smart city. Wireless sensors are to be deployed in several different locations, therefore a relatively inexpensive ability to transmit remote data to reduce the power consumption and maintenance costs; the small built-in sensor is incredibly essential. For each sensor, since it prerequisites for complex information, and Smart City needs is rugged, the integrated sensor system is the concept of Smart City in development. The most important thing is the smart city's side, and the reverse in urban design the plan is to reveal the importance of the role of landscape design. The purpose of this article is, from the point of view of urban design, find outlines the concept of Smart City, highlighting important touchpoint of smart urban landscape design that leads to strong principles of smart, relations and the role of urban design, planning and creativity it is to be sustainable development, city to allow for efficient urban development and beautiful urban landscape.     

咸阳市智慧城市发展愿景

从“一卡通”到“智慧城市”,从政府提出智慧咸阳到首批创建国家智慧城市试点,文章明确了融合智慧理念、规划多个领域、构建支撑体系、梳理重点项目的智慧咸阳发展愿景,并论述了智慧城市建设对咸阳市城市发展的作用。     

Conceptual design of a user-centric smart product-service system using self-organizing map

As an emerging IT-driven business paradigm, smart product-service system (Smart PSS), which offers not only the smart, connected product (SCP) but also its generated service as a solution bundle, has become a vital research topic. Many research efforts have been devoted to constructing the conceptual design framework by considering SCPs and services simultaneously. However, the following critical issues in Smart PSS conceptual design have not been well addressed: how to improve the solution of Smart PSS in the conceptual design stage to meet user emotional requirements. Aiming to fill the gap, this work proposes a conceptual design method for Smart PSS from the perspective of analyzing user-generated emotions/feelings. Specifically, the relevant traditional products are identified, and their public review data is used to analyze user emotions/feelings in user-product interaction. Interactive emotion board as a new design tool is presented to organize the user-generated emotions/feelings, associated design elements, and the potential design points of the initial solution. And the analytic hierarchy process (AHP) is utilized to evaluate the improved solution. To ensure the efficiency of the analysis process, the self-organizing map (SOM) algorithm is utilized in the process of clustering product samples and Kansei words. A case study of smart electric bicycle service system (SEBSS) design is used to demonstrate the performance of the proposed method. Based on the case study, the proposed approach appears effective in helping with Smart PSS conceptual design.     

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.     

An edge-cloud-aided incremental tensor-based fuzzy c-means approach with big data fusion for exploring smart data

Recently, smart data has attracted great attention in the smart city community since it can provide valuable information to support intelligent services such as planning, monitoring, and decision making. However, it imposes a big challenge to explore smart data from big data gathered from smart city with various advanced fusion and analysis approaches. This paper proposes an incremental tensor-based fuzzy c-means approach (IT-FCM) for obtaining smart data from continuously generated big data. Specifically, a weighted version of the tensor-based fuzzy c-means approach (T-FCM) is firstly proposed to cluster the dataset that combines the previous cluster centroids and the new generated data. Aiming to improve the clustering efficiency, the old data objects are represented by the centroids to avoid repeat clustering. Furthermore, this paper presents an edge-cloud-aided clustering scheme to fuse big data from different sources and perspectives and further to implement co-clustering on the fused datasets for exploring smart data. Finally, the proposed IT-FCM approach is evaluated by comparing with T-FCM regarding clustering accuracy and efficiency on two different datasets in the experiments. The results state that IT-FCM outperforms T-FCM in clustering streaming big data in terms of accuracy and efficiency for obtaining smart data.     

大数据在智慧城市中的应用

伴随智慧城市的发展,多源、异构、冗余的大数据应运而生。利用数据挖掘、决策分析等技术,实现大数据转化为数据资产,必将成为大数据时代智慧城市智能化、互联化的必要手段。阐述了智慧城市概念、智慧城市数据资源及大数据处理技术,分析了智慧城市中的大数据综合应用,阐明了大数据在智慧城市重点行业领域的应用现状,并对其进行展望,为未来智慧城市中大数据的深入应用提供解决方案和思路。     

基于天地图的智慧公交移动APP设计与实现

针对太原市智慧公交系统建设的需求,基于天地图移动API和IOS平台,研发了一款智慧公交移动APP.APP提供静态公交查询、实时公交查询、周边公交查询和公交换乘查询等公交查询服务和周边兴趣点查询、天气查询和交通管理通知公告等增值服务.解决传统公交运营管理不能满足公众对出行信息的需求问题,做到了智慧出行.     

A socio-technical analysis of factors affecting the adoption of smart TV in Korea

Smart TV has been highlighted as a new platform of broadcasting, powered for the last five years by its own application store as well as by internet-based contents. However, recently, smart TV's performance in the pay-TV market has been below expectations. In the socio-technical view, this paper investigates three aspects surrounding smart TV: bundling as a market competition strategy; services using technological features represented by N-screen; and consumer attributes, including personal innovativeness and demographics. The results show that the bundles with IPTV have a lock-in effect, while other pay-TV services do not, indicating that bundling by communications service providers is a more effective strategy to keep market share away from new entrants. Policy makers only consider competition among incumbents, neglecting the entrance of new service providers, like over-the-top service providers. Therefore, bundling should be evaluated in terms of an entry barrier. Smart TV doesn't work as a platform because the adoption of smart TV has no influence on the watching of N-screen broadcasting services on TV. There are implications that the new technology alone cannot encourage lean-forward activity on TV. Managers should focus on what consumers expect from ‘smartness’, and develop contents for the smart TV as a home appliance.     

Semantic service provisioning for smart objects: Integrating IoT applications into the web

Internet of Things (IoT) applications residing on the Web are the next logical development of the recent effort from academia and industry to design and standardize new communication protocols for smart objects. This paper proposes the service provisioning architecture for smart objects with semantic annotation to enables the integration of IoT applications into the Web. We aim to bring smart object services to the Web and make them accessible by plenty of existing Web APIs in consideration of its constraints such as limited resources (ROM, RAM, and CPU), low-power microcontrollers, and low-bitrate communication links.     

Quality and the efficiency of data in “Smart-Cities”

As a new form of sustainable development, the concept “Smart Cities” knows a large expansion during the recent years. It represents an urban model, refers to all alternative approaches to metropolitan ICTs case to enhance quality and performance of urban service for better interaction between citizens and government. However, the smart cities based on distributed and autonomous information infrastructure contains millions of information sources that will be expected more than 50 billion devices connected by using IoT or other similar technologies in 2020. In Information Technology, we often need to process and reason with information coming from various sources (sensors, experts, models). Information is almost always tainted with various kinds of imperfection: imprecision, uncertainty, ambiguity, we need a theoretical framework general enough to allow for the representation, propagation and combination of all kinds of imperfect information. The theory of belief functions is one such Framework. Real-time data generated from autonomous and distributed sources can contain all sorts of imperfections regarding on the quality of data e.g. imprecision, uncertainty, ignorance and/or incompleteness. Any imperfection in data within smart city can have an adverse effect over the performance of urban services and decision making. In this context, we address in this article the problem of imperfection in smart city data. We will focus on handling imperfection during the process of information retrieval and data integration and we will create an evidential database by using the evidence theory in order to improve the efficiency of smart city. The expected outcomes from this paper are (1) to focus on handling imperfection during the process of information retrieval and data integration (2) to create an evidential database by using the evidence theory in order to improve the efficiency of smart city. As experimentation we present a special case of modeling imperfect data in the field of Healthcare. An evidential database will be built which will contain all the perfect and imperfect data. These data come from several Heterogeneous sources in a context of Smart Cities. Imperfect aspects in the evidential database expressed by the theory of beliefs that will present in this paper.     

A TRIZ-inspired knowledge-driven approach for user-centric smart product-service system: A case study on intelligent test tube rack design

With the advancement of information and communication technologies, smart product-service system (PSS) has attracted increasing research attention to integrate diverse providers/stakeholders and deliver value-added services. Many studies have thusly been conducted to design and develop the smart PSS, while i) how to identify multi-source requirements through reviewing the entire service interaction cycle, ii) how to define and deduce the innovative smart connected products (SCPs) features under contradictory interests, and iii) how to specify the functional and data service configuration solutions are still unclear. To tackle these problems, a knowledge-driven approach was introduced to better organize the multi-source design knowledge and deduce service recommendations for personalized user demands. Specifically, a user journey map-based method was proposed for knowledge elicitation of the specific user demands. To organize the user knowledge for better understanding, hierarchical personalized user requirements (PURs) analytics were proposed to quantitively transfer PURs into proper design engineering parameters. To inspire the problem-solving logic for design solution generation, TRIZ inventive principles were retrieved and referred to. With the generated design concept, the service logic diagrams were structured to define the personalized service content of SCPs. Having the service logic and SCPs, the overall service network of the user-centric smart PSS can be outlined. The proposed approach was demonstrated and validated in the digital health area via a case study on smart test tube rack (STTR) design, and it was validated from an economic feasibility perspective. It showed that the STTR was promising to reduce manual work, improve the nurses' performance, and enhance patients’ medical experience. Furthermore, it was suggested that the proposed approach can effectively guide the innovative SCPs creation in a straightforward and instructive manner, and is promising to process the service solution deduction and improve the efficiency of service creation in real practice.     

Impacts of low citizen awareness and usage in smart city services: the case of London’s smart parking system

Smart city applications and services are increasingly considered as strategic means to cope with emerging global challenges such as climate change, pollution, the ageing population, and energy shortage. In particular, smart parking is a type of smart services used to improve traffic congestion and pollution within cities. Nevertheless, although smart city services are driven by advanced information technologies, their success is highly dependent on user engagement, which is historically problematic. This paper presents and discusses the results of a case study on the smart parking service in London. A questionnaire (involved a total of 212 local drivers) was adopted as the main data collection method. This was complemented by the collection and analysis of 470 online user comments left for the service. The results showed that London’s smart parking service may potentially help each driver to save an average of £68 (62.2 l) on petrol annually and reduce CO₂ emissions by 238.14 kg per car per year. At city level, a smart parking system could help London save £183.6 million worth of petrol per year and reduce its annual CO₂ emissions by 642,978 tons. However, public awareness, actual usage, and user satisfaction of this smart service are currently very low. These present substantial barriers to realise the potential economic and environmental benefits of the service. This paper concluded that further to the very technological efforts, local authorities and service providers need to make a stronger endeavour to enhance public engagement and user satisfaction towards smart services, in order to realise the promises of such solutions.     

基于情境感知技术的智慧城市服务系统研究

随着城市规模越来越复杂,全国各级政府都在进行城市物联网和信息化建设,目前虽然搭建了互联骨干网和部署了大量的传感器,收集了众多的城市行为数据,但落后的信息管理模式难以体现信息价值,将信息体现在服务提升之中,造成信息资源的极大浪费。因此,将情境感知技术引入到智慧城市服务的应用之中,构建了一个基于情境感知的城市服务系统,并通过情境信息采集、情境信息推理和服务配置模型等关键技术,实时感知城市内的情境需求,从而提供智能化的业务服务组合。最后通过一社区智慧街道管理系统来验证本文所设计的系统效果。