Smart City Pilot Research Articles

Holarchic structures for decentralized deep learning: a performance analysis

Structure plays a key role in learning performance. In centralized computational systems, hyperparameter optimization and regularization techniques such as dropout are computational means to enhance learning performance by adjusting the deep hierarchical structure. However, in decentralized deep learning by the Internet of Things, the structure is an actual network of autonomous interconnected devices such as smart phones that interact via complex network protocols. Self-adaptation of the learning structure is a challenge. Uncertainties such as network latency, node and link failures or even bottlenecks by limited processing capacity and energy availability can significantly downgrade learning performance. Network self-organization and self-management is complex, while it requires additional computational and network resources that hinder the feasibility of decentralized deep learning. In contrast, this paper introduces a self-adaptive learning approach based on holarchic learning structures for exploring, mitigating and boosting learning performance in distributed environments with uncertainties. A large-scale performance analysis with 864,000 experiments fed with synthetic and real-world data from smart grid and smart city pilot projects confirm the cost-effectiveness of holarchic structures for decentralized deep learning.

Project Surveys for Determining and Defining Key Performance Indicators in the Development of Smart Grids in Energy Systems

With the increasing energy needs, it has become obligatory to use technology and computer technology in electricity networks with the advancement of technology. By using the possibilities of high technology, it is possible to carry out audits with two-way data flow and intelligent systems on the sides of energy production and consumption. Many smart grid projects have been implemented around the world, such as the establishment of advanced measurement infrastructure, intelligent meter assembly, generation of electricity from renewable energy sources, energy efficiency, use of electric vehicles and smart buildings . Many developed and developing countries have set up platforms for developing Smart Grids and have set the road map for smart grid. In particular, the main objective of the European Union; By 2020, it was possible to integrate renewable energy resources into the system by 20%, increase energy efficiency by 20%, and reduce carbon emissions by 20%. The American government finances many smart grid projects in its country with a certain amount of reimbursement. Japan has launched smart city pilot applications by taking smart grid projects one step further. Europe, the US and Japan except China, South Korea, Canada and Australia has become interested in smart grids. In this study, development and project examples of smart grids worldwide have been investigated.

Privacy-enhancing aggregation of Internet of Things data via sensors grouping

Big data collection practices using Internet of Things (IoT) pervasive technologies are often privacy-intrusive and result in surveillance, profiling, and discriminatory actions over citizens that in turn undermine the participation of citizens to the development of sustainable smart cities. Nevertheless, real-time data analytics and aggregate information from IoT devices open up tremendous opportunities for managing and regulating smart city infrastructures in a more efficient and sustainable way. The privacy-enhancing aggregation of distributed sensor data, such as residential energy consumption or traffic information, is the research focus and challenge tackled in this paper. Citizens have the option to choose their privacy level by reducing the quality of the shared data at a cost of a lower accuracy in data analytics services. A baseline scenario is considered in which IoT sensor data are shared directly with an untrustworthy central aggregator. A grouping mechanism is introduced that improves privacy by sharing data aggregated first at a group level compared to a baseline scenario in which each individual shares data directly to the central aggregator. Group-level aggregation obfuscates sensor data of individuals, in a similar fashion as differential privacy and homomorphic encryption schemes, thus inference of privacy-sensitive information from single sensors becomes computationally harder compared to the baseline scenario. The proposed system and its generic applicability are evaluated using real-world data from two smart city pilot projects. Privacy under grouping increases, while preserving the accuracy of the baseline scenario. Intra-group influences of privacy by one group member on the other ones are measured and fairness on privacy is found to be maximized between group members with similar privacy choices. Several grouping strategies are compared. Grouping by proximity of privacy choices provides the highest privacy gains. The implications of the strategy on the design of incentives mechanisms are discussed.

Open IoT Ecosystem for Enhanced Interoperability in Smart Cities-Example of Métropole De Lyon.

The Internet of Things (IoT) has promised a future where everything gets connected. Unfortunately, building a single global ecosystem of Things that communicate with each other seamlessly is virtually impossible today. The reason is that the IoT is essentially a collection of isolated “Intranets of Things”, also referred to as “vertical silos”, which cannot easily and efficiently interact with each other. Smart cities are perhaps the most striking examples of this problem since they comprise a wide range of stakeholders and service providers who must work together, including urban planners, financial organisations, public and private service providers, telecommunication providers, industries, citizens, and so forth. Within this context, the contribution of this paper is threefold: (i) discuss business and technological implications as well as challenges of creating successful open innovation ecosystems, (ii) present the technological building blocks underlying an IoT ecosystem developed in the framework of the EU Horizon 2020 programme, (iii) present a smart city pilot (Heat Wave Mitigation in Métropole de Lyon) for which the proposed ecosystem significantly contributes to improving interoperability between a number of system components, and reducing regulatory barriers for joint service co-creation practices.

Smart City Pilot Projects: Exploring the Dimensions and Conditions of Scaling Up

ABSTRACTIn many cities, pilot projects are set up to test new technologies that help to address urban sustainability issues, improve the effectiveness of urban services, and enhance the quality of life of citizens. These projects, often labelled as “smart city” projects, are typically supported by municipalities, funded by subsidies, and run in partnerships. Many of the projects fade out after the pilot stage, and fail to generate scalable solutions that contribute to sustainable urban development. The lack of scaling is widely perceived as a major problem. In this paper, we analyze processes of upscaling, focusing on smart city pilot projects in which several partners—with different missions, agendas, and incentives—join up. We start with a literature review, in which we identify three types of upscaling: roll-out, expansion, and replication, each with its own dynamics and degree of context sensitivity. The typology is further specified in relation to several conditions and requirements that can impact upscaling processes, and illustrated by a descriptive analysis of three smart city pilot projects developed in Amsterdam. The paper ends with conclusions and recommendations on pilot projects and partnership governance, and adds new perspectives on the debate regarding upscaling.

Research of Smart Home Service Platform Based on Mobile Cloud

With the development of smart city pilot projects of Housing Department, there has been a lot of smart city application products, meanwhile, smart home products emerge endlessly. To enjoy better service, people will choose a number of services provided by different suppliers, which causes a home need various service application terminals. Then, timely, quick and safe mobile remote access becomes very important. To solve this problem, the authors integrate service applications of affiliate service suppliers through standardized protocols, based on mobile cloud, and create smart home Platform. This providing customers a unified security service selection entry through customer settings.

Do Smart Cities Produce Smart Entrepreneurs?

Living Labs aim to engage in user-centered design practices where users are included in their daily life environment as innovative agents. However, empirical insights in end user engagement in Living Lab practices are currently lacking. This article focuses on opening up this black box of user engagement by analyzing the involvement of a group of entrepreneurs in a Living Lab smart city pilot in Amsterdam, the Climate street. The goal of the article is to analyze how and to what extent the Climate street enabled the involved entrepreneurs to engage in bottom up innovation. Theoretically, the article explores this pilot from a Science and Technology Studies perspective, specifically its notion of the socio-technical network. The article concludes that user innovativeness was limited by the pre-configuration of the entrepreneur as lay tester rather than as an active user-innovator. Furthermore, it is suggested that the inherent tension in Living Lab practices between configuring users and actual user practices hampers user innovativeness in general. Granting users more agency and opening up Living Lab practices to daily life dynamics stimulates the transition from tester to innovator in a daily life setting and subsequently makes entrepreneurs more readily smart.