scholarly journals The Giant Leap for Smart Cities: Scaling up Smart City Artificial Intelligence of Things (AIoT) Initiatives

2021 ◽  
Vol 13 (21) ◽  
pp. 12295
Author(s):  
Berk Kaan Kuguoglu ◽  
Haiko van der Voort ◽  
Marijn Janssen
Keyword(s):  
Artificial Intelligence ◽  
Smart City ◽  
Smart Cities ◽  
Scale Up ◽  
Pilot Project ◽  
Extensive Study ◽  
Small Scale ◽  
Proof Of Concept ◽  
Giant Leap ◽  
Strategic Factors

Despite the promise of AI and IoT, the efforts of many organizations at scaling smart city initiatives fall short. Organizations often start by exploring the potential with a proof-of-concept and a pilot project, with the process later grinding to a halt for various reasons. Pilot purgatory, in which organizations invest in small-scale implementations without them realizing substantial benefits, is given very little attention in the scientific literature relating to the question of why AI and IoT initiatives fail to scale up for smart cities. By combining extensive study of the literature and expert interviews, this research explores the underlying reasons why many smart city initiatives relying on Artificial Intelligence of Things (AIoT) fail to scale up. The findings suggest that a multitude of factors may leave organizations ill prepared for smart city AIoT solutions, and that these tend to multiply when cities lack much-needed resources and capabilities. Yet many organizations tend to overlook the fact that such initiatives require them to pay attention to all aspects of change: strategy, data, people and organization, process, and technology. Furthermore, the research reveals that some factors tend to be more influential in certain stages. Strategic factors tend to be more prominent in the earlier stages, whereas factors relating to people and the organization tend to feature later when organizations roll out solutions. The study also puts forward potential strategies that companies can employ to scale up successfully. Three main strategic themes emerge from the study: proof-of-value, rather than proof-of-concept; treating and managing data as a key asset; and commitment at all levels.

scholarly journals Challenges and Barriers for Net‐Zero/Positive Energy Buildings and Districts—Empirical Evidence from the Smart City Project SPARCS

Buildings ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 78
Author(s):  
Daria Uspenskaia ◽  
Karl Specht ◽  
Hendrik Kondziella ◽  
Thomas Bruckner
Keyword(s):  
Smart City ◽  
Urban Areas ◽  
Smart Cities ◽  
Scale Up ◽  
Practical Experience ◽  
Positive Energy ◽  
Low Carbon ◽  
Net Zero ◽  
Multidimensional Representation

Without decarbonizing cities energy and climate objectives cannot be achieved as cities account for approximately two thirds of energy consumption and emissions. This goal of decarbonizing cities has to be facilitated by promoting net-zero/positive energy buildings and districts and replicating them, driving cities towards sustainability goals. Many projects in smart cities demonstrate novel and groundbreaking low-carbon solutions in demonstration and lighthouse projects. However, as the historical, geographic, political, social and economic context of urban areas vary greatly, it is not always easy to repeat the solution in another city or even district. It is therefore important to look for the opportunities to scale up or repeat successful pilots. The purpose of this paper is to explore common trends in technologies and replication strategies for positive energy buildings or districts in smart city projects, based on the practical experience from a case study in Leipzig—one of the lighthouse cities in the project SPARCS. One of the key findings the paper has proven is the necessity of a profound replication modelling to deepen the understanding of upscaling processes. Three models analyzed in this article are able to provide a multidimensional representation of the solution to be replicated.

REGULATION IN MANAGEMENT OF HIGH-TECH INDUSTRIES

2021 ◽  
Vol 2 (65) ◽  
pp. 51-57
Author(s):  
Natalya L. Gagulina ◽  
Keyword(s):  
Artificial Intelligence ◽  
Smart City ◽  
Smart Cities ◽  
Integrated Approach ◽  
High Tech ◽  
Economic Relations ◽  
Regulatory Barriers ◽  
Regulatory Functions ◽  
And Robotics ◽  
Market Disequilibrium

The article analyzes the institutional provision of the regulatory functions of the state in such areas as artificial intelligence and robotics. The analysis is based on the Concept of the development of regulation of relations in the field of artificial intelligence and robotics technologies until 2024. Among the problematic areas of regulation are the restriction of competition, the loss of flexibility in economic relations and the market disequilibrium. It is shown that the solution of these problems requires an integrated approach. So, to implement the concept of “smart city”, it is necessary not only to weaken or remove regulatory barriers, but also to use additional tools that have already applied in the world practice. An opportunity of applying of theoretical and methodological base of quality economics is considered. The solution to a significant part of the problems of digitalization of the region’s economy is the use in the management of the development of the “smart city” the international standard “Sustainable cities and Communities – Indicators for smart cities”.

Active Governance and Smart Citizenship

2022 ◽  
pp. 290-296
Author(s):  
Panagiota Konstantinou ◽  
Georgios Stathakis ◽  
Maria Georgia Nomikou ◽  
Athina Mountzouri ◽  
Maria Stamataki
Keyword(s):  
Artificial Intelligence ◽  
Human Behavior ◽  
Citizen Participation ◽  
Smart City ◽  
Personal Autonomy ◽  
Smart Cities ◽  
Active Part ◽  
Urban Living ◽  
Liberal Citizenship

Cities are increasingly dependent on networks, sensors, and microcontrollers. Artificial intelligence has managed to mimic human behavior, and in a few years, many jobs may be replaced by computers or machines. Today, smart cities are evolving in all countries from the poorest to the most economically viable, and there are many smart city applications that rely on observation and participation of the citizens. Active citizens are interested in the benefits of their city, and they are involved in improving and promoting urban living. All levels of smart citizen participation are associated with liberal citizenship and personal autonomy and the choice of individuals to perform specific roles and take responsibility for their actions. The states in turn provide liberal forms of government. Smart cities need “smart people” who can take an active part in both governance and city reform. This kind of citizen participation is more than just a ritual participation in government.

scholarly journals Artificial Intelligence Applications to Smart City and Smart Enterprise

2020 ◽  
Vol 10 (8) ◽  
pp. 2944 ◽  
Author(s):  
Donato Impedovo ◽  
Giuseppe Pirlo
Keyword(s):  
Artificial Intelligence ◽  
Smart City ◽  
Business Models ◽  
Smart Cities ◽  
Wide Spectrum ◽  
Life Quality ◽  
City Management ◽  
Efficient Management ◽  
Social Big Data ◽  
Areas Of Interest

Smart cities work under a more resource-efficient management and economy than ordinary cities. As such, advanced business models have emerged around smart cities, which have led to the creation of smart enterprises and organizations that depend on advanced technologies. In this Special Issue, 21 selected and peer-reviewed articles contributed in the wide spectrum of artificial intelligence applications to smart cities. Published works refer to the following areas of interest: vehicular traffic prediction; social big data analysis; smart city management; driving and routing; localization; and safety, health, and life quality.

scholarly journals Scaling up Smart City Logistics Projects: The Case of the Smooth Project

Smart Cities ◽  
2021 ◽  
Vol 4 (4) ◽  
pp. 1337-1365
Author(s):  
Eleonora Sista ◽  
Pietro De De Giovanni
Keyword(s):  
Smart City ◽  
Success Factors ◽  
Scale Up ◽  
Pilot Project ◽  
Scaling Up ◽  
City Logistics ◽  
Structured Interviews ◽  
The City ◽  
Roll Out

A large number of smart city logistics projects fail to scale up, remaining a local experimental exercise. This lack of scalability is, in fact, commonly recognized as a major problem. This study aims to determine the key success factors related to the scalability of smart city logistics projects. The process of scaling up, which is articulated as expansion, roll-out, and replication, is defined as the ability of a system to improve its scale by aiming to meet the increasing volume demand. Specifically, this study investigates the scalability intended to be used as expansion and roll-out. A qualitative case study was conducted to fulfill the research purpose. The chosen case study is SMOOTh, a pilot project currently underway in the city of Gothenburg, Sweden, involving a diverse group of companies including Volvo Group and DHL. Semi-structured interviews were conducted with seven of the project’s stakeholders. Through a thematic analysis, four categories and the respective success factors were identified. These were represented by a business model, as well as technical, stakeholder and regulatory factors. The paper concludes with observations and recommendations aimed at the pilot initiatives, adding new perspectives to the upscaling debate.

scholarly journals EconLedger: A Proof-of-ENF Consensus Based Lightweight Distributed Ledger for IoVT Networks

2021 ◽  
Vol 13 (10) ◽  
pp. 248
Author(s):  
Ronghua Xu ◽  
Deeraj Nagothu ◽  
Yu Chen
Keyword(s):  
Artificial Intelligence ◽  
Urban Environment ◽  
Situation Awareness ◽  
Electrical Network ◽  
Small Scale ◽  
Proof Of Concept ◽  
Blockchain Technology ◽  
Distributed Ledger ◽  
Security Infrastructure ◽  
Edge Networks

The rapid advancement in artificial intelligence (AI) and wide deployment of Internet of Video Things (IoVT) enable situation awareness (SAW). The robustness and security of IoVT systems are essential for a sustainable urban environment. While blockchain technology has shown great potential in enabling trust-free and decentralized security mechanisms, directly embedding cryptocurrency oriented blockchain schemes into resource-constrained Internet of Video Things (IoVT) networks at the edge is not feasible. By leveraging Electrical Network Frequency (ENF) signals extracted from multimedia recordings as region-of-recording proofs, this paper proposes EconLedger, an ENF-based consensus mechanism that enables secure and lightweight distributed ledgers for small-scale IoVT edge networks. The proposed consensus mechanism relies on a novel Proof-of-ENF (PoENF) algorithm where a validator is qualified to generate a new block if and only if a proper ENF-containing multimedia signal proof is produced within the current round. The decentralized database (DDB) is adopted in order to guarantee efficiency and resilience of raw ENF proofs on the off-chain storage. A proof-of-concept prototype is developed and tested in a physical IoVT network environment. The experimental results validated the feasibility of the proposed EconLedger to provide a trust-free and partially decentralized security infrastructure for IoVT edge networks.

scholarly journals Shared Models and Open Infrastructures for the smart City Internet of Things based on the Semantic Web

2019 ◽  
Author(s):  
Mouad Banane ◽  
Abdessalam Belangour
Keyword(s):  
Semantic Web ◽  
Smart City ◽  
Ad Hoc ◽  
Smart Cities ◽  
Coordination Mechanism ◽  
Sensor Data ◽  
Proof Of Concept ◽  
Sensors And Actuators ◽  
Competition Control ◽  
The City

Contemporary cities face many challenges: energy, ecological, demographic or economic. To answer this, technological means are implemented in cities through the use of sensors and actuators. These cities are said to be smart. Currently, smart cities are operated by actors who share neither their sensor data nor access to their actuators. This situation is called vertical: each operator deploys its own sensors and actuators and has its own IT infrastructure hosting its applications. This leads to infrastructure redundancy and ad-hoc applications to oversee and control an area of the city. A trend is to move towards a so-called horizontal situation via the use of an open and shared mediation platform. Sensor data and access to the actuators are shared within this type of platform, allowing their sharing between the different actors. The costs of infrastructure and development are then reduced. This work is part of such a context of horizontalization, within an open and shared platform, in which we propose: 1) a layer of abstraction for control and supervision of the city, 2) a competition control mechanism handling conflict cases based on the RDF (Resource Description Framework) semantic Web standard, 3) a coordination mechanism promoting the reuse of actuators using ontology, 4) an implementation of our work by a proof of concept. The abstraction we propose is based on models from reactive systems. They aim to be generic and represent the invariant of the smart city: the physical elements. They allow applications to control and supervise the city. To facilitate the development of applications we standardize the interface of our models. Since these applications may have real-time constraints, especially those that have control objectives, we propose to take advantage of the distributed architecture of this type of platform. Given the sharing of the actuators, we have identified that conflicts can arise between applications. We propose a mechanism of competition control to deal with these cases of conflicts. We have also identified that a coordination mechanism must be offered to applications wishing to perform atomic control operations. Such a mechanism promotes the reuse of the actuators present in the city. Finally, we implemented our proposals around a proof of concept, including several use cases, to demonstrate our work.

Applications of Artificial Intelligence for Smart Agriculture

2021 ◽  
pp. 277-288
Author(s):  
Suresh Sankaranarayanan
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Smart City ◽  
Autonomous Robots ◽  
Smart Cities ◽  
Building Blocks ◽  
City Management ◽  
Latency Reduction ◽  
Smart Agriculture ◽  
Growing Population

Smart cities is the latest buzzword towards bringing innovation, technology, and intelligence for meeting the demand of ever-growing population. Technologies like internet of things (IoT), artificial intelligence (AI), edge computing, big data, wireless communication are the main building blocks for smart city project initiatives. Now with the upcoming of latest technologies like IoT-enabled sensors, drones, and autonomous robots, they have their application in agriculture along with AI towards smart agriculture. In addition to traditional farming called outdoor farming, a lot of insights have gone with the advent of IoT technologies and artificial intelligence in indoor farming like hydroponics, aeroponics. Now along with IoT, artificial intelligence, big data, and analytics for smart city management towards smart agriculture, there is big trend towards fog/edge, which extends the cloud computing towards bandwidth, latency reduction. This chapter focuses on artificial intelligence in IoT-edge for smart agriculture.

scholarly journals Smart Cities, Big Data, Artificial Intelligence and Respect for the European Union Data Protection Rules

2020 ◽  
Vol 3 (2) ◽  
pp. 101
Author(s):  
Francisco Javier Durán Ruiz
Keyword(s):  
Artificial Intelligence ◽  
European Union ◽  
Big Data ◽  
Data Protection ◽  
Smart City ◽  
Smart Cities ◽  
Open Data ◽  
Personal Data ◽  
Point Of View ◽  
The European Union

The importance of cities and their populations grow more and more, as well as the need to apply ICT in their management to reduce their environmental impact and improve the services they offer to their citizens. Hence the concept of smart city arises, a transformation of urban spaces that the European Union is strongly promoting which is largely based on the use of data and its treatment using Big data and Artificial Intelligence techniques based in algorithms. For the development of smart cities it is basic, from a legal point of view, EU rules about open data and the reuse of data and the reconciliation of the massive processing of citizens' data with the right to privacy, non-discrimination and protection of personal data. The use of Big data and AI needed for the development of smart city projects requires a particular respect to data protection regulations. In this sense, the research explores in depth the specific hazards of vulnerating this fundamental right in the framework of smart cities due to the use of Big Data and AI.

scholarly journals Smart cities: potential and challenges

2021 ◽  
pp. 41-61
Author(s):  
Andrea Zanella
Keyword(s):  
Smart City ◽  
Smart Cities ◽  
Proof Of Concept ◽  
Smart Services ◽  
Main Research ◽  
Research Challenges ◽  
Enabling Technologies ◽  
The World ◽  
Smart Service

This paper aims to discuss a few fundamental questions related to the smart city paradigm, such as “what is actually a smart city?”, “what can we expect from a smart city?”,and “which problems have to be addressed and solved in order to turn a standard (dumb) city into a smart one?” Starting from a discussion of the Smart City concept, we will illustrate some of the most popular smart services using the results of proof-of-concept experiments carried out in different cities around the world. Successively, we will describe the fundamental functions required to build a smart service and the corresponding enabling technologies. We will then describe the main research challenges that need to be addressed in order to fulfill the Smart City vision, and we will conclude with some final remarks and considerations about the possible evolution of the Smart City concept.

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