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Smart Energy and Cities in the IoT Era

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: closed (20 March 2019) | Viewed by 13201

Special Issue Editor


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Guest Editor
Department of Intelligent Energy and Industry, Chung-Ang University, Seoul 06974, Republic of Korea
Interests: smart energy; carbon neutrality; digital platform; AI-based data; digital twins; smart buildings and cities
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Governments and businesses are applying the concept of "Smart Energy and City" to urban infrastructure and services to improve the quality of citizen’s life and sustainability of cities. The advancement of the smart city starts with sensors. Today, we can utilize the Internet of Things (IoT) to collect and visualize all the information about a city. In the IoT era, smart city refers to a city where all components are connected. A “smart city” aims to benefit citizens and provide them with a favorable life by solving urban problems based on collected and analyzed data. Big data technology is required to take full advantage of the data collected from IoT. Artificial Intelligence (AI) technology is needed to discover and validate meaningful solutions from big data. In addition, blockchain technology must be applied to ensure the reliability of collected data and to provide safe and sustainable services to citizens. Remarkable advancements in IoT, big data, AI, and service platforms, from sensing and learning to customization and optimization, will open up considerable potential of the smart city infrastructure to effectively address invisible but pervasive problems of the city. One of the solutions that can solve urban problems and make the transformation into the smart city is smart energy. Smart energy provides economic benefits to citizens and enables efficient operation of the city by reducing unnecessary energy usage. Therefore, in the near future, smart energy city infrastructure capable of linking with blockchain, AI, and service platforms such as IoT-based Cyber-Physical System (CPS), Virtual Power Plants (VPP), Zero Energy Buildings (ZEB), City Energy Management System (CEMS) and Vehicle to Grid (V2G) will create new services and business models for smart cities and make cities more intelligent. In addition, such service and business models are expected to provide human-centric smart energy services, while enhancing the resilience and efficiency of the smart city. In order for a smart city to become smarter, it is necessary to research and develop various ideas, prototypes, and core technologies centered on platforms that can organically link IoT, big data, AI, blockchain, and smart energy technology.

This Special Issue aims to share and exchange the research findings from scientific ideas to industrial practices on smart energy and city in the IoT era. The Guest Editor welcomes theoretical papers, methodological studies, and empirical research. Topics of interest of this Special Issue include, but are not limited to, the following themes:

Connectivity and Infrastructure (Energy-IoT)

  • Intelligent Sensing Technologies for Smart Energy and Cities
  • Network and Communications Technologies for Smart City Infrastructures
  • Internet of Things and Cyber-Physical Systems for Smart Energy and Cities
  • Virtual Power Plants, Zero Energy Buildings, City Energy Management System, and Vehicle to Grid in Smart Energy Cities
  • Privacy, Safety and Security for Connectivity

Data Analytics (Big Data and AI)

  • Data Science and Data Analytics in Smart Energy and Cities
  • Big Data Technologies for Smart City Solutions
  • Artificial Intelligence for Smart City Prosumers
  • Data Architecture and Management for Smart City Prosumer

Platform and Business Model (Smart Energy and City Services)

  • Blockchain Service for Smart Energy and Cities
  • Smart Energy and City Platform for Sustainability
  • Digital Twins of Smart Energy and City for Sustainability
  • Smart City Prosumer Service for Future Smart City
  • Business Model and Solutions for Smart Energy and City
Prof. Sehyun Park
Guest Editor

Manuscript Submission Information

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Keywords

  • Smart Energy
  • Smart City Prosumer
  • Smart City Infrastructure
  • Smart City Service
  • Internet of Things
  • Artificial Intelligence
  • Big Data Analytics
  • Blockchain Service
  • Smart City Platform

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Published Papers (2 papers)

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Research

23 pages, 5533 KiB  
Article
ADLAuth: Passive Authentication Based on Activity of Daily Living Using Heterogeneous Sensing in Smart Cities
by Maryam Naseer Malik, Muhammad Awais Azam, Muhammad Ehatisham-Ul-Haq, Waleed Ejaz and Asra Khalid
Sensors 2019, 19(11), 2466; https://doi.org/10.3390/s19112466 - 29 May 2019
Cited by 35 | Viewed by 4224
Abstract
The Internet of Things is a rapidly growing paradigm for smart cities that provides a way of communication, identification, and sensing capabilities among physically distributed devices. With the evolution of the Internet of Things (IoTs), user dependence on smart systems and services, such [...] Read more.
The Internet of Things is a rapidly growing paradigm for smart cities that provides a way of communication, identification, and sensing capabilities among physically distributed devices. With the evolution of the Internet of Things (IoTs), user dependence on smart systems and services, such as smart appliances, smartphone, security, and healthcare applications, has been increased. This demands secure authentication mechanisms to preserve the users’ privacy when interacting with smart devices. This paper proposes a heterogeneous framework “ADLAuth” for passive and implicit authentication of the user using either a smartphone’s built-in sensor or wearable sensors by analyzing the physical activity patterns of the users. Multiclass machine learning algorithms are applied to users’ identity verification. Analyses are performed on three different datasets of heterogeneous sensors for a diverse number of activities. A series of experiments have been performed to test the effectiveness of the proposed framework. The results demonstrate the better performance of the proposed scheme compared to existing work for user authentication. Full article
(This article belongs to the Special Issue Smart Energy and Cities in the IoT Era)
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26 pages, 11039 KiB  
Article
A Computer Vision-Based Roadside Occupation Surveillance System for Intelligent Transport in Smart Cities
by George To Sum Ho, Yung Po Tsang, Chun Ho Wu, Wai Hung Wong and King Lun Choy
Sensors 2019, 19(8), 1796; https://doi.org/10.3390/s19081796 - 15 Apr 2019
Cited by 69 | Viewed by 8017
Abstract
In digital and green city initiatives, smart mobility is a key aspect of developing smart cities and it is important for built-up areas worldwide. Double-parking and busy roadside activities such as frequent loading and unloading of trucks, have a negative impact on traffic [...] Read more.
In digital and green city initiatives, smart mobility is a key aspect of developing smart cities and it is important for built-up areas worldwide. Double-parking and busy roadside activities such as frequent loading and unloading of trucks, have a negative impact on traffic situations, especially in cities with high transportation density. Hence, a real-time internet of things (IoT)-based system for surveillance of roadside loading and unloading bays is needed. In this paper, a fully integrated solution is developed by equipping high-definition smart cameras with wireless communication for traffic surveillance. Henceforth, this system is referred to as a computer vision-based roadside occupation surveillance system (CVROSS). Through a vision-based network, real-time roadside traffic images, such as images of loading or unloading activities, are captured automatically. By making use of the collected data, decision support on roadside occupancy and vacancy can be evaluated by means of fuzzy logic and visualized for users, thus enhancing the transparency of roadside activities. The CVROSS was designed and tested in Hong Kong to validate the accuracy of parking-gap estimation and system performance, aiming at facilitating traffic and fleet management for smart mobility. Full article
(This article belongs to the Special Issue Smart Energy and Cities in the IoT Era)
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