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Sensors for Smart Cities

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

Deadline for manuscript submissions: closed (28 February 2021) | Viewed by 5068

Special Issue Editors


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Guest Editor
The University of Texas at San Antonio, San Antonio, Texas, USA
Interests: autonomy; autonomous vehicles; AI; machine learning; robotics

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Guest Editor
University of California Los Angeles (UCLA), Los Angeles, CA, USA
Interests: intelligent sensors and systems; MEMS; autonomous & electric vehicles; computational sensing; machine learning; AI; signal processing; wireless health; RF & Microwave instrumentation; radar and EW systems

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Guest Editor
Department of Energy and Control, Normandy University, 76821 Rouen, France
Interests: power systems; energy; power electronics; renewable energy; smart grids and microgrids; cyber–physical energy systems
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
National Institute of Technology Sikkim, Ravangla, Sikkim, India
Interests: intelligent systems; control; robotics; machine learning; artificial intelligence

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Guest Editor
The University of Texas at San Antonio, San Antonio, Texas, USA
Interests: brain–computing interfaces; intelligent agriculture; perception systems; autonomous systems; machine learning; smart systems

Special Issue Information

Dear Colleagues,

Different types of sensors are widely used in smart cities in different fields: intelligent public lighting, smart grids/microgrids and nanogrids, renewable energies, electric vehicles, autonomous navigation systems, health monitoring systems, materials, brain–machine interfaces, imaging technologies, etc. These sensors are divided into three categories: 1) classical sensors; 2) quantum sensors; 3) smart sensors. These sensors can be wired or wireless.

Prof. Dr. Mo Jamshidi 
Prof. Dr. Asad Madni
Assoc. Prof. Dr. Kambiz Tehrani 
Dr. Anjan Kumar Ray 
Dr. Prasanna Kolar
Guest Editors

Keywords

  • Smart girds/microgrids/nanogrids
  • Electric vehicles
  • Autonomous driving
  • Health monitoring

Published Papers (1 paper)

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Research

25 pages, 4389 KiB  
Article
Traffic Congestion Analysis Based on a Web-GIS and Data Mining of Traffic Events from Twitter
by Juan Salazar-Carrillo, Miguel Torres-Ruiz, Clodoveu A. Davis, Jr., Rolando Quintero, Marco Moreno-Ibarra and Giovanni Guzmán
Sensors 2021, 21(9), 2964; https://0-doi-org.brum.beds.ac.uk/10.3390/s21092964 - 23 Apr 2021
Cited by 21 | Viewed by 4613
Abstract
Smart cities are characterized by the use of massive information and digital communication technologies as well as sensor networks where the Internet and smart data are the core. This paper proposes a methodology to geocode traffic-related events that are collected from Twitter and [...] Read more.
Smart cities are characterized by the use of massive information and digital communication technologies as well as sensor networks where the Internet and smart data are the core. This paper proposes a methodology to geocode traffic-related events that are collected from Twitter and how to use geocoded information to gather a training dataset, apply a Support Vector Machine method, and build a prediction model. This model produces spatiotemporal information regarding traffic congestions with a spatiotemporal analysis. Furthermore, a spatial distribution represented by heat maps is proposed to describe the traffic behavior of specific and sensed areas of Mexico City in a Web-GIS application. This work demonstrates that social media are a good alternative that can be leveraged to gather collaboratively Volunteered Geographic Information for sensing the dynamic of a city in which citizens act as sensors. Full article
(This article belongs to the Special Issue Sensors for Smart Cities)
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