Applications of Intelligent Sensors in Smart Cities

A special issue of Telecom (ISSN 2673-4001).

Deadline for manuscript submissions: closed (28 February 2023) | Viewed by 5531

Special Issue Editor


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Guest Editor
1. COPELABS, Universidade Lusófona, 1749-024 Lisboa, Portugal
2. School of Engineering and Informatics, University of Susex, BN1 9RH Brighton, UK
Interests: computer networks; Internet of Things; cyber security; artificial intelligence

Special Issue Information

Dear Colleagues,

Since the industrial revolution in the mid-18th century, cities around the world began their process of industrial development, leading to population growth. Nowadays, large population centers face resource management problems (such as energy and water efficiency, mobility, waste collection, etc.), where citizens demand optimal solutions that seek to minimize the waste of resources and maximize their benefits. The concept of smart cities arises with the purpose of providing citizens with optimal and sustainable services, as well as better quality of life. As an important tool, smart sensors help the government and decision makers in the resource management process and the collection and processing of relevant data related to strategic central regions or neighborhoods. However, deploying smart sensors in the context of smart cities has its challenges. Since sensors can be spread throughout cities, they can collect data from different networks or devices, where security and privacy are not trivial requirements. Based on this, network managers must ensure optimal security connections and security tools to prevent the collected data from being misused, in which intruders can cause damage to the entire network. Further, due to the large number of deployed sensors, acquiring management and filters for data reliable for each scenario can be a challengeable task. Although the use of smart sensors within smart cities aims to make citizens' lives easier, both technologies have open issues that still require further research in different areas. The purpose of this Special Issue is to provide the academic and industrial communities with an excellent venue covering all aspects of current work on intelligent sensor applications for smart cities.

Topics of interest include (but are not limited to):

  • Intelligent sensors for public transport systems in smart cities;
  • Intelligent sensors for traffic control in smart cities;
  • Energy and water efficiency systems in smart cities;
  • Secure, privacy and trust mechanisms for intelligent sensors;
  • Smart waste management systems for smart cities;
  • Intelligent sensors for connected and smart mobility;
  • Data analytics and fusion for intelligent sensors.

Dr. Naercio David Pedro Magaia
Guest Editor

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Keywords

  • smart cities
  • smart sensors
  • smart networks
  • security
  • Internet of things
  • resource management
  • public transport systems
  • intelligent transportation systems
  • sensing technology

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Published Papers (2 papers)

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Research

9 pages, 3194 KiB  
Article
Coverage Extension for the UK Smart Meter Implementation Programme Using Mesh Connectivity
by David Owens, Shuja Ansari, Haitham Cruickshank, Rahim Tafazolli and Muhammad Ali Imran
Telecom 2022, 3(4), 610-618; https://doi.org/10.3390/telecom3040034 - 31 Oct 2022
Viewed by 1891
Abstract
Smart meters (SM) with wireless capabilities are one of the most meaningful applications of the Internet of Things. Standards like Zigbee have found a niche in transmitting data on energy usage to the user and the supplier wirelessly via these meters and communication [...] Read more.
Smart meters (SM) with wireless capabilities are one of the most meaningful applications of the Internet of Things. Standards like Zigbee have found a niche in transmitting data on energy usage to the user and the supplier wirelessly via these meters and communication hubs. There are still certain difficulties, notably in delivering wireless connectivity to meters situated in difficult-to-reach locations such as basements or deep indoors. To solve this issue, this paper investigates the usage of mesh networks at 868 MHz, particularly to increase coverage, and proposes an additional mounted antenna to significantly increase outside coverage while providing the necessary coverage extension for hard-to-reach indoor locations. Extensive measurements were made in Newbury in both suburban and open environments for validation and delivery of a simple statistical model for the 868 MHz band in United Kingdom conurbations. Results presented in this paper estimate that mesh networks at 868 MHz can accommodate large areas constituting several SMs with the proposed coverage extension method. With our findings and proposed methods on mesh connectivity, only 1% of UK premises will require mesh radios to achieve the desired coverage. Full article
(This article belongs to the Special Issue Applications of Intelligent Sensors in Smart Cities)
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11 pages, 3305 KiB  
Article
Prediction of RF-EMF Exposure by Outdoor Drive Test Measurements
by Shanshan Wang, Taghrid Mazloum and Joe Wiart
Telecom 2022, 3(3), 396-406; https://doi.org/10.3390/telecom3030021 - 28 Jun 2022
Cited by 11 | Viewed by 2996
Abstract
In this paper, we exploit the artificial neural network (ANN) model for a spatial reconstruction of radio-frequency (RF) electromagnetic field (EMF) exposure in an outdoor urban environment. To this end, we have carried out a drive test measurement campaign covering a large part [...] Read more.
In this paper, we exploit the artificial neural network (ANN) model for a spatial reconstruction of radio-frequency (RF) electromagnetic field (EMF) exposure in an outdoor urban environment. To this end, we have carried out a drive test measurement campaign covering a large part of Paris, along a route of approximately 65 Km. The electric (E) field strength has been recorded over a wide band ranging from 700 to 2700 MHz. From these measurement data, the E-field strength is extracted and computed for each frequency band of each telecommunication operator. First, the correlation between the E-fields at different frequency bands is computed and analyzed. The results show that a strong correlation of E-field levels is observed for bands belonging to the same operator. Then, we build ANN models with input data encompassing information related to distances to N neighboring base stations (BS), receiver location and time variation. We consider two different models. The first one is a fully connected ANN model, where we take into account the N nearest BSs ignoring the corresponding operator. The second one is a hybrid model, where we consider locally connected blocks with the N nearest BSs for each operator, followed by fully connected layers. The results show that the hybrid model achieves better performance than the fully connected one. Among N{3,5,7}, we found out that with N=3, the proposed hybrid model allows a good prediction of the exposure level while the maintaining acceptable complexity of the model. Full article
(This article belongs to the Special Issue Applications of Intelligent Sensors in Smart Cities)
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