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IoT for Energy Management Systems and Smart Cities, 2nd Volume
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Electrical Engineering Department, University of Jaen, Campus Las Lagunillas, s/n, 23071 Jaen, Spain
Electrical Engineering Department, University of Jaen, Campus Las Lagunillas, s/n, 23071 Jaen, Spain
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IoT for Energy Management Systems and Smart Cities, 2nd Volume

Abstract submission deadline
30 January 2025
Manuscript submission deadline
30 April 2025
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4713

Topic Information

Dear Colleagues,

This Topic is a continuation of the previous successful Topic “IoT for Energy Management Systems and Smart Cities”.

Smart cities represent a great advance in terms of sustainability, energy efficiency, and being able to respond to the needs of enterprises, institutions, and inhabitants.

In this sense, smart grids contribute to the development of smart cities in the field of electrical energy, including concepts such as renewable energies, distributed generation, energy efficiency, and smart homes and automation.

In order to be able to implement all the functionalities of smart grids, it is necessary to have real-time information on the different installations. In this sense, IoT plays a fundamental role in developing smart grids.

Cloud computing, which integrates the data obtained with smart electrical meters, smart electrical power analyzers, and other intelligent metering devices, contributes to the availability of the measured data in real time and provides intelligence to existing electrical networks.

Wireless communication networks, especially LPWAN, allow the construction of devices with low energy consumption and high operating autonomy, which can be installed in different locations even with difficult access.

The massive implantation of the electric vehicle implies the construction of charging stations. These stations must use renewable energy sources that contribute to saving fossil fuels, reducing CO2, and increasing the sustainability of electric mobility.

Hybrid storage systems, together with renewable energies, constitute new development systems, in which it is necessary to measure electrical variables and control the operation of the system.

Prof. Dr. Antonio Cano-Ortega
Prof. Dr. Francisco Sánchez-Sutil
Topic Editors

Keywords

  • cloud computing
  • smart electric meters
  • smart power analyzers
  • smart grids for smart cities
  • smart home and automation
  • monitoring and control renewable energy
  • public lighting system
  • distributed generation
  • hybrid electric energy storage systems 
  • electric vehicle charging stations 
  • wireless technologies

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Energies
energies 		3.0 6.2 2008 17.5 Days CHF 2600 Submit
Sensors
sensors 		3.4 7.3 2001 16.8 Days CHF 2600 Submit
Electronics
electronics 		2.6 5.3 2012 16.8 Days CHF 2400 Submit
Smart Cities
smartcities 		7.0 11.2 2018 25.8 Days CHF 2000 Submit
IoT
IoT 		- 8.5 2020 15.9 Days CHF 1200 Submit

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Published Papers (3 papers)

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26 pages, 2842 KiB  
Article
Industrial IoT-Based Energy Monitoring System: Using Data Processing at Edge
by Akseer Ali Mirani, Anshul Awasthi, Niall O’Mahony and Joseph Walsh
IoT 2024, 5(4), 608-633; https://doi.org/10.3390/iot5040027 - 28 Sep 2024
Viewed by 1237
Abstract
Edge-assisted IoT technologies combined with conventional industrial processes help evolve diverse applications under the Industrial IoT (IIoT) and Industry 4.0 era by bringing cloud computing technologies near the hardware. The resulting innovations offer intelligent management of the industrial ecosystems, focusing on increasing productivity [...] Read more.
Edge-assisted IoT technologies combined with conventional industrial processes help evolve diverse applications under the Industrial IoT (IIoT) and Industry 4.0 era by bringing cloud computing technologies near the hardware. The resulting innovations offer intelligent management of the industrial ecosystems, focusing on increasing productivity and reducing running costs by processing massive data locally. In this research, we design, develop, and implement an IIoT and edge-based system to monitor the energy consumption of a factory floor’s stationary and mobile assets using wireless and wired energy meters. Once the edge receives the meter’s data, it stores the information in the database server, followed by the data processing method to find nine additional analytical parameters. The edge also provides a master user interface (UI) for comparative analysis and individual UI for in-depth energy usage insights, followed by activity and inactivity alarms and daily reporting features via email. Moreover, the edge uses a data-filtering technique to send a single wireless meter’s data to the cloud for remote energy and alarm monitoring per project scope. Based on the evaluation, the edge server efficiently processes the data with an average CPU utilization of up to 5.58% while avoiding measurement errors due to random power failures throughout the day. Full article
(This article belongs to the Topic IoT for Energy Management Systems and Smart Cities, 2nd Volume)
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29 pages, 9969 KiB  
Article
Calibration of a Class A Power Quality Analyser Connected to the Cloud in Real Time
by A. Cano-Ortega, F. Sanchez-Sutil, J. C. Hernandez, C. Gilabert-Torres and C. R. Baier
Electronics 2024, 13(16), 3209; https://doi.org/10.3390/electronics13163209 - 13 Aug 2024
Viewed by 846
Abstract
Power quality measurements are essential to monitor, analyse and control the operation of smart grids within power systems. This work aims to develop and calibrate a PQ network analyser. As the penetration of non-linear loads connected to power systems is increasing every day, [...] Read more.
Power quality measurements are essential to monitor, analyse and control the operation of smart grids within power systems. This work aims to develop and calibrate a PQ network analyser. As the penetration of non-linear loads connected to power systems is increasing every day, it is essential to measure power quality. In this sense, a power quality (PQ) analyser is based on the high-speed sampling of electrical signals in single-phase and three-phase electrical installations, which are available in real time for analysis using wireless Wi-Fi (Wireless-Fidelity) networks. The PQAE (Power Quality Analyser Embedded) power quality analyser has met the calibration standards for Class A devices from IEC 61000-4-30, IEC 61000-4-7 and IEC 62586-2. In this paper, a complete guide to the tests included in this standard has been provided. The Fast Fourier Transform (FFT) obtains the harmonic components from the measured signals and the window functions used reduce spectral leakage. The window size depends on the fundamental frequency of, intensity of and changes in the signal. Harmonic measurements from the 2nd to 50th harmonics for each phase of the voltage and each phase and neutral of the current have been performed, using the Fast Fourier transform algorithm with various window functions and their comparisons. PQAE is developed on an open-source platform that allows you to adapt its programming to the measurement needs of the users. Full article
(This article belongs to the Topic IoT for Energy Management Systems and Smart Cities, 2nd Volume)
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29 pages, 8934 KiB  
Article
Delay and Energy Efficient Offloading Strategies for an IoT Integrated Water Distribution System in Smart Cities
by Nibi Kulangara Velayudhan, Aiswarya S, Aryadevi Remanidevi Devidas and Maneesha Vinodini Ramesh
Smart Cities 2024, 7(1), 179-207; https://doi.org/10.3390/smartcities7010008 - 16 Jan 2024
Viewed by 1511
Abstract
In the fast-moving world of information and communications technologies, one significant issue in metropolitan cities is water scarcity and the need for an intelligent water distribution system for sustainable water management. An IoT-based monitoring system can improve water distribution system management and mitigate [...] Read more.
In the fast-moving world of information and communications technologies, one significant issue in metropolitan cities is water scarcity and the need for an intelligent water distribution system for sustainable water management. An IoT-based monitoring system can improve water distribution system management and mitigate challenges in the distribution network networks such as leakage, breakage, theft, overflow, dry running of pumps and so on. However, the increase in the number of communication and sensing devices within smart cities has evoked challenges to existing communication networks due to the increase in delay and energy consumption within the network. The work presents different strategies for efficient delay and energy offloading in IoT-integrated water distribution systems in smart cities. Different IoT-enabled communication network topology diagrams are proposed, considering the different water network design parameters, land cover patterns and wireless channels for communication. From these topologies and by considering all the relevant communication parameters, the optimum communication network architecture to continuously monitor a water distribution network in a metropolitan city in India is identified. As a case study, an IoT design and analysis model is studied for a secondary metropolitan city in India. The selected study area is in Kochi, India. Based on the site-specific model and land use and land cover pattern, delay and energy modeling of the IoT-based water distribution system is discussed. Algorithms for node categorisation and edge-to-fog allocation are discussed, and numerical analyses of delay and energy models are included. An approximation of the delay and energy of the network is calculated using these models. On the basis of these study results, and state transition diagrams, the optimum placement of fog nodes linked with edge nodes and a cloud server could be carried out. Also, by considering different scenarios, up to a 40% improvement in energy efficiency can be achieved by incorporating a greater number of states in the state transition diagram. These strategies could be utilized in implementing delay and energy-efficient IoT-enabled communication networks for site-specific applications. Full article
(This article belongs to the Topic IoT for Energy Management Systems and Smart Cities, 2nd Volume)
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