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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A1: Smart Grids and Microgrids".

Deadline for manuscript submissions: closed (30 September 2021) | Viewed by 14875

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Dr. Manuel Moreno-Eguilaz

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Guest Editor

Department of Electronic Engineering, Technical University of Catalonia, UPC BarcelonaTech, 08028 Barcelona, Spain
Interests: deep learning; smart IoT devices; predictive maintenance; secure communications; fault-tolerant systems; identification and control of power converters
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Special Issue Information

Dear Colleagues,

The Internet of Things means billions of physical devices around the world collecting and sending data to the cloud through an internet connection. Things have become smart thanks to the synergy of sensors, artificial intelligence, and wireless communications. Cloud computing may make new bussiness, optimizing everything around the world. State-of-the-art wireless communications allow near real-time transmission and reception of data at a very low cost and with a minimum consumed energy. What is more, communications can be bi-directional, allowing near real-time remote control of smart devices.

This Special Issue will pay attention to near real-time applications of smart devices. Topics of interest for publication include but are not limited to:

Near real-time applications of any kind of smart devices;
Cloud computing for near real-time IoT applications;
Communications for near real-time IoT applications;
IoT platforms for near real-time IoT applications;
Critical aspects (cost, consumption, baudrate, range, etc.) of near real-time IoT applications;
Tools, harware, and software to develop and validate near real-time IoT applications;
Artificial Intelligence for near real-time IoT applications.

Prof. Manuel Moreno
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

Near real-time monitoring and control
IoT applications
Smart IoT
Wireless communications networks
IoT platforms
Cloud computing
Contextual intelligence
Artificial intelligence for IoT applications.

Published Papers (4 papers)

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Research

34 pages, 1836 KiB

Open AccessArticle

A New Hybrid Online and Offline Multi-Factor Cross-Domain Authentication Method for IoT Applications in the Automotive Industry

by Haqi Khalid, Shaiful Jahari Hashim, Sharifah Mumtazah Syed Ahmad, Fazirulhisyam Hashim and Muhammad Akmal Chaudhary

Energies 2021, 14(21), 7437; https://doi.org/10.3390/en14217437 - 08 Nov 2021

Cited by 3 | Viewed by 2585

Abstract

Connected vehicles have emerged as the latest revolution in the automotive industry, utilizing the advent of the Internet of Things (IoT). However, most IoT-connected cars mechanisms currently depend on available network services and need continuous network connections to allow users to connect to their vehicles. Nevertheless, the connectivity availability shortcoming in remote or rural areas with no network coverage makes vehicle sharing or any IoT-connected device problematic and undesirable. Furthermore, IoT-connected cars are vulnerable to various passive and active attacks (e.g., replay attacks, MiTM attacks, impersonation attacks, and offline guessing attacks). Adversaries could all use these attacks to disrupt networks posing a threat to the entire automotive industry. Therefore, to overcome this issue, we propose a hybrid online and offline multi-factor authentication cross-domain authentication method for a connected car-sharing environment based on the user’s smartphone. The proposed scheme lets users book a vehicle using the online booking phase based on the secured and trusted Kerberos workflow. Furthermore, an offline authentication phase uses the OTP algorithm to authenticate registered users even if the connectivity services are unavailable. The proposed scheme uses the AES-ECC algorithm to provide secure communication and efficient key management. The formal SOV logic verification was used to demonstrate the security of the proposed scheme. Furthermore, the AVISPA tool has been used to check that the proposed scheme is secured against passive and active attacks. Compared to the previous works, the scheme requires less computation due to the lightweight cryptographic algorithms utilized. Finally, the results showed that the proposed system provides seamless, secure, and efficient authentication operation for the automotive industry, specifically car-sharing systems, making the proposed system suitable for applications in limited and intermittent network connections. Full article

(This article belongs to the Special Issue Near Real-Time Smart IoT Applications)

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17 pages, 5798 KiB

Open AccessArticle

Optimization and Performance Assessment of a Logic Selectivity Solution Based on LoRa Communication

by Annalisa Liccardo, Francesco Bonavolontà, Ignazio Romano and Rosario Schiano Lo Moriello

Energies 2021, 14(21), 7359; https://doi.org/10.3390/en14217359 - 05 Nov 2021

Cited by 2 | Viewed by 1345

Abstract

Ensuring service continuity has become a fundamental issue for companies involved in electricity distribution; in particular, isolating the smallest possible portion of the network as a result of faults has long been a primary objective. To this aim, solutions based on logic selectivity have been defined and implemented for an efficient search for the network branch affected by the fault and its subsequent isolation. The authors have recently presented a proposal for the implementation of logic selectivity that exploits the LoRa transmission protocol, an ideal solution in the case of areas not reachable by the currently exploited communication technologies. The present paper, instead, deals with the optimization of some LoRa parameters, which made it possible to exploit network configurations in terms of coverage range, sensitivity and signal-to-noise ratio. The performance of the new configuration has been assessed through a number of tests conducted in the laboratory and on-field, highlighting promising results in terms of both intervention times and reliability. In particular, tests conducted in both rural and urban areas have assured fault isolation times as low as 33 ms (fully compliant with the current regulations) in the presence of the most challenging fault condition. Full article

(This article belongs to the Special Issue Near Real-Time Smart IoT Applications)

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17 pages, 3691 KiB

Open AccessArticle

Providing Energy Self-Sufficiency to LoRaWAN Nodes by Means of Thermoelectric Generators (TEGs)-Based Energy Harvesting

by Irene Cappelli, Stefano Parrino, Alessandro Pozzebon and Alessio Salta

Energies 2021, 14(21), 7322; https://doi.org/10.3390/en14217322 - 04 Nov 2021

Cited by 10 | Viewed by 2423

Abstract

The aim of this paper is to present the viability of an energy-harvesting system prototype, based on thermoelectric generators (TEGs), to be embedded in a Long-Range Wide Area Network (LoRaWAN)-based wireless sensor node, allowing continuous quasi-real-time data transmission even for low temperature gradients and for frequent transmissions. To this end, an RFM95x LoRa module is used in the system. The energy management of the entire node is achieved by exploiting a nano power boost charger buck converter integrated circuit, which allows power extraction from the energy-harvesting source and, at the same time, regulates the charging/discharging process of a Li-Po battery that supplies the wireless node. The first phase of the project was dedicated to understanding the electrical characteristics of the TEG. A series of tests were performed to study the open circuit voltage, the current and the power generated by the TEG at different temperature gradients. Following this first phase, tests were then set up to study the charging/discharging process of the battery by changing two crucial parameters: the temperature between the faces of the TEG and the frequency of the transmissions performed by the transceiver. Experimental results show a positive balance for the battery charging at different conditions, which suggests two important conclusions: first of all, with high temperature gradients, it is possible to set relatively high transmission frequencies for the LoRaWAN module without discharging the battery. The second important consideration concerns the operation of the system at extremely low temperature gradients, with a minimum of 5 °C reached during one of the measurements. This suggests the usability of thermoelectric energy-harvesting systems in a wide range of possible applications even in conditions of low temperature gradients. Full article

(This article belongs to the Special Issue Near Real-Time Smart IoT Applications)

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20 pages, 1586 KiB

Open AccessFeature PaperArticle

Secure Elliptic Curve Crypto-Processor for Real-Time IoT Applications

by Stefano Di Matteo, Luca Baldanzi, Luca Crocetti, Pietro Nannipieri, Luca Fanucci and Sergio Saponara

Energies 2021, 14(15), 4676; https://doi.org/10.3390/en14154676 - 01 Aug 2021

Cited by 31 | Viewed by 7580

Abstract

Cybersecurity is a critical issue for Real-Time IoT applications since high performance and low latencies are required, along with security requirements to protect the large number of attack surfaces to which IoT devices are exposed. Elliptic Curve Cryptography (ECC) is largely adopted in an IoT context to provide security services such as key-exchange and digital signature. For Real-Time IoT applications, hardware acceleration for ECC-based algorithms can be mandatory to meet low-latency and low-power/energy requirements. In this paper, we propose a fast and configurable hardware accelerator for NIST P-256/-521 elliptic curves, developed in the context of the European Processor Initiative. The proposed architecture supports the most used cryptography schemes based on ECC such as Elliptic Curve Digital Signature Algorithm (ECDSA), Elliptic Curve Integrated Encryption Scheme (ECIES), Elliptic Curve Diffie-Hellman (ECDH) and Elliptic Curve Menezes-Qu-Vanstone (ECMQV). A modified version of Double-And-Add-Always algorithm for Point Multiplication has been proposed, which allows the execution of Point Addition and Doubling operations concurrently and implements countermeasures against power and timing attacks. A simulated approach to extract power traces has been used to assess the effectiveness of the proposed algorithm compared to classical algorithms for Point Multiplication. A constant-time version of the Shamir’s Trick has been adopted to speed-up the Double-Point Multiplication and modular inversion is executed using Fermat’s Little Theorem, reusing the internal modular multipliers. The accelerator has been verified on a Xilinx ZCU106 development board and synthesized on both 45 nm and 7 nm Standard-Cell technologies. Full article

(This article belongs to the Special Issue Near Real-Time Smart IoT Applications)

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