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A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Electrical and Autonomous Vehicles".

Deadline for manuscript submissions: closed (31 August 2022) | Viewed by 27822

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Special Issue Editors

Prof. Dr. Darius Andriukaitis

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Guest Editor

Faculty of Electrical and Electronics Engineering, Department of Electronics Engineering, Kaunas University of Technology, 44249 Kaunas, Lithuania
Interests: energy harvesting; interactive electronic systems; electric vehicles; integrated information systems; indirect measurement methods; reinforcement learning
Special Issues, Collections and Topics in MDPI journals

Dr. Yongjun Pan

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Guest Editor

College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400030, China
Interests: vehicle system dynamics; lightweight design of automotive components
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Peter Brida

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Guest Editor

Faculty of Electrical Engineering and Information Technology, University of Zilina, Zilina, Slovakia
Interests: wireless positioning; modular positioning systems; ubiquitous positioning; satellite navigation systems; intelligent transport systems; mobile positioning; pedestrian dead reckoning; wireless communication
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The abundance of electronic solutions that are being developed and applied in smart cities is becoming an inevitable part of our life. On the other hand, the growing population is forcing us to look for new, more effective solutions. According to preliminary forecast and modeling results, population growth is expected to stop only at the end of this century (source: a Pew Research Center (pewresearch.org)). Rising demand for power, water supply and waste management, pedestrian safety, efficient use of electric vehicles, traffic jams, commuting, the identification of all road users and prediction of their travel path, and increasing air and noise levels are the most pressing issues in today’s cities. The place we live in has a huge impact on our lives. Advance planning is a feature of green development that reduces dependence on vehicles associated with increased greenhouse gas emissions. The development of eco-friendly cities includes the development and application of new efficient solutions and technologies such as efficient transport management, emission control and pollution control, energy efficiency and usage of renewable energy, resource efficiency, etc., and would ensure a better quality of life of the growing population.

This Special Issue aims to present high-quality research and recent advances of technologies towards eco-friendly cities.

You are invited to submit original papers on topics including but not limited to the following:

Traffic congestion systems;
Transportation efficiency;
Waste management;
Water supply;
Energy efficiency;
Sensors and their networks;
Internet of Things approaches for eco-friendly cities;
Assistance systems;
Connected and autonomous driving;
Emission and pollution control;
Noise pollution control;
Electric vehicles and bicycles sharing;
Pedestrian safety;
Eco-friendly cities inter-relationship with smart homes.

Prof. Dr. Darius Andriukaitis
Dr. Yongjun Pan
Prof. Dr. Peter Brida
Guest Editors

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. Electronics 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 2400 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

eco-friendly city
traffic congestion
transportation system
waste and water management
energy efficiency
sensors
IoT
emission
pollution
electric vehicles

Published Papers (12 papers)

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Editorial

Jump to: Research

4 pages, 192 KiB

Open AccessEditorial

Emerging Electronics Technologies and Solutions for Eco-Friendly Cities

by Darius Andriukaitis, Yongjun Pan and Peter Brida

Electronics 2023, 12(3), 476; https://doi.org/10.3390/electronics12030476 - 17 Jan 2023

Cited by 1 | Viewed by 1103

Abstract

The development of electronic solutions and their application to smart cities are an inevitability [...] Full article

(This article belongs to the Special Issue Emerging Electronics Technologies and Solutions for Eco-Friendly Cities)

Research

Jump to: Editorial

14 pages, 13815 KiB

Open AccessArticle

Prediction of Bucket Fill Factor of Loader Based on Three-Dimensional Information of Material Surface

by Shaojie Wang, Shengfeng Yu, Liang Hou, Binyun Wu and Yanfeng Wu

Electronics 2022, 11(18), 2841; https://doi.org/10.3390/electronics11182841 - 08 Sep 2022

Cited by 3 | Viewed by 1930

Abstract

The bucket fill factor is a core evaluation indicator for the optimization of the loader’s autonomous shoveling operation. Accurately predicting the bucket fill factor of the loader after different excavation trajectories is fundamental for optimizing the loader’s efficiency and energy cost. Therefore, this paper proposes a method for predicting the bucket fill factor of the loader based on the three-dimensional information of the material surface. Firstly, the co-simulation model of loader shoveling material is established based on the multi-body dynamics software RecurDyn and the discrete element method software (DEMS) EDEM, and the co-simulation is conducted under different excavation trajectories. Then, the three-dimensional material surface information before shovel excavation is obtained from DEMS, and the surface function of the material contour is fitted based on the corresponding shovel excavation trajectory information. Meanwhile, the volume of the material excavated by the loader is obtained by the numerical integration method, and it is divided by the rated bucket volume to obtain the estimated bucket fill factor. Finally, the actual volume of the material after the shovel excavation is divided by the rated bucket volume to obtain the accurate bucket fill factor. Based on this, the prediction model of the bucket fill factor is built. The experimental results show that the proposed method is feasible, with a maximum error of 4.3%, a root mean square error of 0.025 and an average absolute error of 0.021. The research work lays the foundation for predicting the bucket fill factor of construction machinery such as loaders and excavators under real working conditions, which is conducive to promoting the development of autonomous, unmanned, and intelligent construction machinery. Full article

(This article belongs to the Special Issue Emerging Electronics Technologies and Solutions for Eco-Friendly Cities)

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17 pages, 3145 KiB

Open AccessArticle

A Novel Seismocardiogram Mathematical Model for Simplified Adjustment of Adaptive Filter

by Gediminas Uskovas, Algimantas Valinevicius, Mindaugas Zilys, Dangirutis Navikas, Michal Frivaldsky, Michal Prauzek, Jaromir Konecny and Darius Andriukaitis

Electronics 2022, 11(15), 2444; https://doi.org/10.3390/electronics11152444 - 05 Aug 2022

Cited by 2 | Viewed by 1577

Abstract

Nonclinical measurements of a seismocardiogram (SCG) can diagnose cardiovascular disease (CVD) at an early stage, when a critical condition has not been reached, and prevents unplanned hospitalization. However, researchers are restricted when it comes to investigating the benefits of SCG signals for moving patients, because the public database does not contain such SCG signals. The analysis of a mathematical model of the seismocardiogram allows the simulation of the heart with cardiovascular disease. Additionally, the developed mathematical model of SCG does not totally replace the real cardio mechanical vibration of the heart. As a result, a seismocardiogram signal of 60 beats per min (bpm) was generated based on the main values of the main artefacts, their duration and acceleration. The resulting signal was processed by finite impulse response (FIR), infinitive impulse response (IRR), and four adaptive filters to obtain optimal signal processing settings. Meanwhile, the optimal filter settings were used to manage the real SCG signals of slowly moving or resting. Therefore, it is possible to validate measured SCG signals and perform advanced scientific research of seismocardiogram. Furthermore, the proposed mathematical model could enable electronic systems to measure the seismocardiogram with more accurate and reliable signal processing, allowing the extraction of more useful artefacts from the SCG signal during any activity. Full article

(This article belongs to the Special Issue Emerging Electronics Technologies and Solutions for Eco-Friendly Cities)

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20 pages, 10585 KiB

Open AccessArticle

Energy Flow Analysis of Excavator System Based on Typical Working Condition Load

by Deying Su, Liang Hou, Shaojie Wang, Xiangjian Bu and Xiaosong Xia

Electronics 2022, 11(13), 1987; https://doi.org/10.3390/electronics11131987 - 24 Jun 2022

Cited by 2 | Viewed by 1987

Abstract

Accurate energy flow results are the premise of excavator energy-saving control research. Only through an accurate energy flow analysis based on operating data can a practical excavator energy-saving control scheme be proposed. In order to obtain the excavator’s accurate energy flow, the excavator components’ performance and operating data requirements are obtained, and the experimental schemes are designed to collect it under typical working conditions. The typical working condition load is reconstructed based on wavelet decomposition, harmonic function, and theoretical weighting methods. This paper analyzes the excavator system’s energy flow under the typical working condition load. In operation conditions, the output energy of the engine only accounts for 50.21% of the engine’s fuel energy, and the actuation and the swing system account for 9.33% and 4%, respectively. In transportation conditions, the output energy of the engine only accounts for 49.80% of the engine’s fuel energy, and the torque converter efficiency loss and excavator driving energy account for 15.09% and 17.98%, respectively. The research results show that the energy flow analysis method based on typical working condition load can accurately obtain each excavator component’s energy margin, which provides a basis for designing energy-saving schemes and control strategies. Full article

(This article belongs to the Special Issue Emerging Electronics Technologies and Solutions for Eco-Friendly Cities)

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14 pages, 2373 KiB

Open AccessArticle

Performance Analysis on Low-Power Energy Harvesting Wireless Sensors Eco-Friendly Networks with a Novel Relay Selection Scheme

by Hoang-Sy Nguyen, Lukas Sevcik and Hoang-Phuong Van

Electronics 2022, 11(13), 1978; https://doi.org/10.3390/electronics11131978 - 24 Jun 2022

Cited by 3 | Viewed by 1292

Abstract

Simultaneous wireless information and power transfer (SWIPT) has been utilized widely in wireless sensor networks (WSNs) to design systems that can be sustained by harvesting energy from the surrounding areas. In this study, we investigated the performance of the low-power energy harvesting (LPEH) WSN. We equipped each relay with a battery that consisted of an on/off (1/0) decision scheme according to the Markov property. In this context, an optimal loop interference relay selection was proposed and investigated. Moreover, the crucial role of the log-normal distribution method in characterizing the LPEH WSN’s constraints was proven and emphasized. System performance was evaluated in terms of the overall ergodic outage probability (OP) both analytically and numerically with Monte Carlo simulation. The system had the lowest overall ergodic OP, thus, performed the best with an energy harvesting time switch of 0.175. Following the increase in the signal-to-noise ratio (SNR), the system without a direct link performed the worst. Furthermore, as more relays were deployed, the better the system performed. Finally, results showed that more than 80% of the data rates can be obtained under the household condition, without the need for extra bandwidth and power supply. Full article

(This article belongs to the Special Issue Emerging Electronics Technologies and Solutions for Eco-Friendly Cities)

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19 pages, 5200 KiB

Open AccessArticle

Performance Enhancement of Functional Delay and Sum Beamforming for Spherical Microphone Arrays

by Yang Zhao, Zhigang Chu and Linyong Li

Electronics 2022, 11(7), 1132; https://doi.org/10.3390/electronics11071132 - 02 Apr 2022

Cited by 3 | Viewed by 1678

Abstract

Functional delay and sum (FDAS) beamforming for spherical microphone arrays can achieve 360° panoramic acoustic source identification, thus having broad application prospects for identifying interior noise sources. However, its acoustic imaging suffers from severe sidelobe contamination under a low signal-to-noise ratio (SNR), which deteriorates the sound source identification performance. In order to overcome this issue, the cross-spectral matrix (CSM) of the measured sound pressure signal is reconstructed with diagonal reconstruction (DRec), robust principal component analysis (RPCA), and probabilistic factor analysis (PFA). Correspondingly, three enhanced FDAS methods, namely EFDAS-DRec, EFDAS-RPCA, and EFDAS-PFA, are established. Simulations show that the three methods can significantly enhance the sound source identification performance of FDAS under low SNRs. Compared with FDAS at SNR = 0 dB and the number of snapshots = 1000, the average maximum sidelobe levels of EFDAS-DRec, EFDAS-RPCA, and EFDAS-PFA are reduced by 6.4 dB, 21.6 dB, and 53.1 dB, respectively, and the mainlobes of sound sources are shrunk by 43.5%, 69.0%, and 80.0%, respectively. Moreover, when the number of snapshots is sufficient, the three EFDAS methods can improve both the quantification accuracy and the weak source localization capability. Among the three EFDAS methods, EFDAS-DRec has the highest quantification accuracy, and EFDAS-PFA has the best localization ability for weak sources. The effectiveness of the established methods and the correctness of the simulation conclusions are verified by the acoustic source identification experiment in an ordinary room, and the findings provide a more advanced test and analysis tool for noise source identification in low-SNR cabin environments. Full article

(This article belongs to the Special Issue Emerging Electronics Technologies and Solutions for Eco-Friendly Cities)

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16 pages, 2223 KiB

Open AccessArticle

Driver Cardiovascular Disease Detection Using Seismocardiogram

by Gediminas Uskovas, Algimantas Valinevicius, Mindaugas Zilys, Dangirutis Navikas, Michal Frivaldsky, Michal Prauzek, Jaromir Konecny and Darius Andriukaitis

Electronics 2022, 11(3), 484; https://doi.org/10.3390/electronics11030484 - 07 Feb 2022

Cited by 4 | Viewed by 2180

Abstract

This article deals with the treatment and application of cardiac biosignals, an excited accelerometer, and a gyroscope in the prevention of accidents on the road. Previously conducted studies say that the seismocardiogram is a measure of cardiac microvibration signals that allows for detecting rhythms, heart valve opening and closing disorders, and monitoring of patients’ breathing. This article refers to the seismocardiogram hypothesis that the measurements of a seismocardiogram could be used to identify drivers’ heart problems before they reach a critical condition and safely stop the vehicle by informing the relevant departments in a nonclinical manner. The proposed system works without an electrocardiogram, which helps to detect heart rhythms more easily. The estimation of the heart rate (HR) is calculated through automatically detected aortic valve opening (AO) peaks. The system is composed of two micro-electromechanical systems (MEMSs) to evaluate physiological parameters and eliminate the effects of external interference on the entire system. The few digital filtering methods are discussed and benchmarked to increase seismocardiogram efficiency. As a result, the fourth adaptive filter obtains the estimated HR = 65 beats per min (bmp) in a still noisy signal (SNR = −11.32 dB). In contrast with the low processing benefit (3.39 dB), 27 AO peaks were detected with a 917.56-ms peak interval mean over 1.11 s, and the calculated root mean square error (RMSE) was 0.1942 m/s² when the adaptive filter order is 50 and the adaptation step is equal to 0.933. Full article

(This article belongs to the Special Issue Emerging Electronics Technologies and Solutions for Eco-Friendly Cities)

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25 pages, 3506 KiB

Open AccessArticle

Rescheduling of Distributed Manufacturing System with Machine Breakdowns

by Xiaohui Zhang, Yuyan Han, Grzegorz Królczyk, Marek Rydel, Rafal Stanislawski and Zhixiong Li

Electronics 2022, 11(2), 249; https://doi.org/10.3390/electronics11020249 - 13 Jan 2022

Cited by 7 | Viewed by 1559

Abstract

This study attempts to explore the dynamic scheduling problem from the perspective of operational research optimization. The goal is to propose a rescheduling framework for solving distributed manufacturing systems that consider random machine breakdowns as the production disruption. We establish a mathematical model that can better describe the scheduling of the distributed blocking flowshop. To realize the dynamic scheduling, we adopt an “event-driven” policy and propose a two-stage “predictive-reactive” method consisting of two steps: initial solution pre-generation and rescheduling. In the first stage, a global initial schedule is generated and considers only the deterministic problem, i.e., optimizing the maximum completion time of static distributed blocking flowshop scheduling problems. In the second stage, that is, after the breakdown occurs, the rescheduling mechanism is triggered to seek a new schedule so that both maximum completion time and the stability measure of the system can be optimized. At the breakdown node, the operations of each job are classified and a hybrid rescheduling strategy consisting of “right-shift repair + local reorder” is performed. For local reorder, we designed a discrete memetic algorithm, which embeds the differential evolution concept in its search framework. To test the effectiveness of DMA, comparisons with mainstream algorithms are conducted on instances with different scales. The statistical results show that the ARPDs obtained from DMA are improved by 88%. Full article

(This article belongs to the Special Issue Emerging Electronics Technologies and Solutions for Eco-Friendly Cities)

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16 pages, 8216 KiB

Open AccessFeature PaperArticle

Coal Thickness Prediction Method Based on VMD and LSTM

by Yaping Huang, Lei Yan, Yan Cheng, Xuemei Qi and Zhixiong Li

Electronics 2022, 11(2), 232; https://doi.org/10.3390/electronics11020232 - 12 Jan 2022

Cited by 11 | Viewed by 1687

Abstract

The change in coal seam thickness has an important influence on coal mine safety and efficient mining. It is very important to predict coal thickness accurately. However, the accuracy of borehole interpolation and BP neural network is not high. Variational mode decomposition (VMD) has strong denoising ability, and the long short-term memory neural network (LSTM) is especially suitable for the prediction of complex sequences. This paper presents a method of coal thickness prediction using VMD and LSTM. Firstly, empirical mode decomposition (EMD) and VMD methods are used to denoise simple signals, and the denoising effect of the VMD method is verified. Then, the wedge-shaped coal thickness model is constructed, and the seismic forward modeling and analysis are carried out. The results show that the coal thickness prediction based on seismic attributes is feasible. On the basis of VMD denoising of the original 3D seismic data, VMD-LSTM is used to predict coal thickness and compared with the prediction results of the traditional BP neural network. The coal thickness prediction method proposed in this paper has high accuracy and basically coincides with the coal seam information exposed by existing boreholes. The minimum absolute error of the predicted coal thickness is only 0.08 m, and the maximum absolute error is 0.48 m. This indicates that VMD-LSTM has high accuracy in predicting coal thickness. The proposed coal thickness prediction method can be used as a new method for coal thickness prediction. Full article

(This article belongs to the Special Issue Emerging Electronics Technologies and Solutions for Eco-Friendly Cities)

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20 pages, 3916 KiB

Open AccessFeature PaperArticle

A Sensor-Based Drone for Pollutants Detection in Eco-Friendly Cities: Hardware Design and Data Analysis Application

by Roberto De Fazio, Leonardo Matteo Dinoi, Massimo De Vittorio and Paolo Visconti

Electronics 2022, 11(1), 52; https://doi.org/10.3390/electronics11010052 - 24 Dec 2021

Cited by 19 | Viewed by 6550

Abstract

The increase in produced waste is a symptom of inefficient resources usage, which should be better exploited as a resource for energy and materials. The air pollution generated by waste causes impacts felt by a large part of the population living in and around the main urban areas. This paper presents a mobile sensor node for monitoring air and noise pollution; indeed, the developed system is installed on an RC drone, quickly monitoring large areas. It relies on a Raspberry Pi Zero W board and a wide set of sensors (i.e., NO₂, CO, NH₃, CO₂, VOCs, PM_2.5, and PM₁₀) to sample the environmental parameter at regular time intervals. A proper classification algorithm was developed to quantify the traffic level from the noise level (NL) acquired by the onboard microphone. Additionally, the drone is equipped with a camera and implements a visual recognition algorithm (Fast R-CNN) to detect waste fires and mark them by a GPS receiver. Furthermore, the firmware for managing the sensing unit operation was developed, as well as the power supply section. In particular, the node’s consumption was analysed in two use cases, and the battery capacity needed to power the designed device was sized. The onfield tests demonstrated the proper operation of the developed monitoring system. Finally, a cloud application was developed to remotely monitor the information acquired by the sensor-based drone and upload them on a remote database. Full article

(This article belongs to the Special Issue Emerging Electronics Technologies and Solutions for Eco-Friendly Cities)

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13 pages, 2178 KiB

Open AccessArticle

Beacon-Based Hybrid Routing Protocol for Large-Scale Unmanned Vehicle Ad Hoc Network

by Weiwei Mu, Guang Li, Yulin Ma, Rendong Wang, Yanbo Li and Zhixiong Li

Electronics 2021, 10(24), 3129; https://doi.org/10.3390/electronics10243129 - 16 Dec 2021

Cited by 3 | Viewed by 1830

Abstract

In this paper, we designed a beacon-based hybrid routing protocol to adapt to the new forms of intelligent warfare, accelerate the application of unmanned vehicles in the military field, and solve the problems such as high maintenance cost, path failure, and repeated routing pathfinding in large-scale unmanned vehicle network communications for new battlefields. This protocol used the periodic broadcast pulses initiated by the beacon nodes to provide synchronization and routing to the network and established a spanning tree through which the nodes communicated with each other. An NS3 platform was used to build a dynamic simulation environment of service data to evaluate the network performance. The results showed that when it was used in a range of 5 ~ 35 communication links, the beacon-based routing protocol’s PDR was approximately 10% higher than that of AODV routing protocol. At 5 ~ 50 communication links, the result was approximately 20% higher than the DSDV routing protocol. The routing load was not related to the number of nodes and communication link data and the protocol had better performance than traditional AODV and DSDV routing protocol, which reduced the cost of the routing protocol and effectively improved the stability and reliability of the network. The protocol we designed is more suitable for the scenarios of large-scale unmanned vehicle network communication in the future AI battlefield. Full article

(This article belongs to the Special Issue Emerging Electronics Technologies and Solutions for Eco-Friendly Cities)

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25 pages, 2541 KiB

Open AccessArticle

Design Thinking as a Framework for the Design of a Sustainable Waste Sterilization System: The Case of Piedmont Region, Italy

by Ivonne Angelica Castiblanco Jimenez, Stefano Mauro, Domenico Napoli, Federica Marcolin, Enrico Vezzetti, Maria Camila Rojas Torres, Stefania Specchia and Sandro Moos

Electronics 2021, 10(21), 2665; https://doi.org/10.3390/electronics10212665 - 31 Oct 2021

Cited by 12 | Viewed by 3005

Abstract

The development of new methods for the correct disposal of waste is unavoidable for any city that aims to become eco-friendly. Waste management is no exception. In the modern era, the treatment and disposal of infectious waste should be seen as an opportunity to generate renewable energy, resource efficiency, and, above all, to improve the population’s quality of life. Northern Italy currently produces 66,600 tons/year of infectious waste, mostly treated through incineration plants. This research aims to explore a more ecological and sustainable solution, thereby contributing one more step toward achieving better cities for all. Particularly, this paper presents a conceptual design of the main sterilization chamber for infectious waste. The methodology selected was Design Thinking (DT), since it has a user-centered approach which allows for co-design and the inclusion of the target population. This study demonstrates to the possibility of obtaining feasible results based on the user’s needs through the application of DT as a framework for engineering design. Full article

(This article belongs to the Special Issue Emerging Electronics Technologies and Solutions for Eco-Friendly Cities)

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