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Energy Efficiency for IoT Systems
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Energy Efficiency for IoT Systems

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F: Electrical Engineering".

Deadline for manuscript submissions: closed (31 August 2021) | Viewed by 28501

Special Issue Editor

Prof. Dr. Adam Glowacz

E-Mail Website
Guest Editor
Department of Automatic, Control and Robotics, AGH University of Science and Technology, 30-059 Kraków, Poland
Interests: machine; fault diagnosis; pattern recognition; IoT; signal processing; signal analysis; image processing; computer science; automatic
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear colleagues,

The proposed Special Issue will cover advanced research in energy-efficient system design for smart cities, healthcare, industrial applications, and commercial buildings. Around 30% of global energy is consumed by buildings. That fact alone presents a high-value opportunity to achieve the next level of energy saving. For smart city design, energy management could be the first step towards fully integrated IoT strategies that optimize productivity and ultimately realize cost-saving goals. Smart IoT solutions could be adopted to reduce wasted energy in various sectors such as smart cities, healthcare, industrial applications, and commercial buildings. Smart energy management is the key to delivering cost-effective and proactive solutions in any ecosystem. The real-time monitoring of all assets leads to improved forecasts and outage management and simultaneously reduces site visits and costly downtimes. This Special Issue will present some of the latest innovations for the development of energy-efficient systems for IoT applications, such as in underwater wireless systems, intelligent transportation systems, medical robotics, wireless condition monitoring systems, and electrical power distribution systems. Potential topics include but are not limited to the following:

  • Energy efficiency
  • IoT-enabled medical systems
  • IoT-based wireless condition monitoring
  • IoT-based system design
  • Energy-efficient smart cities
  • Energy-efficient and intelligent transportation systems
  • Future of IoT
  • Heterogeneous networks for efficient IoT systems

Dr. Adam Glowacz
Guest Editor

Manuscript Submission Information

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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

  • energy efficiency
  • IoT-enabled medical systems
  • IoT-based wireless condition monitoring
  • IoT-based system design
  • energy-efficient smart cities
  • energy-efficient and intelligent transportation systems
  • future of IoT
  • heterogeneous networks for efficient IoT systems

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Published Papers (6 papers)

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Research

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30 pages, 6079 KiB  
Article
Smart Fire Detection and Deterrent System for Human Savior by Using Internet of Things (IoT)
by Abdul Rehman, Muhammad Ahmed Qureshi, Tariq Ali, Muhammad Irfan, Saima Abdullah, Sana Yasin, Umar Draz, Adam Glowacz, Grzegorz Nowakowski, Abdullah Alghamdi, Abdulaziz A. Alsulami and Mariusz Węgrzyn
Energies 2021, 14(17), 5500; https://doi.org/10.3390/en14175500 - 3 Sep 2021
Cited by 22 | Viewed by 6270
Abstract
Fire monitoring systems have usually been based on a single sensor such as smoke or flame. These single sensor systems have been unable to distinguish between true and false presence of fire, such as a smoke from a cigarette which might cause the [...] Read more.
Fire monitoring systems have usually been based on a single sensor such as smoke or flame. These single sensor systems have been unable to distinguish between true and false presence of fire, such as a smoke from a cigarette which might cause the fire alarm to go off. Consuming energy all day long and being dependent on one sensor that might end with false alert is not efficient and environmentally friendly. We need a system that is efficient not only in sensing fire accurately, but we also need a solution which is smart. In order to improve upon the results of existing single sensor systems, our system uses a combination of three sensors to increase the efficiency. The result from the sensor is then analyzed by a specified rule-set using an AI-based fuzzy logic algorithm; defined in the purposed research, our system detects the presence of fire. Our system is designed to make smart decisions based on the situation; it provides feature updated alerts and hardware controls such as enabling a mechanism to start ventilation if the fire is causing suffocation, and also providing water support to minimize the damage. The purposed system keeps updating the management about the current severity of the environment by continually sensing any change in the environment during fire. The purposed system proved to provide accurate results in the entire 15 test performed around different intensities of a fire situation. The simulation work for the SMDD is done using MATLAB and the result of the experiments is satisfactory. Full article
(This article belongs to the Special Issue Energy Efficiency for IoT Systems)
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15 pages, 3816 KiB  
Article
Role of TiO2 Phase Composition Tuned by LiOH on The Electrochemical Performance of Dual-Phase Li4Ti5O12-TiO2 Microrod as an Anode for Lithium-Ion Battery
by Lukman Noerochim, Wahyu Caesarendra, Abdulloh Habib, Widyastuti, Suwarno, Yatim Lailun Ni’mah, Achmad Subhan, Bambang Prihandoko and Buyung Kosasih
Energies 2020, 13(20), 5251; https://doi.org/10.3390/en13205251 - 9 Oct 2020
Cited by 6 | Viewed by 2798
Abstract
In this study, a dual-phase Li4Ti5O12-TiO2 microrod was successfully prepared using a modified hydrothermal method and calcination process. The stoichiometry of LiOH as precursor was varied at mol ratio of 0.9, 1.1, and 1.3, to obtain [...] Read more.
In this study, a dual-phase Li4Ti5O12-TiO2 microrod was successfully prepared using a modified hydrothermal method and calcination process. The stoichiometry of LiOH as precursor was varied at mol ratio of 0.9, 1.1, and 1.3, to obtain the appropriate phase composition between TiO2 and Li4Ti5O12. Results show that TiO2 content has an important role in increasing the specific capacity of electrodes. The refinement of X-ray diffraction patterns by Rietveld analysis confirm that increasing the LiOH stoichiometry suppresses the TiO2 phase. In the scanning electron microscopy images, the microrod morphology was formed after calcination with diameter sizes ranging from 142.34 to 260.62 nm and microrod lengths ranging from 5.03–7.37 μm. The 0.9 LiOH sample shows a prominent electrochemical performance with the largest specific capacity of 162.72 mAh/g and 98.75% retention capacity achieved at a rate capability test of 1 C. This finding can be attributed to the appropriate amount of TiO2 that induced the smaller crystallite size, and lower charge transfer resistance, enhancing the lithium-ion insertion/extraction process and faster diffusion kinetics. Full article
(This article belongs to the Special Issue Energy Efficiency for IoT Systems)
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15 pages, 5307 KiB  
Article
Optical-Interference Mitigation in Visible Light Communication for Intelligent Transport Systems Applications
by Muhammad Irfan, Usman Habib, Fazal Muhammad, Farman Ali, Abdullah S Alwadie, Shakir Ullah, Adam Glowacz and Witold Glowacz
Energies 2020, 13(19), 5064; https://doi.org/10.3390/en13195064 - 27 Sep 2020
Cited by 7 | Viewed by 3169
Abstract
Intelligent Transport Systems (ITS) are anticipated to be one of the key technologies for the next decade and their deployment can benefit from the recent developments in the domain of Visible Light Communication (VLC). Light Emitting Diode (LED)-based low-cost VLC is considered in [...] Read more.
Intelligent Transport Systems (ITS) are anticipated to be one of the key technologies for the next decade and their deployment can benefit from the recent developments in the domain of Visible Light Communication (VLC). Light Emitting Diode (LED)-based low-cost VLC is considered in this work to provide a practical approach towards the implementation of an ITS by addressing the major issues of channel noise, free-space optical multipath reflections and interference from light sources. An analytical model is presented for the proposed Multiple-Input–Single-Output (MISO)-based VLC, and simulations are performed to analyze the performance of the system for various transmission distances. Results show that the proposed optimal receiver for 4 × 1 MISO can provide considerable improvement in the bit error rate for the forward error correction (FEC) threshold of 3.8 × 10−3 in the presence of optical interference, and is suitable to support an ITS with an inter-vehicle transmission approach. The comparison of achieved performance with existing solutions for VLC-based ITS depicts that the proposed framework provides much higher data rates, three times longer transmission distance and improved receiver sensitivity. Full article
(This article belongs to the Special Issue Energy Efficiency for IoT Systems)
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22 pages, 3133 KiB  
Article
Waste Management and Prediction of Air Pollutants Using IoT and Machine Learning Approach
by Ayaz Hussain, Umar Draz, Tariq Ali, Saman Tariq, Muhammad Irfan, Adam Glowacz, Jose Alfonso Antonino Daviu, Sana Yasin and Saifur Rahman
Energies 2020, 13(15), 3930; https://doi.org/10.3390/en13153930 - 1 Aug 2020
Cited by 76 | Viewed by 9139
Abstract
Increasing waste generation has become a significant issue over the globe due to the rapid increase in urbanization and industrialization. In the literature, many issues that have a direct impact on the increase of waste and the improper disposal of waste have been [...] Read more.
Increasing waste generation has become a significant issue over the globe due to the rapid increase in urbanization and industrialization. In the literature, many issues that have a direct impact on the increase of waste and the improper disposal of waste have been investigated. Most of the existing work in the literature has focused on providing a cost-efficient solution for the monitoring of garbage collection system using the Internet of Things (IoT). Though an IoT-based solution provides the real-time monitoring of a garbage collection system, it is limited to control the spreading of overspill and bad odor blowout gasses. The poor and inadequate disposal of waste produces toxic gases, and radiation in the environment has adverse effects on human health, the greenhouse system, and global warming. While considering the importance of air pollutants, it is imperative to monitor and forecast the concentration of air pollutants in addition to the management of the waste. In this paper, we present and IoT-based smart bin using a machine and deep learning model to manage the disposal of garbage and to forecast the air pollutant present in the surrounding bin environment. The smart bin is connected to an IoT-based server, the Google Cloud Server (GCP), which performs the computation necessary for predicting the status of the bin and for forecasting air quality based on real-time data. We experimented with a traditional model (k-nearest neighbors algorithm (k-NN) and logistic reg) and a non-traditional (long short term memory (LSTM) network-based deep learning) algorithm for the creation of alert messages regarding bin status and forecasting the amount of air pollutant carbon monoxide (CO) present in the air at a specific instance. The recalls of logistic regression and k-NN algorithm is 79% and 83%, respectively, in a real-time testing environment for predicting the status of the bin. The accuracy of modified LSTM and simple LSTM models is 90% and 88%, respectively, to predict the future concentration of gases present in the air. The system resulted in a delay of 4 s in the creation and transmission of the alert message to a sanitary worker. The system provided the real-time monitoring of garbage levels along with notifications from the alert mechanism. The proposed works provide improved accuracy by utilizing machine learning as compared to existing solutions based on simple approaches. Full article
(This article belongs to the Special Issue Energy Efficiency for IoT Systems)
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16 pages, 3560 KiB  
Article
Improved Analysis on the Fin Reliability of a Plate Fin Heat Exchanger for Usage in LNG Applications
by Mustansar Hayat Saggu, Nadeem Ahmed Sheikh, Usama Muhamad Niazi, Muhammad Irfan, Adam Glowacz and Stanislaw Legutko
Energies 2020, 13(14), 3624; https://doi.org/10.3390/en13143624 - 14 Jul 2020
Cited by 5 | Viewed by 2424
Abstract
A plate fin heat exchanger (PFHE) is a critical part of the cryogenic industry. A plate fin heat exchanger has many applications, but it is commonly used in the liquefied natural gas (LNG) industry for the gasification/liquefaction process. During this gasification to the [...] Read more.
A plate fin heat exchanger (PFHE) is a critical part of the cryogenic industry. A plate fin heat exchanger has many applications, but it is commonly used in the liquefied natural gas (LNG) industry for the gasification/liquefaction process. During this gasification to the liquefaction process, there is a large temperature gradient. Due to this large temperature gradient, stresses are produced that directly influence the braze joint of PFHE. Significant work has been carried out on heat transfer and the flow enhancement of PFHE; however, little attention has been paid to structural stability and stresses produced in these brazed joints. Due to these stresses, leakages in PFHE are observed, mostly in braze joints. In the current study, standard fin design is analyzed. In addition, the structural stability of brazed joints under standard conditions is also tested. Two techniques are used here to analyze fins, using the finite element method (FEM), first by examining the whole fin brazed joint on the basis of experimentally calculated yield strength and second by dividing the braze seam into three sections and defining individual strength for each section of the seam to find stress magnitude on the basis of heat-affected zones. Moreover, by using two different techniques to analyze brazed joints, the stresses in the lower face of the brazed joint were increased by 13% and decreased by 18% in the upper face using different zone techniques as compared to standard full braze seam analysis. It can be concluded that different zone techniques are better in predicting stresses as compared to simple full braze seam analysis using the finite element method since stresses along the lower face are more critical. Full article
(This article belongs to the Special Issue Energy Efficiency for IoT Systems)
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Review

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16 pages, 2172 KiB  
Review
Progress in Development of Nanostructured Manganese Oxide as Catalyst for Oxygen Reduction and Evolution Reaction
by Jing Han Siow, Muhammad Roil Bilad, Wahyu Caesarendra, Jia Jia Leam, Mohammad Azmi Bustam, Nonni Soraya Sambudi, Yusuf Wibisono and Teuku Meurah Indra Mahlia
Energies 2021, 14(19), 6385; https://doi.org/10.3390/en14196385 - 6 Oct 2021
Cited by 17 | Viewed by 2637
Abstract
The rise in energy consumption is largely driven by the growth of population. The supply of energy to meet that demand can be fulfilled by slowly introducing energy from renewable resources. The fluctuating nature of the renewable energy production (i.e., affected by weather [...] Read more.
The rise in energy consumption is largely driven by the growth of population. The supply of energy to meet that demand can be fulfilled by slowly introducing energy from renewable resources. The fluctuating nature of the renewable energy production (i.e., affected by weather such as wind, sun light, etc.), necessitates the increasing demand in developing electricity storage systems. Reliable energy storage system will also play immense roles to support activities related to the internet of things. In the past decades, metal-air batteries have attracted great attention and interest for their high theoretical capacity, environmental friendliness, and their low cost. However, one of the main challenges faced in metal-air batteries is the slow rate of oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) that affects the charging and the discharging performance. Various types of nanostructure manganese oxide with high specific surface area and excellent catalytic properties have been synthesized and studied. This review provides a discussion of the recent developments of the nanostructure manganese oxide and their performance in oxygen reduction and oxygen evolution reactions in alkaline media. It includes the experimental work in the nanostructure of manganese oxide, but also the fundamental understanding of ORR and OER. A brief discussion on electrocatalyst kinetics including the measurement and criteria for the ORR and the OER is also included. Finally, recently reported nanostructure manganese oxide catalysts are also discussed. Full article
(This article belongs to the Special Issue Energy Efficiency for IoT Systems)
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