This paper proposes a new mass estimation for a vehicle system, utilizing the characteristics of engine torque local convex minimum, where the mass can be estimated based on the driving forces and the longitudinal accelerations only. Fundamentally, this approach generally requires no other information about an aerodynamic effect, a road grade, or a rolling friction, which is usually demanded by the existing well-known longitudinal dynamics and adaptive filter-based estimation methods. The effectiveness of the proposed approach was evaluated and validated by both TruckSim/Simulink co-simulation and actual field test data. It is found that the proposed estimation technique is more favorable for a situation where the vehicle is exposed to low-speed regions. In addition to this new mass estimation strategy, other new and current existing methods were explored and are reviewed here. Moreover, this study suggested a guideline for a hybrid-type mass estimation strategy to predict a mass by co... [more]

Condition monitoring of gear-based mechanical systems in non-stationary operation conditions is in general very challenging. This issue is particularly important for wind energy technology because most of the modern wind turbines are geared and gearbox damages account for at least the 20% of their unavailability time. In this work, a new method for the diagnosis of drive-train bearings damages is proposed: the general idea is that vibrations are measured at the tower instead of at the gearbox. This implies that measurements can be performed without impacting the wind turbine operation. The test case considered in this work is a wind farm owned by the Renvico company, featuring six wind turbines with 2 MW of rated power each. A measurement campaign has been conducted in winter 2019 and vibration measurements have been acquired at five wind turbines in the farm. The rationale for this choice is that, when the measurements have been acquired, three wind turbines were healthy, one wind tur... [more]

LoRa (Long Range) is a long-range communications capacity with chirp spread spectrum modulation. It has been developed for Internet of Things (IoT) applications for long-distance and low power consumption. Some authors proposed LoRa protocols such as LoRaWAN, LoRaBlink, DQ-LoRa and the multi-hop LoRa network with linear topology; however, these protocols have disadvantages. In this paper, we propose a minimized latency multi-hop LoRa network protocol that is collision-free with low latency to improve on the disadvantages. First, in the proposed protocol, tree topology is constructed by exchanging packets between LoRa nodes and the sink node. During this period, a timeslot and channel are assigned to each tree link, over which LoRa nodes communicate with their parent node and which is collision-free with its neighbor nodes. After the tree construction period, LoRa nodes start data transmission using the timeslot and channel that they have already been assigned to in the tree constructio... [more]

Advanced smart grid technologies enable energy prosumers to trade surplus energy from their distributed renewable energy sources with other peer prosumers through peer-to-peer (P2P) energy trading. In many previous works, P2P energy trading was facilitated by blockchain technology through blockchain’s distributive nature and capacity to run smart contracts. However, the feature that all the data and transactions on a blockchain are visible to all blockchain nodes may significantly threaten the privacy of the parties participating in P2P energy trading. There are many previous works that have attempted to mitigate this problem. However, all these works focused on the anonymity of participants but did not protect the data and transactions. To address this issue, we propose a P2P energy trading system on a blockchain where all bids are encrypted and peer matching is performed on the encrypted bids by a functional encryption-based smart contract. The system guarantees that the information... [more]

Although mud pumps are vital components of a drilling rig, their failures are frequent. The identification of technical condition of these high-pressure piston pumps is difficult. There are no reliable criteria for the assessment of mud pump condition. In this paper, faults of the pump valve module are identified by means of acoustic emission (AE) signals. The characteristics of these signals are extracted by wavelet packet signal processing. This method has been verified by experiments conducted on a NOV (National Oilwell Varco) -made triplex 14-P-220 mud pump (mounted in the drillship). The results show that the wavelet packet signal processing method can effectively extract the frequency band energy eigenvalues of the signals. Besides, some operational problems associated with high pressure piston mud pumps are presented. A non-invasive method for diagnosing the technical condition of such pumps is being developed at the Maritime University of Szczecin.

In this paper, a Radio Frequency (RF) energy harvester (EH) system for Internet of Things (IoT)-related applications is presented. The proposed EH architecture operates at 5.2 GHz band and utilizes multiple rectenna. This approach enhances the efficiency of the whole system over a wide dynamic RF input range. In the presented circuit, configuration of the rectenna is controlled by Field-Programmable Gate Array (FPGA) with respect to the input power level of the received RF input signal. In addition, an automatic adaptive matching based on the configuration of the rectenna, level of the received signal, and load current adjusts the matching network. The rectenna is realized through the Radio Frequency-Direct Current (RF-DC) converter composed of two Schottky diodes and generates the output DC voltage. Finally, a buck-boost converter provides the flattened and fixed voltage for the IoT and wearable devices. The 5.2 GHz band reconfigurable system demonstrates 67% high efficiency and 6.1 V... [more]

In order to ensure the information security, most of the important information including the data of advanced metering infrastructure (AMI) in the energy internet is currently transmitted and exchanged through the intranet or the carrier communication. The former increases the cost of network construction, and the latter is susceptible to interference and attacks in the process of information dissemination. The blockchain is an emerging decentralized architecture and distributed computing paradigm. Under the premise that these nodes do not need mutual trust, the blockchain can implement trusted peer-to-peer communication for protecting the important information by adopting distributed consensus mechanisms, encryption algorithms, point-to-point transmission and smart contracts. In response to the above issues, this paper firstly analyzes the information security problems existing in the energy internet from the four perspectives of system control layer, device access, market transaction... [more]

The serious problem of climate change has led the energy sector to modify its generation resources from fuel-based power plants to environmentally friendly renewable resources. However, these green resources are highly intermittent due to weather dependency and they produce increased risks of stability issues in power systems. The deployment of different flexible resources can help the system to become more resilient and secure against uncertainties caused by renewables. Flexible resources can be located at different levels in power systems like, for example, at the transmission-level (TSO), distribution-level (DSO) and customer-level. Each of these levels may have different structures of flexibility trading as well. This paper conducts a comprehensive review from the recent research related to flexible resources at various system levels in smart grids and assesses the trading structures of these resources. Finally, it analyzes the application of a newly emerged ICT technology, blockch... [more]

This study presents a simulation platform for a hybrid electric motorcycle with an engine, a driving motor, and an integrated starter generator (ISG) as three power sources. This platform also consists of the driving cycle, driver, lithium-ion battery, continuously variable transmission (CVT), motorcycle dynamics, and energy management system models. Two Arduino DUE microcontrollers integrated with the required circuit to process analog-to-digital signal conversion for input and output are utilized to carry out a hardware-in-the-loop (HIL) simulation. A driving cycle called worldwide motorcycle test cycle (WMTC) is used for evaluating the performance characteristics and response relationship among subsystems. Control strategies called rule-based control (RBC) and equivalent consumption minimization strategy (ECMS) are simulated and compared with the purely engine-driven operation. The results show that the improvement percentages for equivalent fuel consumption and energy consumption f... [more]

Smart production as one of the key issues for the world to advance toward Industry 4.0 has been a research focus in recent years. In a smart factory, hundreds or even thousands of sensors and smart devices are often deployed to enhance product quality. Generally, sensor data provides abundant information for artificial intelligence (AI) engines to make decisions for these smart devices to collect more data or activate some required activities. However, this also consumes a lot of energy to transmit the sensor data via networks and store them in data centers. Data compression is a common approach to reduce the sensor data size so as to lower transmission energies. Literature indicates that many Bounded-Error Piecewise Linear Approximation (BEPLA) methods have been proposed to achieve this. Given an error bound, they make efforts on how to approximate to the original sensor data with fewer line segments. In this paper, we furthermore consider resolution reduction, which sets a new restri... [more]

Rising electricity prices and the greater penetration of electricity consumption in end-uses have prompted efforts to set up data-driven methodologies to optimise energy consumption and foster user engagement in demand-side management strategies. The performance of energy-management systems is greatly affected by the consumer behaviors and the adopted energy-management methodology. Consequently, it is necessary to develop appliance-level, detailed energy-consumption information models to inform citizens to improve behaviors toward energy use. The goal of the Home Energy Management System (HEMS) is to foster an ecosystem that is energy-optimized and can manage Internet of things (IoT) equipment over its network. HEMS allows consumers to reduce energy costs by adapting their consumption to variable pricing over the day. With the use of descriptive data-mining techniques, we have developed a numerical model that gives consumers access to information on their domestic appliances with regar... [more]

Smart grid integrates computer, communication, and sensing technologies into existing power grid networks to achieve significant informatization-related advantages. It will provide communication between neighbors, localized management, bidirectional power transfer, and effective demand response. Smart grids (SG) replace conventional grids by integrating various operational measures, including smart automation appliances, smart meters, and renewable energy sources. Regarding energy management and resolving energy issues, SG is one of the most cutting-edge and potentially game-changing innovations. Even still, its complexity suggests that decentralization may provide significant gains. Because of its increasing digitization and interconnectedness, it is also vulnerable to cyber threats. Blockchain, in this sense, is a potential SG paradigm solution that provides several great benefits. Even though blockchains have been widely discussed to decentralize and strengthen smart grid cybersecur... [more]

The development of smart grids has paved the way for sustainable energy infrastructure to transition towards decentralized energy trading. As intelligent agents, energy sources engage in energy trading based on their energy surplus or deficit. Buyers and sellers (participants) should achieve maximum payoffs in which buyers cut costs and sellers improve their utilities, and the security of sensitive information of smart agents must be guaranteed. This paper provides a blockchain-based energy trading network where intelligent agents can exchange energy in a secure manner, without the intervention of third parties. We model energy trading as a Stackelberg game, ensuring that the platform maximizes social welfare while participants increase their payoffs. Using the inherited characteristics of blockchain technology, a novel decentralized swarm intelligence technique is applied to solve the game while ensuring the privacy of the smart agents’ sensitive information. The numerical analysis de... [more]

The implementation of the smart grid (SG) and cyber-physical systems (CPS) greatly enhances the safety, reliability, and efficiency of energy production and distribution. Smart grids rely on smart meters (SMs) in converting the power grids (PGs) in a smart and reliable way. However, the proper operation of these systems needs to protect them against attack attempts and unauthorized entities. In this regard, key-management and authentication mechanisms can play a significant role. In this paper, we shed light on the importance of these mechanisms, clarifying the main efforts presented in the context of the literature. First, we address the main intelligent attacks affecting the SGs. Secondly, the main terms of cryptography are addressed. Thirdly, we summarize the common proposed key-management techniques with a suitable critique showing their pros and cons. Fourth, we introduce the effective paradigms of authentication in the state of the art. Fifth, the common two tools for verifying t... [more]

This Special Issue of Energies was devoted to the topic of “Manufacturing Energy Efficiency and Industry 4.0”. To a great extent, this issue follows the successful previous Special Issue on “Energy Efficiency of Manufacturing Processes and Systems”, which attracted some significant attention from scholars, practitioners, and policy-makers from all over the world. In total, six papers were published. The main topics included energy efficiency improvement in both the manufacturing process and system levels, as well as how this can be facilitated through the use of Industry 4.0.

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 enabl... [more]

Integrating data analytics, optimisation and dynamic control to support energy services has seen significant interest in recent years. Larger appliances used in an industry context are now provided with Internet of Things (IoT)-based interfaces that can be remotely monitored, with some also provided with actuation interfaces. The combined use of IoT and edge computing enables connectivity between energy systems and infrastructure, providing the means to implement both energy efficiency/optimisation and cost reduction strategies. We investigate the economic implications of harnessing IoT and edge/cloud technologies to support energy management for HVAC (Heating, Ventilation and Air Conditioning) systems in buildings. In particular, we evaluate the cost savings for building operations through energy optimisation. We use a real use case for energy optimisation as identified in the EU “Sporte2” project (focusing on the energy optimisation of sports facilities) and explore several scenarios... [more]

The Internet of Things (IoT) has found application in many components of implantable medical devices, wearable smart devices, monitoring systems, etc. The IoT devices are conventionally battery powered, even though, in several low power applications, they can also be powered using energy harvesting technology. Independently of the power sources (if batteries or environment), efficient and robust power converters must be designed to provide the small and distributed energy required by such IoT devices. This review paper will first provide an overview about the power consumption in IoT devices; second, it will discuss the most recent research and advance in the field of fully-integrated or embedded DC/DC converters, starting from high-performance integrated charge pumps or embedded inductive boost converters for specific harvesting sources (temperature, solar, and so on), to novel DC/DC converters for multiple energy sources.

Internet of Things (IoT) performs a vital role in providing connectivity between computing devices, processes, and things. It significantly increases the communication facilities and giving up-to-date information to distributed networks. On the other hand, the techniques of artificial intelligence offer numerous and valuable services in emerging fields. An IoT-based healthcare solution facilitates patients, hospitals, and professionals to observe real-time and critical data. In the literature, most of the solution suffers from data intermission, high ethical standards, and trustworthiness communication. Moreover, network interruption with recurrent expose of sensitive and personal health data decreases the reliance on network systems. Therefore, this paper intends to propose an IoT solution for AI-enabled privacy-preserving with big data transferring using blockchain. Firstly, the proposed algorithm uses a graph-modeling to develop a scalable and reliable system for gathering and trans... [more]

Signal processing of the brushed DC motor current was developed in this paper to obtain information about a rotor speed from a measured motor current. The brushed DC motor current contains a signal with a frequency proportional to the rotor speed. This signal is the outcome of a commutation process occurring in the brushed DC motor, and it is called a ripple component. Since the number of ripples in the measured motor current per one rotation is constant, the rotor speed can be estimated. A discrete bandpass filter with a floating bandwidth was developed as the main part of signal processing. This new interpretation of the bandpass filter was used to extract a frequency of the ripple component from the measured motor current. This frequency was used to acquire information about the estimated rotor speed. The estimated speed was set as a feedback value to a cascade control structure to provide sensorless speed control. The advantages and limitations of this approach are presented in thi... [more]

Multi-access edge computing has become a strategic concept of the Internet of Things. The edge computing market has reached USD several billion and is growing intensively. In the edge-computing paradigm, most of the data is processed close to, or at the edge of, the network. This greatly reduces the computation and communication load of the network core. Moreover, edge computing provides better support for user privacy. On the other hand, an increase in data processing locations will proportionately increase the attack surface. An edge node can be put out of service easily by being flooded with spoofed packets owing to limited capacities and resources. Furthermore, wireless edge nodes are quite vulnerable to energy exhaustion attacks. In this situation, traditional network security mechanisms cannot be used effectively. Therefore, a tradeoff between security and efficiency is needed. This study considered the requirements under which the use of an intrusion detection system (IDS) is ju... [more]

Presently, Internet of Things (IoT) protocols are at the heart of Machine-to-Machine (M2M) communication. Irrespective of the radio technologies used for deploying an IoT/M2M network, all independent data generated by IoT devices (sensors and actuators) rely heavily on the special messaging protocols used for M2M communication in IoT applications. As the demand for IoT services is growing, the need for reduced power consumption of IoT devices and services is also growing to ensure a sustainable environment for future generations. The Message-Queuing Telemetry Transport or in short MQTT is a widely used IoT protocol. It is a low-resource-consuming messaging solution based on the publish−subscribe type communication model. This paper aims to assess the performance of several MQTT broker implementations (also known as MQTT servers) using stress testing, and to analyze their relationship with system design. The evaluation of the brokers is performed by a realistic test scenario, and the an... [more]

A Long-Range Wide Area Network (LoRaWAN) is one of the most efficient technologies and is widely adopted for the Internet of Things (IoT) applications. The IoT consists of massive End Devices (EDs) deployed over large geographical areas, forming a large environment. LoRaWAN uses an Adaptive Data Rate (ADR), targeting static EDs. However, the ADR is affected when the channel conditions between ED and Gateway (GW) are unstable due to shadowing, fading, and mobility. Such a condition causes massive packet loss, which increases the convergence time of the ADR. Therefore, we address the convergence time issue and propose a novel ADR at the network side to lower packet losses. The proposed ADR is evaluated through extensive simulation. The results show an enhanced convergence time compared to the state-of-the-art ADR method by reducing the packet losses and retransmission under dynamic mobile LoRaWAN network.

Internet of Things (IoT) is a developing technology for supporting heterogeneous physical objects into smart things and improving the individuals living using wireless communication systems. Recently, many smart healthcare systems are based on the Internet of Medical Things (IoMT) to collect and analyze the data for infectious diseases, i.e., body fever, flu, COVID-19, shortness of breath, etc. with the least operation cost. However, the most important research challenges in such applications are storing the medical data on a secured cloud and make the disease diagnosis system more energy efficient. Additionally, the rapid explosion of IoMT technology has involved many cyber-criminals and continuous attempts to compromise medical devices with information loss and generating bogus certificates. Thus, the increase in modern technologies for healthcare applications based on IoMT, securing health data, and offering trusted communication against intruders is gaining much research attention.... [more]

Based on outlier detection algorithms, a feasible quantification method for supraharmonic emission signals is presented. It is designed to tackle the requirements of high-resolution and low data volume simultaneously in the frequency domain. The proposed method was developed from the skewed distribution data model and the self-tuning parameters of density-based spatial clustering of applications with noise (DBSCAN) algorithm. Specifically, the data distribution of the supraharmonic band was analyzed first by the Jarque−Bera test. The threshold was determined based on the distribution model to filter out noise. Subsequently, the DBSCAN clustering algorithm parameters were adjusted automatically, according to the k-dist curve slope variation and the dichotomy parameter seeking algorithm, followed by the clustering. The supraharmonic emission points were analyzed as outliers. Finally, simulated and experimental data were applied to verify the effectiveness of the proposed method. On the b... [more]