The possibility of the application of an unmanned aerial vehicle (UAV) in search and rescue activities in a deep underground mine has been investigated. In the presented case study, a UAV is searching for a lost or injured human who is able to call for help but is not able to move or use any communication device. A UAV capturing acoustic data while flying through underground corridors is used. The acoustic signal is very noisy since during the flight the UAV contributes high-energetic emission. The main goal of the paper is to present an automatic signal processing procedure for detection of a specific sound (supposed to contain voice activity) in presence of heavy, time-varying noise from UAV. The proposed acoustic signal processing technique is based on time-frequency representation and Euclidean distance measurement between reference spectrum (UAV noise only) and captured data. As both the UAV and “injured” person were equipped with synchronized microphones during the experiment, va... [more]

Since awareness of the influence of home energy management services (HEMS) with Internet of things (IoT) has grown, the study on the acceptance of IoT services has been expanded. Previous studies, however, have not paid attention to the acceptance itself, focusing only on factors affecting the acceptance. This study attempts to draw meaningful implications by exploring the relationships between the acceptance and the factors affecting it with distinctions between passive acceptance and active acceptance. This study analyzed the ordinal logistic regression models based on a survey of 909 adults 19 years of age and older in Korea on HEMS with IoT. In addition, we attempt the ordinal forest to increase the reliability of the research results. As a result, this study showed that consumers’ perception of usefulness was noticeably important to enhance active acceptance and that those who had high sensitivity to new technology acceptance showed high active acceptance, and older women had high... [more]

In an electrical safe microenvironment, all kinds of electrical appliances can be operated safely to ensure the safety of life and property. The significance of safety hazard factors detection is to detect safety hazards in advance, to remind the administrators to exclude risk, to reduce the unnecessary loss, and to ensure that the electrical operation is healthy and orderly before the occurrence of accidents. In this paper, batteries are selected as the primary research subject of safety detection because batteries are used more and more in the Internet of Things (IOT), and they often cause fire in the process of discharging and charging. The existing algorithms need to be embedded into the specialized sensor for each important electrical appliance. However, they are limited by the actual deployment, so it is extremely difficult to spread widely. According to the opinions above, an improved load disaggregation algorithm based on dictionary learning and sparse coding with optimal dicti... [more]

Sound localization is a field of signal processing that deals with identifying the origin of a detected sound signal. This involves determining the direction and distance of the source of the sound. Some useful applications of this phenomenon exists in speech enhancement, communication, radars and in the medical field as well. The experimental arrangement requires the use of microphone arrays which record the sound signal. Some methods involve using ad-hoc arrays of microphones because of their demonstrated advantages over other arrays. In this research project, the existing sound localization methods have been explored to analyze the advantages and disadvantages of each method. A novel sound localization routine has been formulated which uses both the direction of arrival (DOA) of the sound signal along with the location estimation in three-dimensional space to precisely locate a sound source. The experimental arrangement consists of four microphones and a single sound source. Previou... [more]

This paper presents issues related to the adaptive control of the drive system with an elastic clutch connecting the main motor and the load machine. Firstly, the problems and the main algorithms often implemented for the mentioned object are analyzed. Then, the control concept based on the RNN (recurrent neural network) for the drive system with the flexible coupling is thoroughly described. For this purpose, an adaptive model inspired by the Elman model is selected, which is related to internal feedback in the neural network. The indicated feature improves the processing of dynamic signals. During the design process, for the selection of constant coefficients of the controller, the PSO (particle swarm optimizer) is applied. Moreover, in order to obtain better dynamic properties and improve work in real conditions, one model based on the ADALINE (adaptive linear neuron) is introduced into the structure. Details of the algorithm used for the weights’ adaptation are presented (including... [more]

Multiple applications of sensor devices in the form of a Wireless Sensor Network (WSN), such as those represented by the Internet of Things and monitoring dangerous geographical spaces, have attracted the attention by several scientific communities. Despite their interesting properties, sensors present an adverse characteristic: they manage very limited energy. Under such conditions, saving energy represents one of the most important concepts in designing effective protocols for WSNs. The objective of a protocol is to increase the network lifetime through the reduction of energy consumed by each sensor. In this paper, a robust clustering routing protocol for WSNs is introduced. The scheme uses the Locust Search (LS-II) method to determine the number of cluster heads and to identify the optimal cluster heads. Once the cluster heads are recognized, the other sensor elements are assigned to their nearest corresponding cluster head. Numerical simulations exhibit competitive results and dem... [more]

In order to investigate the grid integration of wind turbines (WT) of various scales and designs, a wind turbine emulator (WTE) is being built in Flensburg within the state-funded project GrinSH. The special feature of this WTE is the use of a large gas engine instead of an electric motor to emulate the behavior of a WT. In order to develop the controls of this innovative WTE and to design the upcoming test runs under safe conditions, a software in the loop model (SILM) was applied. This SILM contained a mathematical model of the wind turbine, mathematical models of the gas engine with an integrated controller, and a model of the generator and frequency converter unit, as well as a preventive modulator of the reference signal (PMRS). The PMRS module converts the reference signal of the emulated WT in such a way that the dynamics of the engine components can be calculated and balanced in advance to enable the required behavior of the entire SILM despite the dynamics of the gas engine. I... [more]

Competition on the local and global market forces enterprises to implement modern solutions and adapt to technological changes. Applying modern solutions allows an increase in the quality of the product and reduces production costs. The acoustic sensor, as a relatively cheap solution, allows signals to be obtained which, after appropriate processing, can be used to develop an automatic control of the longwall shearer, together with the recognition of the type of shale. This paper presents an introductory research, the goal of which has been to check whether acoustic signals carry useful information on what kind of material−shale or coal−is being cut by the cutting head of a longwall shearer. For this purpose, the fast Fourier transform and short-time Fourier transform functions implemented in MatLab were used. The results of the analysis are presented in the form of three-dimensional graphs and spectrograms. To sum up, the research carried out so far justifies the need for continuation... [more]

The 5G communication network will underpin a vast number of new and emerging services, paving the way for unprecedented performance and capabilities in mobile networks. In this setting, the Internet of Things (IoT) will proliferate, and IoT devices will be included in many 5G application contexts, including the Smart Grid. Even though 5G technology has been designed by taking security into account, design provisions may be undermined by software-rooted vulnerabilities in IoT devices that allow threat actors to compromise the devices, demote confidentiality, integrity and availability, and even pose risks for the operation of the power grid critical infrastructures. In this paper, we assess the current state of the vulnerabilities in IoT software utilized in smart grid applications from a source code point of view. To that end, we identified and analyzed open-source software that is used in the power grid and the IoT domain that varies in characteristics and functionality, ranging from... [more]

The needs to reduce the imperfection of theoretical and methodological approaches to value and regulate the processes of applying the methods of transactional energy are substantiated. The concept of combining organizational, economic and mathematical models to improve technical, technological and information methods for the effective integration of renewable and traditional energy facilities has been formulated. This determined the goal of forming a digital platform for machine-to-machine automatic processing of transactions. The creation of the platform contributes to solving a number of research tasks including development of schemes for the use of photo and thermoelements for energy generation in distributed energy and control of electrical and thermodynamic parameters of equipment in sensors of its diagnostics and use in electric drives of actuators of the Industrial Internet of Things. The use of big datа and datа science tools is aimed at achieving a number of practical results.... [more]

In recent years, the application of traceability systems in the food and drug industry has developed rapidly, but it is rarely used for wind turbines. From the aspects of low information transparency and information islands in the supply chain process for wind turbines, a reliable traceability system is essential. However, the existing traceability systems are not suitable to be directly applied to wind turbines. Consequently, according to the characteristics of the wind power industry, a semi-centralized traceability architecture based on Internet of Things technology was proposed. Furthermore, a traceability platform was constructed by analyzing the information collected in each stage related to various user needs of wind turbines, and various applications, including manufacturing management and spare parts management, were developed. Compared with the existing systems, the proposed platform was wind-turbine-oriented, effectively improved traceability efficiency and enterprises’ info... [more]

In the 21st century, researchers have been showing keen interest in the areas of wireless networking and internet of things (IoT) devices. Conventionally, batteries have been used to power these networks; however, due to the limited lifespan of batteries and with the recent advancements in piezoelectric technology, there is a dramatic increase in renewable energy harvesting devices. In this research, an eco-friendly wind energy harvesting device based on the piezoelectric technique is analytically modeled, numerically simulated, and statistically optimized for low power applications. MATLAB toolbox SIMSCAPE is utilized to simulate the proposed wind energy harvester in which a windmill is used to produce rotational motion due to the kinetic energy of wind. The windmill’s rotational shaft is further connected to the rotary to linear converter (RLC) and vibration enhancement mechanism (VEM) for the generation of translational mechanical vibration. Consequently, due to these alternative li... [more]

This article presents the problems of powering wireless sensor networks operating in the structures of the Internet of Things (IoT). This issue was discussed on the example of a universal end node in IoT technology containing RFID (Radio Frequency Identification) tags. The basic methods of signal transmission in these types of networks are discussed and their impact on the basic requirements such as range, transmission speed, low energy consumption, and the maximum number of devices that can simultaneously operate in the network. The issue of low power consumption of devices used in IoT solutions is one of the main research objects. The analysis of possible communication protocols has shown that there is a possibility of effective optimization in this area. The wide range of power sources available on the market, used in nodes of wireless sensor networks, was compared. The alternative possibilities of powering the network nodes from Energy Harvesting (EH) generators are presented.

The transition towards the massive penetration of Renewable Energy Resources (RESs) into the electricity system requires the implementation of the Smart Grid (SG) paradigm with innovative control systems and equipment. In this new context, Distributed Energy Resources (DERs), including renewable sources and responsive loads, should be redesigned to enable aggregators to provide ancillary services. In fact, by using the Internet of Things (IoT) systems, aggregators can explore energy usage patterns from residential users, also known as prosumers and predict their services. This is undoubtedly important especially for SGs facing the presence of several RESs, where understanding the optimal match between demand and production is desirable from several points of view. However, revealing energy patterns and information can be of concern for privacy if the entire system is not properly designed. In this article, by assuming that the security of low-level communication protocols is guaranteed... [more]

This paper presents an innovative approach to the extraction of an indicator for the monitoring of bearing degradation. This approach is based on the principles of the empirical mode decomposition (EMD) and the Hilbert transform (HT). The proposed approach extracts the temporal components of oscillating vibration signals called intrinsic mode functions (IMFs). These components are classified locally from the highest frequencies to the lowest frequencies. By selecting the appropriate components, it is possible to construct a bank of self-adaptive and automatic filters. Combined with the HT, the EMD allows an estimate of the instantaneous frequency of each IMF. A health indicator called the Hilbert marginal spectrum density is then extracted in order to detect and diagnose the degradation of bearings. This approach was validated on two test benches with variable speeds and loads. The obtained results demonstrated the effectiveness of this approach for the monitoring of ball and roller be... [more]

The Internet of Things (IoT) is a technology that allows every object or item to become part of the Internet and interact with each other. One of the technologies based on the IoT is Long Range (LoRa). Apart from the increasing number of IoT services, security aspects become a separate issue in the development of the IoT. One of the solutions is to utilize blockchain technology in the IoT topology to secure the data and transactions that occur in the IoT network. The blockchain can take minutes to compute a cryptographic chain. It also needs sufficient computing resources. This problem gave rise to the idea of establishing a lightweight blockchain platform with low latency that could run on devices with low computing resources as well as IoT devices. We offered a technology called Lightweight Multi-Fog (LMF) in our previous publication that is implemented using the Lightweight Scalable Blockchain (LSB) algorithm and the fog network on the IoT to solve the problem of integrating a block... [more]

The Energy Internet paradigm is the evolution of the Internet of Things concept in the power system. Microgrids (MGs), as the essential element in an Energy Internet, are expected to be controlled in a corporative and flexible manner. This paper proposes a novel decentralized robust control strategy for multi-agent systems (MASs) governed MGs in future Energy Internet. The proposed controller is based on a consensus algorithm applied with the connected distributed generators (DGs) in the MGs in the energy internet paradigm. The proposed controller’s objectives are the frequency/voltage regulation and proportional reactive/active power-sharing for the hybrid DGs connected MGs. A proposed two-level communication system is implemented to explain the data exchange between the MG system and the cloud server. The local communication level utilizes the transmission control protocol (TCP)/ internet protocol (IP) and the message queuing telemetry transport (MQTT) is used as the protocol for the... [more]

In this paper, we present a detailed analysis of walkaway vertical seismic profiling (VSP) data, which can be used to obtain Thomsen parameters using P-wave-only inversion. Data acquisition took place in difficult field conditions, which influenced the quality of the data. Therefore, this paper also shows a seismic data processing scheme that allows the estimation of correct polarization angles despite poor input data quality. Moreover, we showed that it is possible to obtain reliable and detailed values of Thomsen’s anisotropy parameters for data that are challenging due to extremely difficult field conditions during acquisition and the presence of an overburden of salt and anhydrite (Zechstein formation). This complex is known for its strong seismic signal-attenuating properties. We designed a special processing workflow with a signal-matching procedure that allows reliable estimation of polarization angles for low-quality data. Additionally, we showed that P-wave-only inversion for... [more]

Recent research advances in sensors, wireless communications, network protocols, microelectronics, cloud computing, and machine learning, among others, are driving the growth of the Internet of Things (IoT) [...]

Physical activity involves movements, which can be considered sources of kinetic energy, that are expected to be important during sports activities. Several transducers can transform this energy into electrical energy. Piezoelectric generators are widely used, and several applications highlight their relevance. However, the generated output power is location dependent, and the analysis of the placement of this kind of generator can be challenging. In order to assess the availability of kinetic energy sources, an acceleration data analysis method is presented. Temporal and harvester model-based studies, using data from 17 inertial measurement units (IMUs) located across the whole human body, were conducted. The results show that piezoelectric cantilever-beam harvesters can be very sensitive to impacts. Extremity segments, such as the feet or hands, can be considered as good energy sources. The most relevant features are proposed as criteria to easily evaluate the harvestable energy sour... [more]

In the present day, it is crucial for individuals and companies to reduce their carbon footprints in a society more self-conscious about climate change and other environmental issues. In this sense, public and private institutions are investing in photovoltaic (PV) systems to produce clean energy for self-consumption. Nevertheless, an essential part of this energy is wasted due to lower consumption during non-business periods. This work proposes a novel framework that uses solar-generated energy surplus to charge external electric vehicles (EVs), creating new business opportunities. Furthermore, this paper introduces a novel marketplace platform based on blockchain technology to allow energy trading between institutions and EV owners. Since the energy provided to charge the EV comes from distributed PV generation, the energy’s selling price can be more attractive than the one offered by the retailers—meaning economic gains for the institutions and savings for the users. A case study wa... [more]

Several factors affect existing electric power systems and negatively impact power quality (PQ): the high penetration of renewable and distributed sources that are based on power converters with or without energy storage, non-linear and unbalanced loads, and the deployment of electric vehicles. In addition, the power grid needs more improvement in the performances of real-time PQ monitoring, fault diagnosis, information technology, and advanced control and communication techniques. To overcome these challenges, it is imperative to re-evaluate power quality and requirements to build a smart, self-healing power grid. This will enable early detection of power system disturbances, maximize productivity, and minimize power system downtime. This paper provides an overview of the state-of-the-art signal processing- (SP) and pattern recognition-based power quality disturbances (PQDs) characterization techniques for monitoring purposes.

The nuclear industry is exploring applications of Artificial Intelligence (AI), including autonomous control and management of reactors and components. A condition assessment framework that utilizes AI and sensor data is an important part of such an autonomous control system. A nuclear power plant has various structures, systems, and components (SSCs) such as piping-equipment that carries coolant to the reactor. Piping systems can degrade over time because of flow-accelerated corrosion and erosion. Any cracks and leakages can cause loss of coolant accident (LOCA). The current industry standards for conducting maintenance of vital SSCs can be time and cost-intensive. AI can play a greater role in the condition assessment and can be extended to recognize concrete degradation (chloride-induced damage and alkali−silica reaction) before cracks develop. This paper reviews developments in condition assessment and AI applications of structural and mechanical systems. The applicability of exist... [more]

With the realization of the “dual carbon” goal, urban public transport with an increasing proportion of new energy vehicles will become the key subject to achieve the carbon emission reduction goal. Under the new background of deep coupling between transport networks and power grids, it is of great significance to study the carbon-trading mode of urban public transport participation in promoting the development of new energy vehicles and improving the operating efficiency and low-carbon level of the “energy-transport” system. In this paper, based on blockchain technology, a framework for urban public transportation networks to participate in carbon trading is established to solve the current problems of urban public transportation’s insufficient motivation to reduce emissions, lax operation strategy and lack of carbon-trading matching mechanisms. Finally, Hyperledger Fabric was selected as the simulation platform, and we simulated the model through the calculation example. The results... [more]

Constantly growing distributed energy generation based on renewable sources creates a number of new challenges for electrical power system operation. One of the challenges is islanding detection. Unintentional islanding, which can cause health and safety hazards for the personnel, is currently being experienced by a growing number of consumers/prosumers especially in the case of photovoltaic inverters. This work presents a new islanding detection method based on synchrophasor measurements. The proposed method works in either a passive or hybrid mode. In a passive mode, a single phasor measurement unit (PMU) in the island region is used. In a hybrid mode, one PMU in the island and another one outside the island are exploited. The proposed method was verified in conducted laboratory tests that confirmed the applicability of PMUs data for effective detection and monitoring of unintentional islanding.