Networked control system with MANET communication and AODV routing

The industries are presently exploring the use of wired and wireless systems for control, automation, and monitoring. The primary benefit of wireless technology is that it reduces the installation cost, in both money and labor terms, as companies already have a significant investment in wiring. The research article presents the work on the analysis of Mobile Ad Hoc Network (MANET) in a wireless real-time communication medium for a Networked Control System (NCS), and determining whether the simulated behavior is significant for a plant or not. The behavior of the MANET is analyzed for Ad-hoc on-demand distance vector routing (AODV) that maintenances communication among 150 nodes for NCS. The simulation is carried out in Network Simulator (NS2) software with different nodes cluster to estimate the network throughput, end-to-end delay, packet delivery ratio (PDR), and control overhead. The benefit of MANET is that it has a fixed topology, which permits flexibility since mobile devices may be used to construct ad-hoc networks anywhere, scalability because more nodes can be added to the network, and minimal operating expenses in that no original infrastructure needs to be developed. AODV routing is a flat routing system that does not require central routing nodes. As the network grows in size, the network can be scaled to meet the network design and configuration requirements. AODV is flexible to support different configurations and topological nodes in dynamic networks because of its versatility. The advantage of such network simulation and routing behavior provides the future direction for the researchers who are working towards the embedded hardware solutions for NCS, as the hardware complexity depends on the delay, throughput, and PDR

Efficient and Secure Strategy for Energy Systems of Interconnected Farmers′ Associations to Meet Variable Energy Demand

Since ancient times, agriculture has been one of the most important resources of national development. At a national level, clean energy is a strategic objective of Romania, in accordance with the EC directive 2016/30.11.2016 (“Clean Energy for All”). At a European level, the European Commission published in January 2019 the “Towards a Sustainable Europe by 2030” strategy, highlighting the strategic importance of the Internet of Things (IoT) and blockchain technologies. In this context, the synergy between the energy management of a hybrid energy system and blockchain technology, applied to farmers’ associations, represents a priority research direction in the field of information and communication technology, blockchain, and security. This paper presents the integration of the management of the energy produced by photovoltaic panels owned by farmers’ association, to support the variable energy demand (necessary for water pumps, charging stations of the electric agricultural machines, the animal farms, and the auxiliary equipment) based on the IoT, DLT, blockchain technologies and smart contracts applied to farmers associations registered as users of the SmartFarm platform

Design and Concept of an Energy System Based on Renewable Sources for Greenhouse Sustainable Agriculture

Bio-organic greenhouses that are based on alternative resources for producing heat and electricity stand out as an efficient option for the sustainable development of agriculture, thus ensuring good growth and development of plants in all seasons, especially during the cold season. Greenhouses can be used with maximum efficiency in various agricultural lands, providing ideal conditions of temperature and humidity for short-term plant growing, thereby increasing the local production of fruit and vegetables. This paper presents the development of a durable greenhouse concept that is based on complex energy system integrating fuel cells and solar panels. Approaching this innovative concept encountered a major problem in terms of local implementation of this type of greenhouses because of the difficulty in providing electrical and thermal energy from conventional sources to ensure an optimal climate for plant growing. The project result consists in the design and implementation of a sustainable greenhouse energy system that is based on fuel cells and solar panels

Optimal Synergy between Photovoltaic Panels and Hydrogen Fuel Cells for Green Power Supply of a Green Building—A Case Study

Alternative energy resources have a significant function in the performance and decarbonization of power engendering schemes in the building application domain. Additionally, “green buildings” play a special role in reducing energy consumption and minimizing CO2 emissions in the building sector. This research article analyzes the performance of alternative primary energy sources (sun and hydrogen) integrated into a hybrid photovoltaic panel/fuel cell system, and their optimal synergy to provide green energy for a green building. The study addresses the future hydrogen-based economy, which involves the supply of hydrogen as the fuel needed to provide fuel cell energy through a power distribution infrastructure. The objective of this research is to use fuel cells in this field and to investigate their use as a green building energy supply through a hybrid electricity generation system, which also uses photovoltaic panels to convert solar energy. The fuel cell hydrogen is supplied through a distribution network in which hydrogen production is outsourced and independent of the power generation system. The case study creates virtual operating conditions for this type of hybrid energy system and simulates its operation over a one-year period. The goal is to demonstrate the role and utility of fuel cells in virtual conditions by analyzing energy and economic performance indicators, as well as carbon dioxide emissions. The case study analyzes the optimal synergy between photovoltaic panels and fuel cells for the power supply of a green building. In the simulation, an optimally configured hybrid system supplies 100% of the energy to the green building while generating carbon dioxide emissions equal to 11.72% of the average value calculated for a conventional energy system providing similar energy to a standard residential building. Photovoltaic panels account for 32% of the required annual electricity production, and the fuel cells generate 68% of the total annual energy output of the system

Machine Learning Human Behavior Detection Mechanism Based on Python Architecture

Human behavior is stimulated by the outside world, and the emotional response caused by it is a subjective response expressed by the body. Humans generally behave in common ways, such as lying, sitting, standing, walking, and running. In real life of human beings, there are more and more dangerous behaviors in human beings due to negative emotions in family and work. With the transformation of the information age, human beings can use Industry 4.0 smart devices to realize intelligent behavior monitoring, remote operation, and other means to effectively understand and identify human behavior characteristics. According to the literature survey, researchers at this stage analyze the characteristics of human behavior and cannot achieve the classification learning algorithm of single characteristics and composite characteristics in the process of identifying and judging human behavior. For example, the characteristic analysis of changes in the sitting and sitting process cannot be for classification and identification, and the overall detection rate also needs to be improved. In order to solve this situation, this paper develops an improved machine learning method to identify single and compound features. In this paper, the HATP algorithm is first used for sample collection and learning, which is divided into 12 categories by single and composite features; secondly, the CNN convolutional neural network algorithm dimension, recurrent neural network RNN algorithm, long- and short-term extreme value network LSTM algorithm, and gate control is used. The ring unit GRU algorithm uses the existing algorithm to design the model graph and the existing algorithm for the whole process; thirdly, the machine learning algorithm and the main control algorithm using the proposed fusion feature are used for HATP and human beings under the action of wearable sensors. The output features of each stage of behavior are fused; finally, by using SPSS data analysis and re-optimization of the fusion feature algorithm, the detection mechanism achieves an overall target sample recognition rate of about 83.6%. Finally, the research on the algorithm mechanism of machine learning for human behavior feature classification under the new algorithm is realized

A Review of the Public Transport Services Based on the Blockchain Technology

This paper presents a comprehensive review of the technical aspects and challenges in existing public transport services. This review highlights the challenges and solutions for the main subsystems of public transport services, being focused on the influence of public transportation in an urban area with high demographics to identify solutions based on blockchain technology for future development of the current management platforms. More than 2000 research papers, published since 2018 and until now, have been analyzed in Web of Science, Scopus, and ScienceDirect. The keywords used for the analysis of blockchain integration in public transport are related to technology, services, management, the use of electric vehicles, and the impact of public transport on the environment. In this research, we analyzed why there is a need for integrating the blockchain technologies in public transport

Hydrogen Fuel Cell Technology for the Sustainable Future of Stationary Applications

The climate changes that are becoming visible today are a challenge for the global research community. The stationary applications sector is one of the most important energy consumers. Harnessing the potential of renewable energy worldwide is currently being considered to find alternatives for obtaining energy by using technologies that offer maximum efficiency and minimum pollution. In this context, new energy generation technologies are needed to both generate low carbon emissions, as well as identifying, planning and implementing the directions for harnessing the potential of renewable energy sources. Hydrogen fuel cell technology represents one of the alternative solutions for future clean energy systems. This article reviews the specific characteristics of hydrogen energy, which recommends it as a clean energy to power stationary applications. The aim of review was to provide an overview of the sustainability elements and the potential of using hydrogen as an alternative energy source for stationary applications, and for identifying the possibilities of increasing the share of hydrogen energy in stationary applications, respectively. As a study method was applied a SWOT analysis, following which a series of strategies that could be adopted in order to increase the degree of use of hydrogen energy as an alternative to the classical energy for stationary applications were recommended. The SWOT analysis conducted in the present study highlights that the implementation of the hydrogen economy depends decisively on the following main factors: legislative framework, energy decision makers, information and interest from the end beneficiaries, potential investors, and existence of specialists in this field

Delegated Proof of Accessibility (DPoAC): A Novel Consensus Protocol for Blockchain Systems

As the backbone of every blockchain application, the consensus protocol is impacted by numerous risks, namely resource requirements and energy consumption, which limit the usage of blockchain. Applications such as IoT/IIoT cannot use these high-cost consensus methods due to limited resources. Therefore, we introduce Delegated Proof of Accessibility (DPoAC), a new consensus technique that employs secret sharing, PoS with random selection, and an interplanetary file system (IPFS).DPoAC is decomposed into two stages. During the initial stage, a secret is generated by a randomly chosen super node and divided into n shares. These shares are encrypted and stored in different n nodes on the IPFS network. The nodes will compete to access these shareholders to reconstruct the secret. The winning node will be awarded block generation rights. PoS with random selection is used in the second stage to compute the appropriate hash value and construct a block with valid transactions. In this novel approach, a node with few computational resources and small stakes can still obtain block generation rights by providing access to secret shares and reconstructing the secret, making the system reasonably fair. We qualitatively analyze and compare our scheme based on performance parameters against existing mainstream consensus protocols in the context of IoT/IIoT networks

Image Geo-Site Estimation Using Convolutional Auto-Encoder and Multi-Label Support Vector Machine

The estimation of an image geo-site solely based on its contents is a promising task. Compelling image labelling relies heavily on contextual information, which is not as simple as recognizing a single object in an image. An Auto-Encode-based support vector machine approach is proposed in this work to estimate the image geo-site to address the issue of misclassifying the estimations. The proposed method for geo-site estimation is conducted using a dataset consisting of 125 classes of various images captured within 125 countries. The proposed work uses a convolutional Auto-Encode for training and dimensionality reduction. After that, the acquired preprocessed input dataset is further processed by a multi-label support vector machine. The performance assessment of the proposed approach has been accomplished using accuracy, sensitivity, specificity, and F1-score as evaluation parameters. Eventually, the proposed approach for image geo-site estimation presented in this article outperforms Auto-Encode-based K-Nearest Neighbor and Auto-Encode-Random Forest methods

Delegated Proof of Accessibility (DPoAC): A Novel Consensus Protocol for Blockchain Systems

As the backbone of every blockchain application, the consensus protocol is impacted by numerous risks, namely resource requirements and energy consumption, which limit the usage of blockchain. Applications such as IoT/IIoT cannot use these high-cost consensus methods due to limited resources. Therefore, we introduce Delegated Proof of Accessibility (DPoAC), a new consensus technique that employs secret sharing, PoS with random selection, and an interplanetary file system (IPFS).DPoAC is decomposed into two stages. During the initial stage, a secret is generated by a randomly chosen super node and divided into n shares. These shares are encrypted and stored in different n nodes on the IPFS network. The nodes will compete to access these shareholders to reconstruct the secret. The winning node will be awarded block generation rights. PoS with random selection is used in the second stage to compute the appropriate hash value and construct a block with valid transactions. In this novel approach, a node with few computational resources and small stakes can still obtain block generation rights by providing access to secret shares and reconstructing the secret, making the system reasonably fair. We qualitatively analyze and compare our scheme based on performance parameters against existing mainstream consensus protocols in the context of IoT/IIoT networks