Internet of Things based Messaging Protocols for Aquaculture Applications - A Bibliometric Analysis and Review

Internet of Things (IoT) which connects real-world physical objects with various identities involves different technologies and research areas. As it is an integration of different standards and technologies with numerous capabilities, the implementation phase needs to consider important parameters of communication. In IoT this is achieved through messaging protocols. Each object has its own limitations in terms of sensing capability, storage capacity, connectivity, power utilization, etc. And hence when such objects are deployed for different applications, they need to perform well in terms of their various capabilities. Messaging protocols at this stage need to consider these diverse elements. One of such IoT enabling technologies can be categorized as communication technology and networks, wherein data transmission protocols such as Hypertext Transmission Protocol (HTTP), Constrained Application Protocol (CoAP), Message Queue Telemetry Protocol (MQTT), MQTT for Sensor Networks (MQTT-SN), Advanced Message Queuing Protocol (AMQP) are used for data transmission. Each protocol has its own messaging architecture and standard. Any IoT application intends to provide optimum utilization of limited processing power and energy. In such a scenario integration and translation between various popular messaging protocols is needed. In this article bibliometric study for application like Aquaculture has been undertaken. The analysis done through Scopus database provides information about prominent countries involved in research field, highest citation documents, co-authorship links, funding sponsors etc. The bibliometric study conducted helped in understanding scope of the research field

Demystifying Artificial Intelligence based Digital Twins in Manufacturing- A Bibliometric Analysis of Trends and Techniques

Nowadays, data is considered as a new life force for operations of physical systems in various domains such as manufacturing, healthcare, transportations, etc. However, the hugely generated data, which mirrors the working essence of the product life cycle, is still underutilised. Digital Twin (DT), a collective representation of active and passive captured data, is a virtual counterpart of the physical resources that could help prevent effective preventive maintenance in any applied domain. Currently, lots of research is going on about the applicability of digital twin in smart IOT based manufacturing industry 4.0 environment. Still, it lacks a formal study, which can provide a bird\u27s eye view about the research efforts and directions. In this paper, the authors represent a bibliometric survey of the digital twin concept based on the Scopus database to present a global view about scholars\u27 contributions in the manufacturing area. The study was conducted by retrieving 844 Scopus research papers published from 2015-2020 and analysed to find out critical insights such as publication volume, co-authorship networks, citation analysis, and demographic research distribution. The study revealed that significant contribution is made via concept propositions in conferences and some papers published in the journal. However, there is a scope of lots of research work in the direction of actual and secure digital twin implementation

Characterization of Bioethanol Extracted from Napier Grass Using the Fermentation Process

Due to the diminishing supply of fossil fuels, biodiesel is gaining popularity as a feasible fuel. It is produced through the fermentation of Napier liquid with the help of bakery yeast. The pH test, viscosity analysis, multi-cylinder, and other tests yielded favourable results when compared to traditional fuels such as diesel. In the Viscosity analysis, we compare the pure and blended fuel with regular diesel, it was discovered that pure ethanol has reduced dynamic viscosity, which improves when blended with diesel. For the multi-cylinder engine performance test, adding 10 % ethanol to gasoline results in a bit of improvement in efficiency over regular diesel. The efficiency is greater than the previous one when it reaches 20 %. As a significance, we blended ethanol up to 20 % with normal diesel to obtain optimum results. Because complete combustion is achieved due to oxygen contained in ethanoldiesel blends, the exhaust gas temperature of the blends is found to be lower, and Nitrogen emission is higher compared to diesel

Estimating Remaining Useful Life in Machines Using Artificial Intelligence: A Scoping Review

The remaining useful life (RUL) estimations become one of the most essential aspects of predictive maintenance (PdM) in the era of industry 4.0. Predictive maintenance aims to minimize the downtime of machines or process, decreases maintenance costs, and increases the productivity of industries. The primary objective of this bibliometric paper is to understand the scope of literature available related to RUL prediction. Scopus database is used to perform the analysis of 1673 extracted scientific literature from the year 1985 to 2020. Based on available published documents, analysis is done on the year-wise publication data, document types, language-wise distribution of documents, funding sponsors, authors contributions, affiliations, document wise citations, etc. to give an in-depth view of the research trends in the area of RUL prediction. The paper also focuses on the available maintenance methods, predictive maintenance models, RUL models, deep learning algorithms for RUL prediction challenges and future directions in the RUL prediction area

Evaluation of Friction Stir Processing for fabrication of composites in the context of Industry 4.0: A Bibliometric Review

Aluminum alloys having good strength to weight ratio and resistance to corrosion have a wide range of applications in aerospace, automobiles, military, sports and many other applications. In order to enhance the hardness and wear resistance of the surface without compromising the bulk properties, aluminum matrix based surface composites fabricated with various reinforcements on the surface are now a days being utilized widely as new generation materials. In the manufacturing of metal surface hybrid composites (precisely of light weight alloys like- Al, Mg, etc.), the friction stir processing is a promising new solid state processing technique which is versatile enough to incorporate controlled uniform distribution of the reinforcements into the matrix for reduced defects and improved properties at the surface. The objective of this bibliometric review is to understand the scope of Industry 4.0 applications in the condition monitoring and evaluation of friction stir processing for fabrication of surface hybrid composites based on the existing literature. In order to analyze the available literature, a total of 1027 published documents have been studied using scopus database. Based on the published documents, research is focused on the analysis based on yearly published documents, types of documents, source titles, keywords searched, affiliations of authors, funding sponsors, countries related, source types, languages of publications, etc

Breast Cancer Detection from Histopathology Images using Machine Learning Techniques: A Bibliometric Analysis

Computer aided diagnosis has become upcoming area of research over past few years. With the advent of machine learning and especially deep learning techniques, the scenario of work flow management in healthcare sector is changing drastically. Artificial intelligence has shown potential in the field of breast cancer care. With datasets for machine learning frameworks getting eventually richer with time, we can definitely get newer insights in the field of breast cancer care. This will help in narrowing down the treatment range for patients and increasing patient survivability. The purpose of this study was to perform bibliometric analysis of the literature in the area of breast cancer detection using machine learning. Analysis was done for various elements like publication types, highly influential authors, most prominent journals, institutional affiliations, main keywords, etc. This analysis may direct future researchers by giving thorough quantitative evaluation of research documents in the field of breast cancer detection using machine learning

Three Degrees of Freedom Robotic arm and its Digital Twin using Simulink – A Bibliometric Analysis

The 3-degree Digital Twin robotic arm for freedom can diagnose the joints off-board by placing a torque in the robotic arm joint. MATLAB, Simulink®, SimscapeTM, and Simscape Multibody were the basis of this model. Virtual space with a virtual robot arm was connected to a physical space that was a 3D printed replica of the virtual space and robot arm, built using Unity (a modern Game Engine). The arm in the Digital Twin model was created using the hardware prototype’s dimensions, which were then used to simulate a real-world situation. With its revolute joints, the arm has a certain degree of freedom. The relations between the different elements of the arm were explained through frame transformations. Simulink signal builder generates the inputs. Robotic arms are one of the most frequently used devices for manufacturing processes and can automate a range of tasks on the floor, for instance. However, for these devices to work, they must have AI that has been properly trained. It proposes a method for dealing with virtual learning to the real robot twin mapping. Considering the importance of Digital Twin, it is essential to study the research trends and research origin. Hence, in this article detailed and meticulous study of digital twin and its bibliometric analysis is carried out. Various aspects such as top research articles, funding resources, affiliations, document types, etc. are collected from the Scopus database. The bibliometric study is even extended to network analysis to understand co-author relations, and citation analysis is also presented

Extraction and Performance Analysis of Hydrocarbons from Waste Plastic Using the Pyrolysis Process

Ecosystem destruction is one of today’s significant challenges due to fast industrialisation and an increasing population. It takes several years for solid trash, such as plastic bottles and super-market bags, to decompose in nature. In addition, plastic disposal techniques such as landfilling, reuse, and incineration pose significant threats to human health and the environment. In this paper, we investigated whether the impact of mixing biodiesel with waste oil from recycled plastic on the resulting fuel mixture’s yields better physical and chemical properties. Consequently, pyrolysis is one of the most advantageous and practical waste disposal methods as it is both environmentally benign and efficient. Pyrolysis is the high-temperature thermal breakdown of solid waste to produce pyrolytic oil. The pyrolytic (plastic) oil produced is converted to a hydrocarbon-rich pyrolytic fuel. Similar to diesel and gasoline, pyrolytic fuel has the same calorific value. Internal combustion engines may operate on pyrolytic fuel without suffering a performance reduction. Researchers examined engine performance and exhaust pollutants. The research discovered that the engine could operate on plastic pyrolysis fuel at full load, enhance brake thermal efficiency by 6–8%, and lower UBHC and CO emissions; however, nitrous oxide (NOx) emissions were noticeably higher. The findings demonstrated the possibility of using plastic pyrolysis fuel as a diesel substitute

Real-Time Monitoring of FDM 3D Printer for Fault Detection Using Machine Learning: A Bibliometric Study

Additive Manufacturing has wide application range including healthcare, Fashion, Manufacturing, Prototypes, Tooling etc. AM techniques are subjected to various defects that may be printing defects or anomalies in machine. There is gap between current AM techniques and smart manufacturing since current AM lacks in build sensors necessary for process monitoring and fault detection. Both of these issues can be solved by incorporating real-time monitoring into AM. So the study is carried out to identify recent work done in AM to improve current system. For this bibliometric study Scopus database is used, study is kept limited to year 2010-2021 and English language for recent trend analysis. Total of 1483 documents are analyzed based on author co-authors, keyword, geographical area, funding sponsor, affiliation, subject area, source title and citation count. The study is also focused on use of ML for fault detection in AM, types of monitoring methods, challenges and future direction of AM in smart manufacturing

Extraction and Performance Analysis of Hydrocarbons from Waste Plastic Using the Pyrolysis Process

Ecosystem destruction is one of today’s significant challenges due to fast industrialisation and an increasing population. It takes several years for solid trash, such as plastic bottles and super-market bags, to decompose in nature. In addition, plastic disposal techniques such as landfilling, reuse, and incineration pose significant threats to human health and the environment. In this paper, we investigated whether the impact of mixing biodiesel with waste oil from recycled plastic on the resulting fuel mixture’s yields better physical and chemical properties. Consequently, pyrolysis is one of the most advantageous and practical waste disposal methods as it is both environmentally benign and efficient. Pyrolysis is the high-temperature thermal breakdown of solid waste to produce pyrolytic oil. The pyrolytic (plastic) oil produced is converted to a hydrocarbon-rich pyrolytic fuel. Similar to diesel and gasoline, pyrolytic fuel has the same calorific value. Internal combustion engines may operate on pyrolytic fuel without suffering a performance reduction. Researchers examined engine performance and exhaust pollutants. The research discovered that the engine could operate on plastic pyrolysis fuel at full load, enhance brake thermal efficiency by 6–8%, and lower UBHC and CO emissions; however, nitrous oxide (NOx) emissions were noticeably higher. The findings demonstrated the possibility of using plastic pyrolysis fuel as a diesel substitute