Journal of Edge Computing最新文献

{"title":"Enhanced deep learning model architecture for plant disease detection in Chilli plants","authors":"Sultanul Arifeen Hamim, Akinul Islam Jony","doi":"10.55056/jec.758","DOIUrl":"https://doi.org/10.55056/jec.758","url":null,"abstract":"A new deep-learning model for classifying and detecting plant diseases in chilli plants is described. It is built on a modified version of the MobileNet architecture. The model overcomes conventional diagnostic tools’ high computing costs and restricted adaptability by combining sophisticated optimisation models and reliable training procedures. The model considerably reduces the time and resources needed for an accurate diagnosis while effectively managing complicated illness presentations, with a diagnostic accuracy of 97.18%. Using the chilli leaf picture dataset, data augmentation, and finetuning techniques, the model shows promise for real-time disease diagnosis in agricultural environments. The study underscores the importance of high-quality image data and extensive training datasets, calling for further evaluation across various climatic and environmental conditions to ensure robustness and adaptability. This research opens new opportunities for AI-based models in diverse agricultural contexts, potentially leading to significant advancements in precision farming.","PeriodicalId":397265,"journal":{"name":"Journal of Edge Computing","volume":"114 20","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141820389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancing IoT interoperability: dynamic data serialization using ThingsBoard","authors":"Dmytro I. Shvaika, Andrii I. Shvaika, Volodymyr O. Artemchuk","doi":"10.55056/jec.745","DOIUrl":"https://doi.org/10.55056/jec.745","url":null,"abstract":"Benchmarking leading data serialization protocols such as schemaless JSON with binary serialization formats demonstrates the superior performance of the latter in Internet of Things (IoT) ecosystems. However, ease of integration and maintenance are equally important factors for real-world applications. IoT developers choose schemaless JSON formats for primary serialization because of their user-friendliness. However, interest in using Protocol Buffers directly at the device level in Internet of Things ecosystems is growing. Many IoT devices now transfer data exclusively via Protobuf, while others are switching to this format to improve efficiency and reduce network load. However, the static nature of Protobuf requires constant developer intervention, which undermines the scalability and versatility of the platforms, especially in cloud deployments. We explore the challenges of integrating devices that communicate exclusively through Protobuf into IoT platforms using the ThingsBoard as an example. Our study proposes a dynamic method for integrating new Protobuf-compatible devices by automating the compilation of the scheme into the platform’s code base. This approach aims to simplify integration and maintenance, which, in addition to productivity, are key factors in operating efficiencyin IoT environments.","PeriodicalId":397265,"journal":{"name":"Journal of Edge Computing","volume":" 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141822809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Empowering the Edge: Research advances from doors 2024","authors":"T. Vakaliuk, S. Semerikov","doi":"10.55056/jec.747","DOIUrl":"https://doi.org/10.55056/jec.747","url":null,"abstract":"The 4th Edge Computing Workshop (doors 2024) held in Zhytomyr, Ukraine, aimed to bring together researchers to share advances and applications in edge computing, a critical technology for enabling the Internet of Things and analytics close to data sources. This report summarises the event, highlighting the peer-reviewed papers covering topics from edge hardware to AI and security. The nine accepted papers, selected from 19 submissions, propose innovative approaches to advance the field. Common themes include leveraging edge computing for sensing applications and addressing resource utilisation and management challenges. The workshop stimulated valuable discussion and collaboration around these important research directions.","PeriodicalId":397265,"journal":{"name":"Journal of Edge Computing","volume":"130 27","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141115178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial for JEC Volume 3 Issue 1 (2024)","authors":"S. Semerikov","doi":"10.55056/jec.737","DOIUrl":"https://doi.org/10.55056/jec.737","url":null,"abstract":"This editorial introduces the first issue of the third volume of the Journal of Edge Computing (JEC). It provides an overview of the five articles featured in this issue, which cover diverse applications of edge computing technologies in domains such as cybersecurity, healthcare, and distributed systems. The first article summarizes the 4th Edge Computing Workshop (doors 2024), highlighting research advances in edge computing. The second article proposes an LSTM-based model for detecting cyber attacks in IoT systems using the CIC-IoT2023 dataset. The third article presents a machine-learning model for classifying respiratory system sounds to aid in the early diagnosis of respiratory diseases. The fourth article describes an IoT system that analyzes environmental data using geolocation to generate alerts about potential health risks. The fifth article explores the use of telemetry for dynamic analysis of distributed systems to identify architectural smells and anomalies. The editorial highlights the potential of edge computing technologies in addressing various challenges and expresses gratitude to the authors, reviewers, and editorial team for their contributions.","PeriodicalId":397265,"journal":{"name":"Journal of Edge Computing","volume":"139 30","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141114516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A long short-term memory based approach for detecting cyber attacks in IoT using CIC-IoT2023 dataset","authors":"Akinul Islam Jony, Arjun Kumar Bose Arnob","doi":"10.55056/jec.648","DOIUrl":"https://doi.org/10.55056/jec.648","url":null,"abstract":"The growth of Internet of Things (IoT) gadgets has ushered in a new era of connectedness and convenience, but it has also sparked worries about security flaws. Long Short-Term Memory (LSTM) networks are used in this research's use of intrusion detection as a novel strategy to strengthen IoT security. The proposed LSTM-based model excels in detecting both known and evolving cyber-attack patterns with an accuracy rate of 98.75% and an F1 score of 98.59% in extensive experimental evaluations using the vast CIC-IoT2023 dataset, representing a varied array of IoT network traffic scenarios. This research contributes significantly to IoT security while addressing the urgent need for adaptable intrusion detection systems to defend against changing cyber threats. It is an essential step toward ensuring IoT technology's long-term development and dependability in a world that is becoming more interconnected.","PeriodicalId":397265,"journal":{"name":"Journal of Edge Computing","volume":"31 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139126045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial for JEC Volume 2 Issue 2 (2023)","authors":"T. Vakaliuk","doi":"10.55056/jec.654","DOIUrl":"https://doi.org/10.55056/jec.654","url":null,"abstract":"This editorial presents innovative research at the intersection of edge computing and various disciplines, demonstrating the transformative potential of edge computing technologies. The issue includes a study on a digital Proportional-Integral-Derivative (PID) regulator model for controlling unmanned aerial vehicles, using digital filtering methods and a genetic algorithm; discusses an autonomous Internet of Things (IoT) system for monitoring classroom microclimates, contributing to the understanding of how microclimate parameters influence the physiological state of students; details the design and implementation of an educational model for a smart home, integrating various subsystems and renewable energy sources. This issue aims to inspire further exploration and innovation in edge computing, driving the field forward and opening up new possibilities for technology and society.","PeriodicalId":397265,"journal":{"name":"Journal of Edge Computing","volume":"51 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139260523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design and implementation of an IoT-based educational model for smart homes: a STEM approach","authors":"N. Balyk, S. Leshchuk, D. Yatsenyak","doi":"10.55056/jec.632","DOIUrl":"https://doi.org/10.55056/jec.632","url":null,"abstract":"This work presents a comprehensive study on the design and implementation of an educational model for a smart home, leveraging the principles of the Internet of Things (IoT). The model encompasses three key levels: command, communication, and management, and integrates several subsystems, including communication, signalling, lighting control, temperature regulation, garbage container filling, nd sensor data monitoring. The hardware components for implementing the Mini Smart House, a practical application of the model, are detailed in the study. The Mini Smart House utilizes a range of technologies for efficient management and incorporates renewable energy sources for power. The model was independently produced by students participating in a STEM project, with research activities encompassing sketching, construction part creation, sensor assembly, Arduino board programming in the Arduino IDE environment, and system functionality testing. The Mini Smart House was validated within the STEM-center of the Physics and Mathematics Faculty of Ternopil Volodymyr Hnatiuk National Pedagogical University during the educational process and numerous trainings and seminars for pupils and teachers of computer science.","PeriodicalId":397265,"journal":{"name":"Journal of Edge Computing","volume":"15 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139260888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design and implementation of an edge computing-based GPS tracking system","authors":"M. V. Klymenko, A. Striuk","doi":"10.55056/jec.634","DOIUrl":"https://doi.org/10.55056/jec.634","url":null,"abstract":"This paper presents a comprehensive study on the technical aspects of edge-enabled GPS tracking systems, their evolution, and an analysis of existing problem-solving approaches. It introduces mathematical models that simulate the operation of the hardware and software components of these systems. An adaptive user interface has been developed, enabling usage across various platforms such as smartphones and personal computers. The paper also explores innovative methods for visualizing the trajectory of a moving object on an electronic map. Specialized software for the Atmega162-16PU microcontroller has been developed to control the GSM module and GPS receiver. A novel method for data transmission from a GPS tracker to a web server is proposed. The paper concludes with the successful testing of two experimental GPS-tracker prototypes under uncertain conditions. The developed edge-enabled GPS tracking software and hardware show potential for monitoring moving objects within the coverage of GSM cellular networks.","PeriodicalId":397265,"journal":{"name":"Journal of Edge Computing","volume":"22 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139260842","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Edge computing in environmental science: automated intelligent robotic platform for water quality assessment","authors":"Andrii G. Tkachuk, Mariia Hrynevych, T. Vakaliuk, O. Chernysh, Mykhailo G. Medvediev","doi":"10.55056/jec.633","DOIUrl":"https://doi.org/10.55056/jec.633","url":null,"abstract":"This paper introduces a novel intelligent robotic platform designed to expedite and enhance the process of water quality assessment and bottom relief analysis in reservoirs. The platform, equipped with an array of sensors and actuators, is capable of conducting comprehensive studies over larger areas of the reservoir, thereby overcoming the limitations of traditional water analysis methods. The platform’s advanced design includes a control board, servo motors, a brushless motor, a radio module, a GPS module, and a motor speed controller, all housed within a robust casing. The paper presents a functional diagram of the platform and discusses the results of a system study conducted on a reservoir. The study aimed to verify the system’s operation, evaluate the effectiveness of the research conducted, and calibrate water quality sensors. The platform utilizes an ultrasonic sensor for depth measurement and sensors for water acidity and temperature. The results of the monitoring system experiments led to the creation of a detailed map of the reservoir’s bottom area and provided valuable insights into water quality.","PeriodicalId":397265,"journal":{"name":"Journal of Edge Computing","volume":"200 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139259906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigating the effect of virtual machine migration accounting on reliability using a cluster model","authors":"A. V. Riabko, T. Vakaliuk, O. Zaika, R. Kukharchuk, V. Kontsedailo","doi":"10.55056/jec.585","DOIUrl":"https://doi.org/10.55056/jec.585","url":null,"abstract":"The purpose of the article is to develop and verify with the help of mathematical modeling a software method of deploying a fault-tolerant computing cluster with a virtual machine, which consists of two physical servers (main and backup), on which a distributed data storage system with synchronous data replication from the source server to the backup server is deployed. For this purpose, the task is to conduct a computational experiment on a model of a fault-tolerant cluster, which neglects costs during recovery for the migration of virtual machines by means of the mathematical application Mathcad. Combining computing resources into clusters is a way to ensure high reliability, fault tolerance, and continuity of the computing process of computer systems. This is achieved through virtualization, which enables the movement of virtual resources, services, or applications between physical servers while maintaining the continuity of computing processes. The focus of this study is on a failover cluster, which is composed of two physical servers (primary and backup) connected through a switch, and each server has a local hard disk. A distributed storage system with synchronous data replication from the source server to the backup server is deployed on the local disks of the servers, and a virtual machine is running on the cluster. Markovian processes, flows of podias, and Kolmogorov's systems of differential equations are built into the mathematical tools of the model of a water cluster. To ensure the continuity of the computing process in case of a failure of the main server, a shadow copy of the virtual machine is launched on the backup server. The reliability of the failover cluster is measured by the coefficient of non-stationary readiness. A Markov model is proposed to assess the reliability of the failover cluster, taking into account the costs of migrating virtual machines and mechanisms that ensure the continuity of the computing process in the cluster in case of a failure of one physical server. The memory migration process maintains two copies of the virtual machine on different physical servers, enabling them to continue working on the other in the event of failure. A simplified model of the failover cluster neglects the cost of migrating virtual machines and provides an upper estimate of reliability. The study shows that the reliability of a failover cluster, as measured by the non-stationary availability factor, is significantly impacted by the virtual machine migration process. The findings of this study can be used to inform decisions about the technology chosen to ensure the failure stability and continuity of the computing process of computer systems with cluster architecture. The calculations allow us to draw a conclusion about the significant impact of virtual machine migration accounting on reliability. The calculations allow us to draw a conclusion about the significant impact of virtual machine migration accounting on reliability. ","PeriodicalId":397265,"journal":{"name":"Journal of Edge Computing","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133044788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}