Pub Date : 2020-12-17DOI: 10.1201/9781003038467-14
Dhruv Rawat, Amit Kumar, Suresh Kumar
{"title":"A Secure Electronic Voting System Using Decentralized Computing","authors":"Dhruv Rawat, Amit Kumar, Suresh Kumar","doi":"10.1201/9781003038467-14","DOIUrl":"https://doi.org/10.1201/9781003038467-14","url":null,"abstract":"","PeriodicalId":42597,"journal":{"name":"ADCAIJ-Advances in Distributed Computing and Artificial Intelligence Journal","volume":"47 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2020-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75399831","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}
Pub Date : 2020-12-17DOI: 10.1201/9781003038467-16
Pushpa Singh, R. Singh, Narendra Singh, M. Singh
{"title":"A Distributed Artificial Intelligence","authors":"Pushpa Singh, R. Singh, Narendra Singh, M. Singh","doi":"10.1201/9781003038467-16","DOIUrl":"https://doi.org/10.1201/9781003038467-16","url":null,"abstract":"","PeriodicalId":42597,"journal":{"name":"ADCAIJ-Advances in Distributed Computing and Artificial Intelligence Journal","volume":"15 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2020-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78217511","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}
Pub Date : 2020-12-16DOI: 10.14201/ADCAIJ20209495106
Javier Parra Domínguez, Pedro Roseiro
This article aims at presenting Blockchain and Distributed Ledger Technologies from business perspective (although providing adequate technology context) and, especially, highlighting concrete implementations in Agri-Food Supply Chain, bringing security, transparency and robustness to solutions, and enabling the creation of added value through the provisioning of information to consumers which allow them to understand the origin, the transformation and the transportation of agri-food goods. It also brings some examples of European Programmes and Projects that are supporting innovative solutions to reach the market.
{"title":"Blockchain: a brief review of Agri-Food Supply Chain Solutions and Opportunities","authors":"Javier Parra Domínguez, Pedro Roseiro","doi":"10.14201/ADCAIJ20209495106","DOIUrl":"https://doi.org/10.14201/ADCAIJ20209495106","url":null,"abstract":"This article aims at presenting Blockchain and Distributed Ledger Technologies from business perspective (although providing adequate technology context) and, especially, highlighting concrete implementations in Agri-Food Supply Chain, bringing security, transparency and robustness to solutions, and enabling the creation of added value through the provisioning of information to consumers which allow them to understand the origin, the transformation and the transportation of agri-food goods. It also brings some examples of European Programmes and Projects that are supporting innovative solutions to reach the market.","PeriodicalId":42597,"journal":{"name":"ADCAIJ-Advances in Distributed Computing and Artificial Intelligence Journal","volume":"41 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2020-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78817556","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}
Pub Date : 2020-12-15DOI: 10.14201/ADCAIJ2020948394
Aníbal Reñones, Marta Galende
Practical research in AI often lacks of available and reliable datasets so the practitioners can try different algorithms. The field of predictive maintenance is particularly challenging in this aspect as many researchers don't have access to full-size industrial equipment or there is not available datasets representing a rich information content in different evolutions of faults. In this paper, it is presented a dataset with evolution of typical faults (commutator, winding and brush wear) in inexpensive DC motors under extensive monitoring (vibration, temperature, voltage, current and noise). These motors exhibit a particularly short useful life when operating out of nominal conditions (from 30 minutes to 6 hours) which make them very interesting to test different signal processing algorithms and introduce students and researchers into signal processing, fault detection and predictive maintenance. The paper explains in detail the experimentation and the structure of the real, un-processed, dataset published in the AI4EU platform with the aim of complying with the FAIR principle so the dataset is Findable, Accessible, Interoperable and Reusable.
{"title":"F.A.I.R. open dataset of brushed DC motor faults for testing of AI algorithms","authors":"Aníbal Reñones, Marta Galende","doi":"10.14201/ADCAIJ2020948394","DOIUrl":"https://doi.org/10.14201/ADCAIJ2020948394","url":null,"abstract":"Practical research in AI often lacks of available and reliable datasets so the practitioners can try different algorithms. The field of predictive maintenance is particularly challenging in this aspect as many researchers don't have access to full-size industrial equipment or there is not available datasets representing a rich information content in different evolutions of faults. In this paper, it is presented a dataset with evolution of typical faults (commutator, winding and brush wear) in inexpensive DC motors under extensive monitoring (vibration, temperature, voltage, current and noise). These motors exhibit a particularly short useful life when operating out of nominal conditions (from 30 minutes to 6 hours) which make them very interesting to test different signal processing algorithms and introduce students and researchers into signal processing, fault detection and predictive maintenance. The paper explains in detail the experimentation and the structure of the real, un-processed, dataset published in the AI4EU platform with the aim of complying with the FAIR principle so the dataset is Findable, Accessible, Interoperable and Reusable.","PeriodicalId":42597,"journal":{"name":"ADCAIJ-Advances in Distributed Computing and Artificial Intelligence Journal","volume":"52 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2020-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80157128","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}
Pub Date : 2020-12-14DOI: 10.14201/adcaij2020947182
Sergio Márquez Sánchez
Currently, companies in the industrial sector are focusing their efforts on incorporating the advances contained in the Industry 4.0 model, to continue competing in an increasingly high-tech market. These advances, in addition to productivity, have a remarkable impact on the working environment of workers and on the measures adopted to maintain a healthy workspace. Thus, for example, there are projects to develop augmented reality technologies for maintenance and industrial training, advanced modelling tools for additive manufacturing, or Big Data analysis platforms for industrial data. However, the solutions designed are too specific to a particular industry problem or the platforms proposed are too generalist and not easily adaptable to the industries. This work seeks to provide a reference software architecture at the service of the connected industry that allows the provision of new capacities for process optimisation, predictive maintenance and real-time visualisation, integrating all the relevant information generated by the existing systems, incorporating new sources of data resulting from the digital society, and ensuring future compatibility with the new sources of information, solutions and Industrial Internet of Things (IIoT) devices that may be implemented.
{"title":"Integral Support Predictive Platform for Industry 4.0","authors":"Sergio Márquez Sánchez","doi":"10.14201/adcaij2020947182","DOIUrl":"https://doi.org/10.14201/adcaij2020947182","url":null,"abstract":"Currently, companies in the industrial sector are focusing their efforts on incorporating the advances contained in the Industry 4.0 model, to continue competing in an increasingly high-tech market. These advances, in addition to productivity, have a remarkable impact on the working environment of workers and on the measures adopted to maintain a healthy workspace. Thus, for example, there are projects to develop augmented reality technologies for maintenance and industrial training, advanced modelling tools for additive manufacturing, or Big Data analysis platforms for industrial data. However, the solutions designed are too specific to a particular industry problem or the platforms proposed are too generalist and not easily adaptable to the industries. This work seeks to provide a reference software architecture at the service of the connected industry that allows the provision of new capacities for process optimisation, predictive maintenance and real-time visualisation, integrating all the relevant information generated by the existing systems, incorporating new sources of data resulting from the digital society, and ensuring future compatibility with the new sources of information, solutions and Industrial Internet of Things (IIoT) devices that may be implemented.","PeriodicalId":42597,"journal":{"name":"ADCAIJ-Advances in Distributed Computing and Artificial Intelligence Journal","volume":"41 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83652747","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}
Pub Date : 2020-12-12DOI: 10.14201/ADCAIJ2020945570
J. Maestro-Prieto, S. Rodríguez, R. Casado, J. Corchado
Real world applications using agent-based solutions can include many agents that needs communicate and interact each other in order to meet their objectives. In open multi-agent systems, the problems may include the organisation of a large number of agents that may be heterogeneous, of unpredictable provenance and where competitive behaviours or conflicting objectives may occur. An overview of the alternatives for dealing with these problems is presented, highlighting the way they try to solve or mitigate these problems.
{"title":"Agent organisations: from independent agents to virtual organisations and societies of agents","authors":"J. Maestro-Prieto, S. Rodríguez, R. Casado, J. Corchado","doi":"10.14201/ADCAIJ2020945570","DOIUrl":"https://doi.org/10.14201/ADCAIJ2020945570","url":null,"abstract":"Real world applications using agent-based solutions can include many agents that needs communicate and interact each other in order to meet their objectives. In open multi-agent systems, the problems may include the organisation of a large number of agents that may be heterogeneous, of unpredictable provenance and where competitive behaviours or conflicting objectives may occur. An overview of the alternatives for dealing with these problems is presented, highlighting the way they try to solve or mitigate these problems.","PeriodicalId":42597,"journal":{"name":"ADCAIJ-Advances in Distributed Computing and Artificial Intelligence Journal","volume":"45 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2020-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85958148","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}
Pub Date : 2020-12-07DOI: 10.1201/9781003038467-17
G. Kiruthiga, G. Devi, N. Yuvaraj, R. Raja, N. V. Kousik
{"title":"Analysis of Hybrid Deep Neural Networks with Mobile Agents for Traffic Management in Vehicular Adhoc Networks","authors":"G. Kiruthiga, G. Devi, N. Yuvaraj, R. Raja, N. V. Kousik","doi":"10.1201/9781003038467-17","DOIUrl":"https://doi.org/10.1201/9781003038467-17","url":null,"abstract":"","PeriodicalId":42597,"journal":{"name":"ADCAIJ-Advances in Distributed Computing and Artificial Intelligence Journal","volume":"110 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2020-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76134891","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":"Knowledge-Based Problem-Solving","authors":"R. Goel, S. Vishnoi, C. S. Yadav, Pankaj Tyagi","doi":"10.1201/9781003038467-3","DOIUrl":"https://doi.org/10.1201/9781003038467-3","url":null,"abstract":"","PeriodicalId":42597,"journal":{"name":"ADCAIJ-Advances in Distributed Computing and Artificial Intelligence Journal","volume":"21 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2020-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86710740","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}
Pub Date : 2020-12-07DOI: 10.1201/9781003038467-13
Naziya Hussain, P. Rani
{"title":"Comparative Studied Based on Attack Resilient and Efficient Protocol with Intrusion Detection System Based on Deep Neural Network for Vehicular System Security","authors":"Naziya Hussain, P. Rani","doi":"10.1201/9781003038467-13","DOIUrl":"https://doi.org/10.1201/9781003038467-13","url":null,"abstract":"","PeriodicalId":42597,"journal":{"name":"ADCAIJ-Advances in Distributed Computing and Artificial Intelligence Journal","volume":"15 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2020-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74437049","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}
Pub Date : 2020-12-07DOI: 10.1201/9781003038467-11
Shubhangi Sankhyadhar, M. Pandey
{"title":"Test Beds for Distributed AI Research","authors":"Shubhangi Sankhyadhar, M. Pandey","doi":"10.1201/9781003038467-11","DOIUrl":"https://doi.org/10.1201/9781003038467-11","url":null,"abstract":"","PeriodicalId":42597,"journal":{"name":"ADCAIJ-Advances in Distributed Computing and Artificial Intelligence Journal","volume":"11 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2020-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74702531","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}
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