Pub Date : 1900-01-01DOI: 10.4108/eai.24-11-2022.2329810
Ousmane W. Compaore, G. Hoblos, Z. Koalaga
. The performance of Photovoltaic Generators (PVG) drops over time due to failures compared with its maximum operating point. So, an early fault diagnosis method would make it possible to restore the PVG to good working order. The quality of this diagnostic method lies in several factors but also in the nature of the detection modes. Thanks to the computing capabilities, the analysis databases, and development of efficient algorithms closer to artificial intelligence, we realize that decision support methods are a great success for data science. This article offers an analysis of the complementarity of two diagnostic methods based on the analysis of redundancy relationships and on artificial neural networks. These two methods are supposed to provide a good return on investment for a PVG and set guidelines for diagnostic research.
{"title":"Analysis of the Complementarity of Two Diagnostic Methods on a PV Generator","authors":"Ousmane W. Compaore, G. Hoblos, Z. Koalaga","doi":"10.4108/eai.24-11-2022.2329810","DOIUrl":"https://doi.org/10.4108/eai.24-11-2022.2329810","url":null,"abstract":". The performance of Photovoltaic Generators (PVG) drops over time due to failures compared with its maximum operating point. So, an early fault diagnosis method would make it possible to restore the PVG to good working order. The quality of this diagnostic method lies in several factors but also in the nature of the detection modes. Thanks to the computing capabilities, the analysis databases, and development of efficient algorithms closer to artificial intelligence, we realize that decision support methods are a great success for data science. This article offers an analysis of the complementarity of two diagnostic methods based on the analysis of redundancy relationships and on artificial neural networks. These two methods are supposed to provide a good return on investment for a PVG and set guidelines for diagnostic research.","PeriodicalId":152951,"journal":{"name":"Proceedings of the 5th edition of the Computer Science Research Days, JRI 2022, 24-26 November 2022, Ouagadougou, Burkina Faso","volume":"398 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124134306","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 of a machine learning based model for academic performance prediction","authors":"Moustapha Bikienga, Ozias Bombiri, Emmanuel Sawadogo","doi":"10.4108/eai.24-11-2022.2329809","DOIUrl":"https://doi.org/10.4108/eai.24-11-2022.2329809","url":null,"abstract":"","PeriodicalId":152951,"journal":{"name":"Proceedings of the 5th edition of the Computer Science Research Days, JRI 2022, 24-26 November 2022, Ouagadougou, Burkina Faso","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121633517","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 : 1900-01-01DOI: 10.4108/eai.24-11-2022.2329814
Yacouba Ouedraogo, Mahamadou Belem, M. Dandjinou, T. Tapsoba
. The growing demography and galloping urbanization of the city of Ouagadougou in recent years had a considerable impact on the demand for school infrastructure. Urban dynamics coupled with school dynamics is a complex system characterized by a set of complex interactions at different spatio-temporal scales. Modeling by its ability to abstract and integrate data from different sources and natures and to predict the state of a complex system is relevant for analyzing the impact of demography on the development of school infrastructures. This study aims at developing an agent-based model to represent the interactions between the urban system and the school system. Throughout this study, a conceptual framework based on a multi-formalism and multi-scale approaches have been proposed. Finally, a simulation prototype was developed to analyze the impact of demography on the development of school infrastructures. In perspective, it will be a question of finalizing the development of the decision-making tool, carrying out simulations and setting up a massive database.
{"title":"Simulation of the Impact of Urbanization and Demography on the Demand for School Infrastructure in the City of Ouagadougou: Towards a conceptual framework","authors":"Yacouba Ouedraogo, Mahamadou Belem, M. Dandjinou, T. Tapsoba","doi":"10.4108/eai.24-11-2022.2329814","DOIUrl":"https://doi.org/10.4108/eai.24-11-2022.2329814","url":null,"abstract":". The growing demography and galloping urbanization of the city of Ouagadougou in recent years had a considerable impact on the demand for school infrastructure. Urban dynamics coupled with school dynamics is a complex system characterized by a set of complex interactions at different spatio-temporal scales. Modeling by its ability to abstract and integrate data from different sources and natures and to predict the state of a complex system is relevant for analyzing the impact of demography on the development of school infrastructures. This study aims at developing an agent-based model to represent the interactions between the urban system and the school system. Throughout this study, a conceptual framework based on a multi-formalism and multi-scale approaches have been proposed. Finally, a simulation prototype was developed to analyze the impact of demography on the development of school infrastructures. In perspective, it will be a question of finalizing the development of the decision-making tool, carrying out simulations and setting up a massive database.","PeriodicalId":152951,"journal":{"name":"Proceedings of the 5th edition of the Computer Science Research Days, JRI 2022, 24-26 November 2022, Ouagadougou, Burkina Faso","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122395506","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 : 1900-01-01DOI: 10.4108/eai.24-11-2022.2329806
H. O. Hamidou, Justin P. Kouraogo, Oumarou Sié, David Tapsoba
In this paper, we discuss quality of experience in multimedia networks. We present an architecture and a survey of machine learning methods to predict the quality of experience in an enterprise multimedia network environment. Our approach is based on subjective methods. It consists of the use PRTG (Paessler Router Traffic Grapher) for QoS (quality of service) data collection and Google Forms for the different users of the network MOS (Minimum Score Opinion) parameters collection. We then implement different supervised machine learning schemes using the data collected, and finally analyze their performance. We compare two classes of algorithms namely regression algorithms and classification algorithms. The Random Forest Classifier in the second class algorithm give the best results.
{"title":"Machine learning based Quality of Experience (QoE) Prediction Approach in Enterprise Multimedia Networks","authors":"H. O. Hamidou, Justin P. Kouraogo, Oumarou Sié, David Tapsoba","doi":"10.4108/eai.24-11-2022.2329806","DOIUrl":"https://doi.org/10.4108/eai.24-11-2022.2329806","url":null,"abstract":"In this paper, we discuss quality of experience in multimedia networks. We present an architecture and a survey of machine learning methods to predict the quality of experience in an enterprise multimedia network environment. Our approach is based on subjective methods. It consists of the use PRTG (Paessler Router Traffic Grapher) for QoS (quality of service) data collection and Google Forms for the different users of the network MOS (Minimum Score Opinion) parameters collection. We then implement different supervised machine learning schemes using the data collected, and finally analyze their performance. We compare two classes of algorithms namely regression algorithms and classification algorithms. The Random Forest Classifier in the second class algorithm give the best results.","PeriodicalId":152951,"journal":{"name":"Proceedings of the 5th edition of the Computer Science Research Days, JRI 2022, 24-26 November 2022, Ouagadougou, Burkina Faso","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127772208","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 : 1900-01-01DOI: 10.4108/eai.24-11-2022.2329811
Salifou Ouedraogo, D. Guel, Justin P. Kouraogo, Yann Sanou
. Producers need to have information on the agricultural parameters of their plantations without having to be on site. The objective of this work is to propose an intelligent agriculture platform or Precision Agriculture (PA) in order to collect soil humidity, air and temperature. The purpose of the PA is to contribute to food security while ensuring optimal use of resources. To do this, we offer a platform consisting of HW-390 capacitive soil humidity sensors, DHT22 air temperature and humidity sensors and microcontrollers. The HW-390 returns an analog value that gravitates around 1540 when the soil is wet and 3155 when the soil is dry. The DHT22 measures temperature and humidity with an accuracy of +/- 0.5°C and +/- 1% respectively. The power supply circuit consisting of a rechargeable battery in a maximum of 10 hours has an autonomy of 38 hours.
{"title":"Design of an IoT Platform for a Precision Agriculture (PA) in Burkina Faso","authors":"Salifou Ouedraogo, D. Guel, Justin P. Kouraogo, Yann Sanou","doi":"10.4108/eai.24-11-2022.2329811","DOIUrl":"https://doi.org/10.4108/eai.24-11-2022.2329811","url":null,"abstract":". Producers need to have information on the agricultural parameters of their plantations without having to be on site. The objective of this work is to propose an intelligent agriculture platform or Precision Agriculture (PA) in order to collect soil humidity, air and temperature. The purpose of the PA is to contribute to food security while ensuring optimal use of resources. To do this, we offer a platform consisting of HW-390 capacitive soil humidity sensors, DHT22 air temperature and humidity sensors and microcontrollers. The HW-390 returns an analog value that gravitates around 1540 when the soil is wet and 3155 when the soil is dry. The DHT22 measures temperature and humidity with an accuracy of +/- 0.5°C and +/- 1% respectively. The power supply circuit consisting of a rechargeable battery in a maximum of 10 hours has an autonomy of 38 hours.","PeriodicalId":152951,"journal":{"name":"Proceedings of the 5th edition of the Computer Science Research Days, JRI 2022, 24-26 November 2022, Ouagadougou, Burkina Faso","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128814765","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 : 1900-01-01DOI: 10.4108/eai.24-11-2022.2329802
Aboudramane Diarra, Tegawendé F. Bissyandé, Pasteur Poda
{"title":"A Deep Learning App for Counterfeit Banknote Detection in the WAEMU","authors":"Aboudramane Diarra, Tegawendé F. Bissyandé, Pasteur Poda","doi":"10.4108/eai.24-11-2022.2329802","DOIUrl":"https://doi.org/10.4108/eai.24-11-2022.2329802","url":null,"abstract":"","PeriodicalId":152951,"journal":{"name":"Proceedings of the 5th edition of the Computer Science Research Days, JRI 2022, 24-26 November 2022, Ouagadougou, Burkina Faso","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133374525","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 : 1900-01-01DOI: 10.4108/eai.24-11-2022.2329804
Charles Traoré, Stéphane Aimé Metchebon Takougang
{"title":"Full Integration of the multiple criteria decision making method KEMIRA-sort into a Geographical Information System for spatial management","authors":"Charles Traoré, Stéphane Aimé Metchebon Takougang","doi":"10.4108/eai.24-11-2022.2329804","DOIUrl":"https://doi.org/10.4108/eai.24-11-2022.2329804","url":null,"abstract":"","PeriodicalId":152951,"journal":{"name":"Proceedings of the 5th edition of the Computer Science Research Days, JRI 2022, 24-26 November 2022, Ouagadougou, Burkina Faso","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131245557","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 : 1900-01-01DOI: 10.4108/eai.24-11-2022.2329807
Dekpeltakié Augustin Metouale Somda, A. Séré
{"title":"Traffic Saturation Detection using Hough Transform and VANET","authors":"Dekpeltakié Augustin Metouale Somda, A. Séré","doi":"10.4108/eai.24-11-2022.2329807","DOIUrl":"https://doi.org/10.4108/eai.24-11-2022.2329807","url":null,"abstract":"","PeriodicalId":152951,"journal":{"name":"Proceedings of the 5th edition of the Computer Science Research Days, JRI 2022, 24-26 November 2022, Ouagadougou, Burkina Faso","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128435895","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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