Pub Date : 2024-03-08DOI: 10.47709/brilliance.v3i2.3649
Rahmadani Putri, Ratna Dewi, Silfia Rifka, Sri Nita, Andi Ahmad Dahlan
This research focuses on the design and implementation of a rainfall monitoring system for chili pepper farms using Internet of Things (IoT) technology. The rainfall monitoring system consists of a transmitter system, a receiver system, the Thingspeak platform as a database, and a weather station application that can be accessed via a mobile device. The weather station application is built using the MIT App Inventor platform. In the testing phase, the system successfully collected data from two sensors used, namely the rainfall intensity sensor and the raindrop sensor. The test results showed that the data obtained from the rainfall intensity sensor was 0.25 inches and the raindrop sensor was 1. This result shows that there was no rain during the test. This rain intensity and raindrop data can provide farmers with an overview of the weather conditions in the chili pepper farm. So, with this rainfall monitoring system, farmers can monitor the condition of their agricultural land in real-time. The collected data can help farmers to care for chili pepper plants more effectively and adapt to environmental changes. In addition, this system is expected to increase the productivity of chili pepper farming because it uses a more precise and responsive approach to changes in environmental conditions on the chili pepper farm.
{"title":"IoT-Based Rainfall Monitoring System for Chili Farming Land","authors":"Rahmadani Putri, Ratna Dewi, Silfia Rifka, Sri Nita, Andi Ahmad Dahlan","doi":"10.47709/brilliance.v3i2.3649","DOIUrl":"https://doi.org/10.47709/brilliance.v3i2.3649","url":null,"abstract":"This research focuses on the design and implementation of a rainfall monitoring system for chili pepper farms using Internet of Things (IoT) technology. The rainfall monitoring system consists of a transmitter system, a receiver system, the Thingspeak platform as a database, and a weather station application that can be accessed via a mobile device. The weather station application is built using the MIT App Inventor platform. In the testing phase, the system successfully collected data from two sensors used, namely the rainfall intensity sensor and the raindrop sensor. The test results showed that the data obtained from the rainfall intensity sensor was 0.25 inches and the raindrop sensor was 1. This result shows that there was no rain during the test. This rain intensity and raindrop data can provide farmers with an overview of the weather conditions in the chili pepper farm. So, with this rainfall monitoring system, farmers can monitor the condition of their agricultural land in real-time. The collected data can help farmers to care for chili pepper plants more effectively and adapt to environmental changes. In addition, this system is expected to increase the productivity of chili pepper farming because it uses a more precise and responsive approach to changes in environmental conditions on the chili pepper farm.","PeriodicalId":440433,"journal":{"name":"Brilliance: Research of Artificial Intelligence","volume":"23 25","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140258144","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}
Digital marketing is promotional activities and market search through the media digitally online by utilizing various means such as social networks. The aim of this research is to increase knowledge and skills about digital marketing, especially social media, for Small and Medium Enterprises (SME) business people to increase their sales and profits. Digital marketing is the use of social media networks to carry out promotional activities and map digital markets. By using computers or other electronic equipment, digital marketing ideas can bring together geographically diverse parties. The aim of this research is to identify the most effective digital marketing tactics for the growth of MSMEs in Tegal City and Tegal Regency. The method used in this research is descriptive qualitative. With Data collection through observation, interviews, and secondary sources, such as books, journals, and articles, were used to collect information for this research. The results of this research show that the productivity growth of MSMEs in Tegal City and Tegal Regency has not been positive. Even when a website for an online business has been created, not everyone has implemented a digital marketing plan. It can be seen that digital marketing strategies have not received much attention from MSMEs in Tegal City and Tegal Regency. So it is hoped that MSMEs in Tegal City and Tegal Regency can adapt to changing times, namely selling online using digital marketing strategies.
{"title":"Digital Marketing Efforts to Improve Products of Micro Small and Medium Enterprises (UMKM) in Tegal","authors":"Nugroho Adhi Santoso, Bangkit Indarmawan Nugroho, Aang Alim Murtopo, Sarif Surorejo, Gunawan Gunawan","doi":"10.47709/brilliance.v3i2.3646","DOIUrl":"https://doi.org/10.47709/brilliance.v3i2.3646","url":null,"abstract":"Digital marketing is promotional activities and market search through the media\u0000digitally online by utilizing various means such as social networks. The aim of this research is to increase knowledge and skills about digital marketing, especially social media, for Small and Medium Enterprises (SME) business people to increase their sales and profits. Digital marketing is the use of social media networks to carry out promotional activities and map digital markets. By using computers or other electronic equipment, digital marketing ideas can bring together geographically diverse parties. The aim of this research is to identify the most effective digital marketing tactics for the growth of MSMEs in Tegal City and Tegal Regency. The method used in this research is descriptive qualitative. With Data collection through observation, interviews, and secondary sources, such as books, journals, and articles, were used to collect information for this research. The results of this research show that the productivity growth of MSMEs in Tegal City and Tegal Regency has not been positive. Even when a website for an online business has been created, not everyone has implemented a digital marketing plan. It can be seen that digital marketing strategies have not received much attention from MSMEs in Tegal City and Tegal Regency. So it is hoped that MSMEs in Tegal City and Tegal Regency can adapt to changing times, namely selling online using digital marketing strategies.","PeriodicalId":440433,"journal":{"name":"Brilliance: Research of Artificial Intelligence","volume":"96 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140408710","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 : 2024-01-31DOI: 10.47709/brilliance.v3i2.3488
Gregorius Airlangga
The efficacy of machine learning models in speaker recognition tasks is critical for advancements in security systems, biometric authentication, and personalized user interfaces. This study provides a comparative analysis of three prominent machine learning models: Naive Bayes, Logistic Regression, and Gradient Boosting, using the LibriSpeech test-clean dataset—a corpus of read English speech from audiobooks designed for training and evaluating speech recognition systems. Mel-Frequency Cepstral Coefficients (MFCCs) were extracted as features from the audio samples to represent the power spectrum of the speakers’ voices. The models were evaluated based on precision, recall, F1-score, and accuracy to determine their performance in correctly identifying speakers. Results indicate that Logistic Regression outperformed the other models, achieving nearly perfect scores across all metrics, suggesting its superior capability for linear classification in high-dimensional spaces. Naive Bayes also demonstrated high efficiency and robustness, despite the inherent assumption of feature independence, while Gradient Boosting showed slightly lower performance, potentially due to model complexity and overfitting. The study underscores the potential of simpler machine learning models to achieve high accuracy in speaker recognition tasks, particularly where computational resources are limited. However, limitations such as the controlled nature of the dataset and the focus on a single feature type were noted, with recommendations for future research to include more diverse environmental conditions and feature sets.
{"title":"Evaluating the Efficacy of Traditional Machine Learning Models in Speaker Recognition: A Comparative Study Using the LibriSpeech Dataset","authors":"Gregorius Airlangga","doi":"10.47709/brilliance.v3i2.3488","DOIUrl":"https://doi.org/10.47709/brilliance.v3i2.3488","url":null,"abstract":"The efficacy of machine learning models in speaker recognition tasks is critical for advancements in security systems, biometric authentication, and personalized user interfaces. This study provides a comparative analysis of three prominent machine learning models: Naive Bayes, Logistic Regression, and Gradient Boosting, using the LibriSpeech test-clean dataset—a corpus of read English speech from audiobooks designed for training and evaluating speech recognition systems. Mel-Frequency Cepstral Coefficients (MFCCs) were extracted as features from the audio samples to represent the power spectrum of the speakers’ voices. The models were evaluated based on precision, recall, F1-score, and accuracy to determine their performance in correctly identifying speakers. Results indicate that Logistic Regression outperformed the other models, achieving nearly perfect scores across all metrics, suggesting its superior capability for linear classification in high-dimensional spaces. Naive Bayes also demonstrated high efficiency and robustness, despite the inherent assumption of feature independence, while Gradient Boosting showed slightly lower performance, potentially due to model complexity and overfitting. The study underscores the potential of simpler machine learning models to achieve high accuracy in speaker recognition tasks, particularly where computational resources are limited. However, limitations such as the controlled nature of the dataset and the focus on a single feature type were noted, with recommendations for future research to include more diverse environmental conditions and feature sets.","PeriodicalId":440433,"journal":{"name":"Brilliance: Research of Artificial Intelligence","volume":"81 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140478739","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 : 2024-01-22DOI: 10.47709/brilliance.v3i2.3389
Muhammad Akram Hamzah, Siaulhak Siaulhak, Iriansa Iriansa, Andi Jumardi, Andryanto Aman
This research aims to develop an artificial intelligence-based chatbot as a support tool for the New Student Admission (PMB) process at Cokroaminoto University Palopo. The system development method applied is the waterfall method, which consists of analysis, design, implementation, testing, and maintenance stages. The main focus of this research is to design and implement a chatbot that is able to provide information and support to prospective new students throughout the admission process. In the analysis stage, user needs and scenarios were identified to guide the development of the chatbot. System design includes the selection of artificial intelligence algorithms and a friendly user interface. Implementation involves developing a chatbot prototype that utilizes artificial intelligence technology. The expected results can improve the efficiency and quality of new student admission services at Universitas Cokroaminoto Palopo.
{"title":"Utilization of Artificial Intelligence in Chatbot Development for New Student Admission Support at Cokroaminoto University Palopo","authors":"Muhammad Akram Hamzah, Siaulhak Siaulhak, Iriansa Iriansa, Andi Jumardi, Andryanto Aman","doi":"10.47709/brilliance.v3i2.3389","DOIUrl":"https://doi.org/10.47709/brilliance.v3i2.3389","url":null,"abstract":"This research aims to develop an artificial intelligence-based chatbot as a support tool for the New Student Admission (PMB) process at Cokroaminoto University Palopo. The system development method applied is the waterfall method, which consists of analysis, design, implementation, testing, and maintenance stages. The main focus of this research is to design and implement a chatbot that is able to provide information and support to prospective new students throughout the admission process. In the analysis stage, user needs and scenarios were identified to guide the development of the chatbot. System design includes the selection of artificial intelligence algorithms and a friendly user interface. Implementation involves developing a chatbot prototype that utilizes artificial intelligence technology. The expected results can improve the efficiency and quality of new student admission services at Universitas Cokroaminoto Palopo.","PeriodicalId":440433,"journal":{"name":"Brilliance: Research of Artificial Intelligence","volume":"285 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140500012","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}
Diabetic Retinopathy (DR) is a disease whose main cause is complications of diabetes mellitus. High levels of sugar in the blood (glucose) are caused by the pancreas' inability to produce insulin. Prevention of diabetic retinopathy and blindness by carrying out examinations at an early stage and doing them regularly. Currently, doctors still carry out examinations manually so they are prone to errors in examinations. This research aims to build an application to diagnose Diabetic Retinopathy in order to facilitate the work of the medical team and doctors at the eye clinic. In the application creation process, MATLAB is used, while feature extraction uses GLCM and for classification, SVM is used. The results of the research are that doctors and medical teams are helped in carrying out manual patient diagnoses and reduce the occurrence of human error.
{"title":"Application of the Support Vector Machine (SVM) Algorithm for the Diagnosis of Diabetic Retinopathy","authors":"Yuliadi Yuliadi, Fadhli Dzil Ikram, M. Julkarnain, Fahri Hamdan, Halid Nuryadi","doi":"10.47709/brilliance.v3i2.3436","DOIUrl":"https://doi.org/10.47709/brilliance.v3i2.3436","url":null,"abstract":"Diabetic Retinopathy (DR) is a disease whose main cause is complications of diabetes mellitus. High levels of sugar in the blood (glucose) are caused by the pancreas' inability to produce insulin. Prevention of diabetic retinopathy and blindness by carrying out examinations at an early stage and doing them regularly. Currently, doctors still carry out examinations manually so they are prone to errors in examinations. This research aims to build an application to diagnose Diabetic Retinopathy in order to facilitate the work of the medical team and doctors at the eye clinic. In the application creation process, MATLAB is used, while feature extraction uses GLCM and for classification, SVM is used. The results of the research are that doctors and medical teams are helped in carrying out manual patient diagnoses and reduce the occurrence of human error.","PeriodicalId":440433,"journal":{"name":"Brilliance: Research of Artificial Intelligence","volume":"41 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140504406","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 : 2024-01-18DOI: 10.47709/brilliance.v3i2.3434
Juniardi Akhir Putra, Halid Nuryadi, Yuliadi Yuliadi, Erwin Mardinata, C. Hudaya, Shinta Esabella, Ardiansyah Putra, Ahmad Juliansyah
This research aims to design and build a tourism system in Sumbawa Regency. In this research is using a qualitative approach that used model of rapid application development (RAD) for system development life circle (SDLC) method. Overall the first stage is system planning, next stage is analyzing tourism data and information that would be presented on web and android technology based. In addition, for users interface display is the attractive database design. The final stage is coding the system and produce a prototype for the implementation which is presenting on the web pages and google play store for android smartphones. The system presented could be used for evaluation, monitoring and facilitating of tourism transaction and promotion processes in Sumbawa Regency.
{"title":"Design and Implementation of the SALUTS System to Support of Improvement of Tourism Transactions and Promotion","authors":"Juniardi Akhir Putra, Halid Nuryadi, Yuliadi Yuliadi, Erwin Mardinata, C. Hudaya, Shinta Esabella, Ardiansyah Putra, Ahmad Juliansyah","doi":"10.47709/brilliance.v3i2.3434","DOIUrl":"https://doi.org/10.47709/brilliance.v3i2.3434","url":null,"abstract":"This research aims to design and build a tourism system in Sumbawa Regency. In this research is using a qualitative approach that used model of rapid application development (RAD) for system development life circle (SDLC) method. Overall the first stage is system planning, next stage is analyzing tourism data and information that would be presented on web and android technology based. In addition, for users interface display is the attractive database design. The final stage is coding the system and produce a prototype for the implementation which is presenting on the web pages and google play store for android smartphones. The system presented could be used for evaluation, monitoring and facilitating of tourism transaction and promotion processes in Sumbawa Regency.","PeriodicalId":440433,"journal":{"name":"Brilliance: Research of Artificial Intelligence","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140504210","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 : 2023-03-23DOI: 10.47709/brilliance.v3i1.2192
M. Khaleel
Microgrids (MG) are complex systems that integrate distributed energy resources to provide reliable and efficient power to local loads. Due to the dynamic and uncertain nature of the MG environment, intelligent control techniques have become a popular solution to ensure optimal performance. This paper provides an overview of the recent advances in intelligent control techniques applied in MG, including neural networks, model predictive control, game theory, deep reinforcement learning, and Bayesian controllers. The paper also presents a discussion of the advantages and limitations of these techniques, highlighting the challenges associated with implementing them in MG systems. Finally, investigation of the existing literature on the performance of intelligent control techniques in MG systems is presented, providing insights into their effectiveness in improving the energy efficiency, stability, and reliability of MG systems.
{"title":"Intelligent Control Techniques for Microgrid Systems","authors":"M. Khaleel","doi":"10.47709/brilliance.v3i1.2192","DOIUrl":"https://doi.org/10.47709/brilliance.v3i1.2192","url":null,"abstract":"Microgrids (MG) are complex systems that integrate distributed energy resources to provide reliable and efficient power to local loads. Due to the dynamic and uncertain nature of the MG environment, intelligent control techniques have become a popular solution to ensure optimal performance. This paper provides an overview of the recent advances in intelligent control techniques applied in MG, including neural networks, model predictive control, game theory, deep reinforcement learning, and Bayesian controllers. The paper also presents a discussion of the advantages and limitations of these techniques, highlighting the challenges associated with implementing them in MG systems. Finally, investigation of the existing literature on the performance of intelligent control techniques in MG systems is presented, providing insights into their effectiveness in improving the energy efficiency, stability, and reliability of MG systems. \u0000 ","PeriodicalId":440433,"journal":{"name":"Brilliance: Research of Artificial Intelligence","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125310310","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 : 2023-03-20DOI: 10.47709/brilliance.v3i1.2191
Bimalendu Pendy
The article discusses the increasing applications of AI in business management. In sales and marketing, AI-powered tools can help businesses understand customer needs, create personalized marketing campaigns, and improve customer engagement. AI is also revolutionizing supply chain management, improving efficiency, and agility by analyzing real-time data. Customer service is also transforming through AI-powered chatbots that handle routine queries, allowing human agents to focus on more complex issues. In financial analysis, AI provides accurate and timely insights into financial performance, risk management, and investment opportunities. The article also highlights the benefits of AI, including increased efficiency and productivity, improved accuracy and precision, and better customer experience. It also addresses some challenges of AI in business management, such as data quality and availability, skills and expertise, cost, ethics and bias, and integration with existing systems. Finally, it discusses the future potential of AI in business management, such as predictive analytics, personalized marketing, chatbots, and process automation.
{"title":"Role of AI in Business Management","authors":"Bimalendu Pendy","doi":"10.47709/brilliance.v3i1.2191","DOIUrl":"https://doi.org/10.47709/brilliance.v3i1.2191","url":null,"abstract":"The article discusses the increasing applications of AI in business management. In sales and marketing, AI-powered tools can help businesses understand customer needs, create personalized marketing campaigns, and improve customer engagement. AI is also revolutionizing supply chain management, improving efficiency, and agility by analyzing real-time data. Customer service is also transforming through AI-powered chatbots that handle routine queries, allowing human agents to focus on more complex issues. In financial analysis, AI provides accurate and timely insights into financial performance, risk management, and investment opportunities. The article also highlights the benefits of AI, including increased efficiency and productivity, improved accuracy and precision, and better customer experience. It also addresses some challenges of AI in business management, such as data quality and availability, skills and expertise, cost, ethics and bias, and integration with existing systems. Finally, it discusses the future potential of AI in business management, such as predictive analytics, personalized marketing, chatbots, and process automation.","PeriodicalId":440433,"journal":{"name":"Brilliance: Research of Artificial Intelligence","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114181325","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 : 2023-03-13DOI: 10.47709/brilliance.v3i1.2189
Khusnul Azima, Arifah Adani, H. Setiawan
At this time transportation is one of the important things in human life activities. One of the most widely used transportation is two-wheeled vehicles, especially motorcycles. According to the Ministry of Transportation (Kemenhub) reports that in 2021 the number of accidents caused by drivers who are drowsy is 2,140 incidents. This condition encouraged the author to design an anti-drowsiness helmet to reduce the number of accidents and avoid the possibility of accidents due to drowsy driving. The result of this study was that this tool can provide notification in the form of an early warning to motorbike drivers who are indicated to be drowsy by using a vibrating motor. If the head moves on the front, which is the Y axis 300°-360° and on the X axis the right side 20°-60° and on the left side 300°-335°, then the helmet will vibrate. If the Y and X axes of the helmet are in the normal position, the vibration will automatically turn off, and the helmet will return to normal.
{"title":"Early Warning System on Motorcycle Rider Helmets Using Gyrescope Sensors","authors":"Khusnul Azima, Arifah Adani, H. Setiawan","doi":"10.47709/brilliance.v3i1.2189","DOIUrl":"https://doi.org/10.47709/brilliance.v3i1.2189","url":null,"abstract":"At this time transportation is one of the important things in human life activities. One of the most widely used transportation is two-wheeled vehicles, especially motorcycles. According to the Ministry of Transportation (Kemenhub) reports that in 2021 the number of accidents caused by drivers who are drowsy is 2,140 incidents. This condition encouraged the author to design an anti-drowsiness helmet to reduce the number of accidents and avoid the possibility of accidents due to drowsy driving. The result of this study was that this tool can provide notification in the form of an early warning to motorbike drivers who are indicated to be drowsy by using a vibrating motor. If the head moves on the front, which is the Y axis 300°-360° and on the X axis the right side 20°-60° and on the left side 300°-335°, then the helmet will vibrate. If the Y and X axes of the helmet are in the normal position, the vibration will automatically turn off, and the helmet will return to normal.","PeriodicalId":440433,"journal":{"name":"Brilliance: Research of Artificial Intelligence","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121791145","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 : 2023-03-13DOI: 10.47709/brilliance.v3i1.2170
M. Khaleel, A. Ahmed, Abdulgader Alsharif
Artificial intelligence (AI) has moved past its primitive stages and is now poised to revolutionize various fields, making it a disruptive technology. This technology is expected to completely transform traditional engineering in design, electrical, communication, and renewable energy approaches that have been human-centred. Despite being in its early stages, AI-powered engineering applications can work with vague design parameters and resolve intricate engineering problems that cannot be tackled using traditional design, electrical, communication, and renewable energy methods. This article aims to shed light on the current progress and future research trends in AI applications in engineering concepts, focusing on the ramp-up period of the last 5 years. Various methods such as machine learning, genetic algorithm, and fuzzy logic have been carefully evaluated from an engineering standpoint. AI-powered design studies have been reviewed and categorized for different design stages such as inspiration, idea and concept generation, evaluation, optimization, decision-making, and modeling. The review shows that there has been an increased interest in data-based design methods and explainable artificial intelligence in recent years. The use of AI methods in engineering applications has proven to be efficient, fast, accurate, and comprehensive, particularly with the use of deep learning methods and combinations that address situations where human capacity is inadequate. However, it is crucial to choose the appropriate AI method for an engineering problem to achieve successful results.
{"title":"Artificial Intelligence in Engineering","authors":"M. Khaleel, A. Ahmed, Abdulgader Alsharif","doi":"10.47709/brilliance.v3i1.2170","DOIUrl":"https://doi.org/10.47709/brilliance.v3i1.2170","url":null,"abstract":"Artificial intelligence (AI) has moved past its primitive stages and is now poised to revolutionize various fields, making it a disruptive technology. This technology is expected to completely transform traditional engineering in design, electrical, communication, and renewable energy approaches that have been human-centred. Despite being in its early stages, AI-powered engineering applications can work with vague design parameters and resolve intricate engineering problems that cannot be tackled using traditional design, electrical, communication, and renewable energy methods. This article aims to shed light on the current progress and future research trends in AI applications in engineering concepts, focusing on the ramp-up period of the last 5 years. Various methods such as machine learning, genetic algorithm, and fuzzy logic have been carefully evaluated from an engineering standpoint. AI-powered design studies have been reviewed and categorized for different design stages such as inspiration, idea and concept generation, evaluation, optimization, decision-making, and modeling. The review shows that there has been an increased interest in data-based design methods and explainable artificial intelligence in recent years. The use of AI methods in engineering applications has proven to be efficient, fast, accurate, and comprehensive, particularly with the use of deep learning methods and combinations that address situations where human capacity is inadequate. However, it is crucial to choose the appropriate AI method for an engineering problem to achieve successful results. \u0000 ","PeriodicalId":440433,"journal":{"name":"Brilliance: Research of Artificial Intelligence","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115893209","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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