Pub Date : 2023-02-20DOI: 10.1109/ICAIIC57133.2023.10066975
Daeyoung Kang, Seunghyun Yoon, Hyuk-Soon Lim
In recent years, stability issues of power grids have become critical with the rapid increase in power consumption. Demand response (DR) is a policy that incentivizes consumers to reduce their power usage so that electricity demand does not exceed the supply of a power grid to prevent the power grid's instability. We propose a Deep Q-Network (DQN)-based building energy management system that reduces the amount of electricity supplied by electric power companies by utilizing the surplus power of electric vehicles (EVs) upon DR requests. The proposed scheme considers the DR incentives and penalties as well as the cost of buying energy from EVs. In addition, the amount of time used for discharging EVs is also taken into consideration in DQN's reward function. We perform the simulations to compare the proposed scheme with a random selection scheme and a greedy scheme to recruit the nearest EVs until the DR request is fulfilled. The simulation result indicates that the proposed scheme succeeds to balance the building cost and the EV waiting time performance at the EV stations.
{"title":"Deep Reinforcement Learning-based Building Energy Management using Electric Vehicles for Demand Response","authors":"Daeyoung Kang, Seunghyun Yoon, Hyuk-Soon Lim","doi":"10.1109/ICAIIC57133.2023.10066975","DOIUrl":"https://doi.org/10.1109/ICAIIC57133.2023.10066975","url":null,"abstract":"In recent years, stability issues of power grids have become critical with the rapid increase in power consumption. Demand response (DR) is a policy that incentivizes consumers to reduce their power usage so that electricity demand does not exceed the supply of a power grid to prevent the power grid's instability. We propose a Deep Q-Network (DQN)-based building energy management system that reduces the amount of electricity supplied by electric power companies by utilizing the surplus power of electric vehicles (EVs) upon DR requests. The proposed scheme considers the DR incentives and penalties as well as the cost of buying energy from EVs. In addition, the amount of time used for discharging EVs is also taken into consideration in DQN's reward function. We perform the simulations to compare the proposed scheme with a random selection scheme and a greedy scheme to recruit the nearest EVs until the DR request is fulfilled. The simulation result indicates that the proposed scheme succeeds to balance the building cost and the EV waiting time performance at the EV stations.","PeriodicalId":105769,"journal":{"name":"2023 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125926953","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 : 2023-02-20DOI: 10.1109/ICAIIC57133.2023.10066993
Mouna Lamine, Sang-Chul Kim
Machine Learning is facing rapid development due to the almost unlimited amount of data available, and it is widely applied in diverse areas. Optimization is one of the core components in the machine learning which attracted more researcher's attention to it. In recent years there has been a great deal of work on improving optimisation methods in machine learning. In this paper we will introduce the Adaptive Gradient(Adapg), a new extension in the adaptive learning family Optimization algorithm.
{"title":"Introduction of Optimization Algorithm for Adaptive Gradient","authors":"Mouna Lamine, Sang-Chul Kim","doi":"10.1109/ICAIIC57133.2023.10066993","DOIUrl":"https://doi.org/10.1109/ICAIIC57133.2023.10066993","url":null,"abstract":"Machine Learning is facing rapid development due to the almost unlimited amount of data available, and it is widely applied in diverse areas. Optimization is one of the core components in the machine learning which attracted more researcher's attention to it. In recent years there has been a great deal of work on improving optimisation methods in machine learning. In this paper we will introduce the Adaptive Gradient(Adapg), a new extension in the adaptive learning family Optimization algorithm.","PeriodicalId":105769,"journal":{"name":"2023 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124865403","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 : 2023-02-20DOI: 10.1109/ICAIIC57133.2023.10067017
Elhaam Abdulrahman Debas, R. Alajlan, Mohammad Sohel Rahman
Our lives totally depend on computers and mobile devices. Nowadays, we see a massive development in the digital world that makes it easy to stay in touch with friends and family and even work remotely. The growth led to losses and distress caused by cyber-attacks, which attempt to harm by unauthorized access. Cybersecurity is a major issue in our digital world, while cybercrime is increasing. The banking and finance sectors have started to rely on biometric security systems for their apps and services. Biometric identification uses unique human characteristics to authenticate a person's identity, such as voice/speech recognition, fingerprint recognition, facial recognition, iris recognition, signature dynamics, etc. Biometric technology is used in banking, e-commerce, account login, access control, etc, which can be considered a valuable measure against cybercrime. Biometrics is a key to the future of cybersecurity and safeguards against cybercrime.
{"title":"Biometric in Cyber Security: A Mini Review","authors":"Elhaam Abdulrahman Debas, R. Alajlan, Mohammad Sohel Rahman","doi":"10.1109/ICAIIC57133.2023.10067017","DOIUrl":"https://doi.org/10.1109/ICAIIC57133.2023.10067017","url":null,"abstract":"Our lives totally depend on computers and mobile devices. Nowadays, we see a massive development in the digital world that makes it easy to stay in touch with friends and family and even work remotely. The growth led to losses and distress caused by cyber-attacks, which attempt to harm by unauthorized access. Cybersecurity is a major issue in our digital world, while cybercrime is increasing. The banking and finance sectors have started to rely on biometric security systems for their apps and services. Biometric identification uses unique human characteristics to authenticate a person's identity, such as voice/speech recognition, fingerprint recognition, facial recognition, iris recognition, signature dynamics, etc. Biometric technology is used in banking, e-commerce, account login, access control, etc, which can be considered a valuable measure against cybercrime. Biometrics is a key to the future of cybersecurity and safeguards against cybercrime.","PeriodicalId":105769,"journal":{"name":"2023 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130602572","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 : 2023-02-20DOI: 10.1109/ICAIIC57133.2023.10066989
Quota Alief Sias, Sol Lim, Rahma Gantassi, Yonghoon Choi
This paper describes the implementation of artificial intelligence (AI) using single linear regression (SLR) and multiple linear regression (MLR) methods to predict daily energy needs. SLR implementation is applied using one input variable that is the total energy produced. MLR implementation is applied with more than one input variable, which is taken from detailed energy production data from various energy sources such as gas, coal, geothermal, water, wind, biomass, oil, etc. This paper shows that energy demand prediction can be obtained by analyzing energy production data from previous time. MLR implementation shows better performance because it can get a smaller error value than SLR implementation. This paper explains that energy demand and supply can be analyzed directly together to produce a more comprehensive analysis.
{"title":"Implementation of Single and Multi Linear Regression for Prediction of Energy Consumption based on Previous Data of Energy Production","authors":"Quota Alief Sias, Sol Lim, Rahma Gantassi, Yonghoon Choi","doi":"10.1109/ICAIIC57133.2023.10066989","DOIUrl":"https://doi.org/10.1109/ICAIIC57133.2023.10066989","url":null,"abstract":"This paper describes the implementation of artificial intelligence (AI) using single linear regression (SLR) and multiple linear regression (MLR) methods to predict daily energy needs. SLR implementation is applied using one input variable that is the total energy produced. MLR implementation is applied with more than one input variable, which is taken from detailed energy production data from various energy sources such as gas, coal, geothermal, water, wind, biomass, oil, etc. This paper shows that energy demand prediction can be obtained by analyzing energy production data from previous time. MLR implementation shows better performance because it can get a smaller error value than SLR implementation. This paper explains that energy demand and supply can be analyzed directly together to produce a more comprehensive analysis.","PeriodicalId":105769,"journal":{"name":"2023 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130651509","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 : 2023-02-20DOI: 10.1109/ICAIIC57133.2023.10067046
Ji Yeon Kim, Young-Jin Kang, Sanghyun Ha, Seok Chan Jeong
In this paper, we propose a visualization technique to develop an algorithm for optimizing the cargo arrangement of a vehicle carrier. The vehicle carrier has a complex structure in which the cargo hold space is different because the position of the lamp and other facilities is different for each deck. A visualization method was proposed through CMD-based numerical calculation to output the drawing results of an optimized layout plan for a complex structure. To express the coordinates of the facilities in the deck in dot format, an array was created by assigning numbers. After determining the loadable space, the visualization was completed by defining symbols to distinguish each component.
{"title":"Visualization Algorithm for Cargo Stowage Optimization of Vehicle Carriers","authors":"Ji Yeon Kim, Young-Jin Kang, Sanghyun Ha, Seok Chan Jeong","doi":"10.1109/ICAIIC57133.2023.10067046","DOIUrl":"https://doi.org/10.1109/ICAIIC57133.2023.10067046","url":null,"abstract":"In this paper, we propose a visualization technique to develop an algorithm for optimizing the cargo arrangement of a vehicle carrier. The vehicle carrier has a complex structure in which the cargo hold space is different because the position of the lamp and other facilities is different for each deck. A visualization method was proposed through CMD-based numerical calculation to output the drawing results of an optimized layout plan for a complex structure. To express the coordinates of the facilities in the deck in dot format, an array was created by assigning numbers. After determining the loadable space, the visualization was completed by defining symbols to distinguish each component.","PeriodicalId":105769,"journal":{"name":"2023 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132095168","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 : 2023-02-20DOI: 10.1109/ICAIIC57133.2023.10066982
N. Pah, V. Indrawati, D. Kumar
Parkinson'$s$ disease (PD) is one of the most common neurodegenerative disorders. PD has been the fastest growth in prevalence, and it has become the leading cause of disability. The severity or progression of PD can be reduced if diagnosed at the early stages. It is therefore necessary to develop rapid and simple screening methods or tools to diagnose PD. Speech impairment is one of the early symptoms of PD which is commonly termed Parkinsonian hypokinetic dysarthria. Many researchers have developed a computerized method to identify of diagnosing PD based on voice features. However, the inaccuracy of the developed models was inconsistent especially when being tested on different datasets. The possible cause is the unwanted variability and biases between datasets. This study investigates the possible inconsistencies between Parkinson's voice datasets. The inconsistencies were investigated in the statistical distribution of voice parameters of the healthy-control (HC) group. This work observes the statistical distribution of sustained phoneme parameters extracted from the healthy-control (HC) group of five datasets using ANOVA and the Post-Hoc Turkey-Cramer test. The result suggests that the diversity in language and ethnicity were not contributing significantly to any biases between databases. The other result confirms that noises in the recording contribute to the biases in the extracted voice features, especially the harmonic features
{"title":"Cross-Corpus Disparity of Parkinson's Voice Datasets Observed on Control Group Distribution","authors":"N. Pah, V. Indrawati, D. Kumar","doi":"10.1109/ICAIIC57133.2023.10066982","DOIUrl":"https://doi.org/10.1109/ICAIIC57133.2023.10066982","url":null,"abstract":"Parkinson'$s$ disease (PD) is one of the most common neurodegenerative disorders. PD has been the fastest growth in prevalence, and it has become the leading cause of disability. The severity or progression of PD can be reduced if diagnosed at the early stages. It is therefore necessary to develop rapid and simple screening methods or tools to diagnose PD. Speech impairment is one of the early symptoms of PD which is commonly termed Parkinsonian hypokinetic dysarthria. Many researchers have developed a computerized method to identify of diagnosing PD based on voice features. However, the inaccuracy of the developed models was inconsistent especially when being tested on different datasets. The possible cause is the unwanted variability and biases between datasets. This study investigates the possible inconsistencies between Parkinson's voice datasets. The inconsistencies were investigated in the statistical distribution of voice parameters of the healthy-control (HC) group. This work observes the statistical distribution of sustained phoneme parameters extracted from the healthy-control (HC) group of five datasets using ANOVA and the Post-Hoc Turkey-Cramer test. The result suggests that the diversity in language and ethnicity were not contributing significantly to any biases between databases. The other result confirms that noises in the recording contribute to the biases in the extracted voice features, especially the harmonic features","PeriodicalId":105769,"journal":{"name":"2023 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126462641","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 : 2023-02-20DOI: 10.1109/ICAIIC57133.2023.10067120
Mahmoud Hamido, Abdallah Mohialdin, Ayman Atia
Document manipulation is a recently arising problem, especially with the rapid spread of fabrication technology. The tools to alter documents are now publicly available and can result in high quality forgeries, indistinguishable from genuine ones. Forged documents may wreak havoc on many processes dependent on the validity of the document, leading to lasting consequences such as financial loss. Therefore, the process of identifying a document that has been altered is essential. A system that is capable of scrutinizing documents as either forged or genuine through discriminative features (such as distortions or character misalignment) can assist industries with heavily reliance on documents for processes such as identity verification. Most of the documents involved in such processes have sufficiently complex backgrounds. We present a computer-vision-based system that detects changes in the background of the aforementioned documents as a result of manipulations made to its contents through the use of image subtraction. The system takes an image as input and then classifies the document as genuine or forged. Our proposed system produces an accuracy of 95% using CNN on unaligned images as well as 100% for aligned images.
{"title":"The Use of Background Features, Template Synthesis and Deep Neural Networks in Document Forgery Detection","authors":"Mahmoud Hamido, Abdallah Mohialdin, Ayman Atia","doi":"10.1109/ICAIIC57133.2023.10067120","DOIUrl":"https://doi.org/10.1109/ICAIIC57133.2023.10067120","url":null,"abstract":"Document manipulation is a recently arising problem, especially with the rapid spread of fabrication technology. The tools to alter documents are now publicly available and can result in high quality forgeries, indistinguishable from genuine ones. Forged documents may wreak havoc on many processes dependent on the validity of the document, leading to lasting consequences such as financial loss. Therefore, the process of identifying a document that has been altered is essential. A system that is capable of scrutinizing documents as either forged or genuine through discriminative features (such as distortions or character misalignment) can assist industries with heavily reliance on documents for processes such as identity verification. Most of the documents involved in such processes have sufficiently complex backgrounds. We present a computer-vision-based system that detects changes in the background of the aforementioned documents as a result of manipulations made to its contents through the use of image subtraction. The system takes an image as input and then classifies the document as genuine or forged. Our proposed system produces an accuracy of 95% using CNN on unaligned images as well as 100% for aligned images.","PeriodicalId":105769,"journal":{"name":"2023 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122713442","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}
Generation Z interest of Indonesian culture especially folktale keep decreasing. This research is trying to increase the interest of generation $mathbf{Z}$ to folktale by adapting it into game. This research use Unity engine for its development based on one of Indonesian folktale Timun Mas. The creation of game application that tell the story of Timun Mas are successfully made and can be used as medium to increase interest of Generation Z in Indonesian Folklore. Based on survey that has been done, folklore adaptation in form of game is more is more efficient in increasing interest of Generation Z to Indonesian Folklore more than Folklore in form of Text although not significant.
{"title":"Development of Timun Mas Game Platformer for Increasing Generation Z Interest to Indonesian Folklore","authors":"Andru Baskara Putra, Alief Kukuh Nurkusuma, Gregorious Juan Khawarga, Meiliana, Muhamad Fajar","doi":"10.1109/ICAIIC57133.2023.10067133","DOIUrl":"https://doi.org/10.1109/ICAIIC57133.2023.10067133","url":null,"abstract":"Generation Z interest of Indonesian culture especially folktale keep decreasing. This research is trying to increase the interest of generation $mathbf{Z}$ to folktale by adapting it into game. This research use Unity engine for its development based on one of Indonesian folktale Timun Mas. The creation of game application that tell the story of Timun Mas are successfully made and can be used as medium to increase interest of Generation Z in Indonesian Folklore. Based on survey that has been done, folklore adaptation in form of game is more is more efficient in increasing interest of Generation Z to Indonesian Folklore more than Folklore in form of Text although not significant.","PeriodicalId":105769,"journal":{"name":"2023 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128003136","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 : 2023-02-20DOI: 10.1109/ICAIIC57133.2023.10067004
Jihye Kim, Jaehyoung Park, Jong-Hyouk Lee
Recently, the manufacturing industry is changing into a smart manufacturing era with the development of 5G, artificial intelligence, and cloud computing technologies. As a result, Operational Technology (OT), which controls and operates factories, has been digitized and used together with Information Technology (IT). Security is indispensable in the smart manu-facturing industry as a problem with equipment, facilities, and operations in charge of manufacturing can cause factory shutdown or damage. In particular, security is required in smart factories because they implement automation in the manufacturing industry by monitoring the surrounding environment and collecting meaningful information through Industrial IoT (IIoT). Therefore, in this paper, IIoT security proposed in 2022 and recent technology trends are analyzed and explained in order to understand the current status of IIoT security technology in a smart factory environment.
{"title":"Analysis of Recent IIoT Security Technology Trends in a Smart Factory Environment","authors":"Jihye Kim, Jaehyoung Park, Jong-Hyouk Lee","doi":"10.1109/ICAIIC57133.2023.10067004","DOIUrl":"https://doi.org/10.1109/ICAIIC57133.2023.10067004","url":null,"abstract":"Recently, the manufacturing industry is changing into a smart manufacturing era with the development of 5G, artificial intelligence, and cloud computing technologies. As a result, Operational Technology (OT), which controls and operates factories, has been digitized and used together with Information Technology (IT). Security is indispensable in the smart manu-facturing industry as a problem with equipment, facilities, and operations in charge of manufacturing can cause factory shutdown or damage. In particular, security is required in smart factories because they implement automation in the manufacturing industry by monitoring the surrounding environment and collecting meaningful information through Industrial IoT (IIoT). Therefore, in this paper, IIoT security proposed in 2022 and recent technology trends are analyzed and explained in order to understand the current status of IIoT security technology in a smart factory environment.","PeriodicalId":105769,"journal":{"name":"2023 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133681511","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 : 2023-02-20DOI: 10.1109/ICAIIC57133.2023.10066971
Junhyung Jo, Zeu Kim, Y. Suh
The belt conveyor system is widely used in production and distribution industries because it is more cost-effective than manpower and can be used in a variety of ways. Prognostics of the belt conveyor system is the main activity to maintain efficiency. Lack of performance of the system is most often an error in which the system is no longer available to meet the desired performance which arises the entire system can be damaged and fatal industrial accidents may occur. In this paper, we present a model that predicts the remaining useful life of the head pulley, a key part of the belt conveyor system. The ensemble learning-based model to predict is composed of a deep learning-based representation model and boosting model. The model is trained using a combination of classification and regression rather than simple regression to predict the remaining useful life. The data used to train the model was collected by directly building a test bed with an environment similar to a belt conveyor system.
{"title":"Remaining Useful Life Prediction Using an Ensemble Learning-Based Network for a Belt Conveyor System","authors":"Junhyung Jo, Zeu Kim, Y. Suh","doi":"10.1109/ICAIIC57133.2023.10066971","DOIUrl":"https://doi.org/10.1109/ICAIIC57133.2023.10066971","url":null,"abstract":"The belt conveyor system is widely used in production and distribution industries because it is more cost-effective than manpower and can be used in a variety of ways. Prognostics of the belt conveyor system is the main activity to maintain efficiency. Lack of performance of the system is most often an error in which the system is no longer available to meet the desired performance which arises the entire system can be damaged and fatal industrial accidents may occur. In this paper, we present a model that predicts the remaining useful life of the head pulley, a key part of the belt conveyor system. The ensemble learning-based model to predict is composed of a deep learning-based representation model and boosting model. The model is trained using a combination of classification and regression rather than simple regression to predict the remaining useful life. The data used to train the model was collected by directly building a test bed with an environment similar to a belt conveyor system.","PeriodicalId":105769,"journal":{"name":"2023 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131787728","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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