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Please use this identifier to cite or link to this item: https://epub.vgu.edu.vn/handle/dlibvgu/1874
DC FieldValueLanguage
dc.contributor.authorTran Huu Phucen_US
dc.date.accessioned2024-11-15T06:52:47Z-
dc.date.available2024-11-15T06:52:47Z-
dc.date.issued2024-
dc.identifier.urihttps://epub.vgu.edu.vn/handle/dlibvgu/1874-
dc.description.abstractThe amalgamation of artificial intelligence (AI) with Internet of Things (IoT) offers substantial prospects for predictive maintenance across diverse applications, empowering systems to self-monitor, evaluate, and react to environmental data instantaneously. This research investigates the creation of intelligent software intende to handle, track, and identify irregularities in Internet of Things (IoT) sensor data by applying a Convolutional Neural Network (CNN) model. The system is structured around four main modules: Data Preparation and Processing, Training, Prediction, and a Mobile App interface. Data from multiple sensors is processed and used to train a CNN model, which then predicts future values and identifies any deviations that could indicate potential issues. The Mobile App displays these insights in a user-friendly manner, providing real-time alerts for any detected anomalies. Despite challenges such as the need for extensive training data and the complexity of developing cross-platform applications, the project demonstrates the potential of combining IoT and AI for predictive maintenance. Future enhancements could further refine the system's accuracy, speed, and user experience, making it a valuable tool in various industrial and domestic settings.en_US
dc.language.isoenen_US
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectIOT applicationsen_US
dc.subjectAI modelen_US
dc.titleAnomaly detection in predictive maintenance for internet of things applicationsen_US
dc.typeThesisen_US
item.fulltextWith Fulltext-
item.languageiso639-1other-
item.grantfulltextrestricted-
Appears in Collections:Computer Science (CS)
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