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Design and Modeling of an IOT Based Transformer Health Monitoring System

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dc.contributor.author Shuvo, Md. Shoriful Islam
dc.contributor.author Paul, Partho Protim
dc.date.accessioned 2026-06-25T04:48:39Z
dc.date.available 2026-06-25T04:48:39Z
dc.date.issued 2025-01-06
dc.identifier.citation EEE en_US
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/17514
dc.description Project Report en_US
dc.description.abstract The paper focuses on Design and Modeling of an IOT-based Transformer Health Monitoring System designed to improve transformer reliability and lifespan byenabling real-time monitoring and predictive maintenance. Transformers, essential to power systems, are prone to failures that can cause costly repairs and service disruptions. Traditional manual or basic automated monitoring methods often fail to provide timely insights.This system integrates sensors to measure parameters like temperature, humidity, load current, oil level, and voltage, with data transmitted to a cloud-based platform. Using IOT technology, data analytics, and machine learning, it detects abnormalities and predicts faults, allowing operators to take preventive actions. Alerts and reports are accessible via web or mobile apps, enabling quick responses. The system reduces maintenance costs, extends transformer life, and enhances grid stability, making it vital for advancing smart grid infrastructure and energy management efficiency. en_US
dc.description.sponsorship DIU en_US
dc.language.iso en_US en_US
dc.publisher Daffodil International University en_US
dc.subject Sensor-based Diagnostics en_US
dc.subject Internet of Things (IoT) en_US
dc.subject Transformer Condition en_US
dc.subject Monitoring Predictive Maintenance en_US
dc.title Design and Modeling of an IOT Based Transformer Health Monitoring System en_US
dc.type Other en_US


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