DOIONLINE 
DOIONLINE Publish In |
International Journal of Advances in Electronics and Computer Science-IJAECS |
 Journal Home Volume Issue |
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Issue |
Volume-9,Issue-12 ( Dec, 2022 ) | |||||||||
Paper Title |
A Framework for IoT Fault Diagnosis using Scaled Grid Off loading Model | |||||||||
Author Name |
Si Woo Byun | |||||||||
Affilition |
Software Department, Anyang University, Korea | |||||||||
Pages |
61-64 | |||||||||
Abstract |
Abstract - IoT fault diagnosis is becoming more difficult as tiny sensor devices become more complex and vast amounts of sensor data are generated continuously. Therefore, it is important to eliminate worthless sensor data in advance. To efficiently reduce the amount of sensor data, we present a four-layer offloading model and propose a scaled grid pattern matching skill using multiple sensor contexts from individual sensors. Since sensor data that is highly likely to be a clue of the expected fault is transmitted, proposed model can achieve superior offloading performance. Keywords - Fault Diagnosis, Sensor Context, Pattern Matching, Off Loading Model | |||||||||
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