International journal of advanced smart convergence

The Institute of Internet, Broadcasting and Communication (한국인터넷방송통신학회)
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Temperature Trend Predictive IoT Sensor Design for Precise Industrial Automation

  • Li, Vadim (Graduate School of Nano IT Design Fusion, Seoul National University of Science and Technology) ;
  • Mariappan, Vinayagam (Dept. Integrated IT Engineering, Seoul National University of Science and Technology)
  • Received : 2018.09.26
  • Accepted : 2018.10.08
  • Published : 2018.12.31
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Abstract

Predictive IoT Sensor Algorithm is a technique of data science that helps computers learn from existing data to predict future behaviors, outcomes, and trends. This algorithm is a cloud predictive analytics service that makes it possible to quickly create and deploy predictive models as analytics solutions. Sensors and computers collect and analyze data. Using the time series prediction algorithm helps to predict future temperature. The application of this IoT in industrial environments like power plants and factories will allow organizations to process much larger data sets much faster and precisely. This rich source of sensor data can be networked, gathered and analyzed by super smart software which will help to detect problems, work more productively. Using predictive IoT technology - sensors and real-time monitoring - can help organizations exactly where and when equipment needs to be adjusted, replaced or how to act in a given situation.

Keywords

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Figure 1. IoT System Usage Model

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Figure 3. System Implementation

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Figure 4. Time Series Prediction Algorithm

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Figure 5. Diagram of Time Series Prediction

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Figure 6. IoT Sensor Based Environment Temperature Trend

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Figure 7. Training Trend Graph

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Figure 8. Real Time Prediction and Trending Window

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Figure 2. Block Diagram

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