earticle

논문검색

Environmental Information Technology (EIT)

Data-Based Monitoring System for Smart Kitchen Farm

초록

영어

Pandemic situations such as COVID-19 can occur supply chain crisis. Under the supply chain crisis, delivering farm products from the farm to the city is also very challenging. Therefore it is essential to prepare food sufficiency people who live in a city. We firmly insist on food self-production/consumption systems in each home. However, since it is impossible to grow high-quality crops without expertise knowledge. Therefore expert system is essential to grow high-quality crops in home. To address this problem, we propose a smart kitchen farm as a data-based monitoring system and platform with ICT convergence technology. Our proposed approach 1) collects data and makes judgments based on expert knowledge for home users, 2) increases product quality of the smart kitchen farms by predicting abnormal/normal crops, and 3) controls each personal home cultivation environment through data-based monitoring within the smart central server. We expect people can cultivate high-quality crops in thir kitchens through this system without expert knowledge about cultivation.

목차

Abstract
1. Introduction
2. Related Works
2.1 Heterogeneous Smart Farm Data Collection Based on Model Transformation Techniques
2.2 Convolutional Neural Network (CNN)
2.3 Hydroponics
3. Our Data-Based Monitoring System for the Smart Kitchen Farm
3.1 Overall System Structure
3.2 Deep Learning-Based Abnormal/Normal Crop Learning Method
4. A DATA-BASED MONITORING SYSTEM FOR HOME SMART FARMS
5. RESULTS
6. CONCLUSION

저자정보

  • Ye Dong Yoon M.S, Department of Software and Communication Engineering, Hongik University, Korea
  • Woo Sung Jang Dr, Department of Software and Communication Engineering, Hongik University, Korea
  • So Young Moon Post Dr, Department of Software and Communication Engineering, Hongik University, Korea
  • R. Young Chul Kim Professor, Department of Software and Communication Engineering, Hongik University, Korea

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