IoT based hydroponics system using Deep Neural Networks
| Autor: | Sameer Saxena, M Veeramanikandan, Rijo Jackson Tom, Suresh Sankaranarayanan, Manav Mehra |
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| Rok vydání: | 2018 |
| Předmět: |
Aeroponics
Artificial neural network business.industry Computer science 010401 analytical chemistry Bayesian network Forestry Control engineering 04 agricultural and veterinary sciences Horticulture Hydroponics 01 natural sciences 0104 chemical sciences Computer Science Applications Machine to machine Arduino 040103 agronomy & agriculture 0401 agriculture forestry and fisheries Deep neural networks Internet of Things business Agronomy and Crop Science |
| Zdroj: | Computers and Electronics in Agriculture. 155:473-486 |
| ISSN: | 0168-1699 |
| DOI: | 10.1016/j.compag.2018.10.015 |
| Popis: | Agriculture has the significant impact on the economy of the country. With the practice of modern farming techniques where plants can be grown without the need of soil by means of nutrient solution, Hydroponics and Aeroponics are in the rise. Now towards controlling the hydroponic plant growth, some amount of research has been done in applying machine learning algorithms like Neural Networks and Bayesian network. Internet of Things allows for Machine to Machine interaction and controlling the hydroponic system autonomously and intelligently. This work proposes to develop an intelligent IoT based hydroponic system by employing Deep Neural Networks which is first of its kind. The system so developed is intelligent enough in providing the appropriate control action for the hydroponic environment based on the multiple input parameters gathered. A prototype for Tomato plant growth as a case study was developed using Arduino, Raspberry Pi3 and Tensor Flow. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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