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Green House based on Artificial intelligence

Green House Based on AI

Price : 8000

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Course Duration
Approx 10

Course Price
₹ 8000

Course Level
Moderate

Course Content

The area of greenhouse production is increasing with the rapid growth of global population and demands for fresh food. However, the greenhouse industry encounters challenges to find automatic control policy. Green house environment monitoring technology has continuously improved, and good greenhouse environment can improve crop quality, short the growth cycle and increase production, which have very important theoretical significance and value for study. Reinforcement Learning (RL) is a powerful tool in solving the autonomous decision making problems. We propose a novel Deep Reinforcement Learning framework for a crop climate control. Although some machine learning methods have been proposed to address the dynamic climate control problem, these methods have two major issues. First, they only consider the current reward .Second, previous study only considers one control variable. However, the growth of crops are impacted by multiple factors synchronously (e.g., CO2 and Temperature).To solve these challenges, we propose a Deep Reinforcement learning based climate control method, which can model future reward explicitly.

Green House

METHODOLOGY 

 

1.     Collects all the sensors data using controller.

2.     Water pump is controlled by controller using relay.

3.     Monitor all the data in cloud through wifi.

4.     Analyzing the sensor data using various machine learning algorithms.

5.     Finalizing the ML model which gives the better accuracy.

Green house is a kind of place which can change plant growth environment; create the best conditions for plant growth, and keep off influence on plant growth due to outside changing seasons and severe weather. For greenhouse measurement and control system, in order to in step-up crop yield, improve quality, regulate the growth period and improve the economic efficiency, the good condition of crop growth is obtained on the basis of taking full use of natural resources by changing green house environment factors such as temperature, humidity and Co2 concentration. Continuous monitoring and control of these climate factors will allow for maximum crop yield. This can be done with our propose model using deep learning techniques.

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