My interest and research led me to the data which revealed that to reduce overutilization of natural resources, a large number of greenhouses are turning to automation globally, to meet the growing demand for food.

 

However as the cost of automation is extremely high, in a developing country like India, farmers are not able to afford fully automated farms. Also cheap labour encourages farmers to undertake certain work manually. 

 

Most greenhouses are successfully not able to optimize production because they use manual interventions to control parameters like temperature and humidity. Also, the data could be more predictive hence call to action is sometimes delayed, affecting productivity.

 

I would like to deepen my research and develop a system that could monitor and predict the internal environment of naturally ventilated greenhouses and successfully predict when the vent should be opened and closed so that optimal temperature is maintained at all times, leading to optimization in production.

 

I have gathered data during my summer break at my parent’s farm.  As the data involves continuous variables like temperature and humidity, I plan to use linear regression or polynomial regression to understand the relationship between dependent and independent variables.