The increasing demand for food supply in India is a major problem with respect to the production of crops. According to FAO, more than 40 percent of the crop grown is wasted in India. There are several reasons leading to this huge wastage. One of the major reasons is withered crops due to an unsustainable environment. Many technologies are evolving these days and with the help of those, we can minimize wastage. This paper includes an experimental analysis in a cloud-based smart sensor-controlled environment that can increase crop growth. IoT devices were used to measure different environmental parameters like temperature, humidity, moisture, NPK values, etc. via sensors, and the data collected was stored in the cloud. LightGBM, one of the popular machine learning algorithms was used for the analysis and prediction. This algorithm is based on the gradient boosting technique and is very accurate with its results. The model architecture which was trained gave an accuracy of 99.38 percent. The high accuracy rate of the model makes it most effective to use it in real-life applications. The further expansion of this idea can help a lot of farmers to understand and plan according to environmental conditions.