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Farming is important because it plays a vital role in the economy of our country. For better crop production, choosing a suitable crop is very important. This can be decided based on many factors, such as soil type, temperature, water availability, market rate of the crop, crop storage capabilities, etc. The soil minerals play a vital role in finding suitable crops for cultivation. At present, sensors, drones, cameras, Wi-Fi, GPS, and many other advanced tools have been implemented for smart irrigation. All these are not affordable for common farmers, and many times they need technical experts. A model has been proposed that implements a few low-cost sensors to collect the soil minerals periodically and stores them in a low-cost cloud memory. Further, by implementing suitable machine learning and deep learning methods, the suitable crops are listed out. A smart phone application can be used to interact with cloud memory and analyse the data using learning methods. Furthermore, the same data can be used on a regular basis to determine soil mineral deficiency. A keen focus has been given to balancing the cost and expertise of implementing this model. [ABSTRACT FROM AUTHOR]