REAL-TIME PEST DETECTION AND FUMIGATION USING MACHINE LEARNING

Abstract

Pakistan generates 70% economy from agricultural sector. It is the largest growing sector in Pakistan. It contributes 24% to the GDP. The geographical location and environmental conditions of Pakistan are suitable for the growth of most of the crops. Every crop requires different climatic condition to grow. Crops such as rice, cotton , vegetables and fruits are mainly exported to Europe and other countries. These countries face harsh climate which does not satisfy the necessary climatic conditions required for several crops and therefore these countries export these crops from countries like Pakistan due to its excellent crop quality , production and growth rate. The crop demand is directly dependant on the crop quality which is a major factor that must not be compromised. Providing the necessary conditions to grow and protecting from any diseases is the major goal that needs to be achieved. These crops are prone to get affected by any diseases that can be caused by different pests. Pests largely compromise the crop quality and destroy several crops which affects the economy. Therefore a pesticide needs to be used in order to get rid of any pests present on the crops that might compromise the crop quality. Large amounts of plants may contain several pests of different sizes and colors which may not be visible to human eye. Therefore, we have designed a robotic arm that can move around the crop field and effectively scan the plants for the presence of any pests on the crops and spraying pesticide to get rid ofthem. The pesticide used will get rid of these pests without causing any harm to the nature as it is environmental friendly. Using Innovative technology we will try to reduce wastage of crops, improve crop quality and reducing poverty. This will reduce labour work and promote increased p demand resulting in good impact on the economy