The world is facing a global challenge for abusing drug which is basically extracted from the cultivation of the opium poppy. On the other hand, drugs extracted from opium cultivation are used in medicine for life-saving purposes. It becomes crucial to understand the cultivation of opium poppy in remote areas and identify the cause of cultivation. It also becomes crucial to monitor every instance of cultivation and verify the cause. The challenges also occurred in finding the opium poppy cultivation among several other cultivations and giving accurate results to the authority. Here in the proposed system, it leverages the use of deep learning models for object detection, specifically the YOLO algorithm initially, then applies the proposed hybrid YOLO-ResNet50 model. These models analyze datasets to identify opium poppy cultivation, and their performance is assessed based on the training outcomes. The performance of the hybrid model is better in comparison to other models. This experiment helps users to support an investigation into the illegal cultivation of opium poppy and thus helps address the global challenges of the misuse of drugs.