Utilization resource of artificial intelligence, machine learning, and deep learning: this study investigates infrared thermal imaging as a potential method for skin cancer diagnosis. Skin disorders present a significant medical challenge in the twenty-first century due to their complex and costly diagnostic procedures and the potential for subjective interpretation. When faced with fatal diseases like melanoma, early diagnosis is critical in determining the likelihood of curing the disease. We believe that early diagnosis will be possible through automated methods, especially for datasets that have a variety of diagnoses. We present, in this paper, a system that automatically identifies skin lesions using images, rather than using medical personnel for the detection of dermatological diseases. Three phases make up our model, including data collection and augmentation, identification of appropriate components, and making predictions. Using Convolutional Neural Networks combined with image processing tools, we have developed a method of detecting melanoma.