IoT-Driven Image Processing Framework for Accurate Skin Diseases Diagnosis and Classification

Skin diseases affect millions worldwide, and accurate diagnosis classification are critical for effective treatment. The Internet of Things (IoT) has emerged as a powerful technology that can be used to improve healthcare systems in recent years. This paper proposes an image processing framework based on IoT skin disease classification. To enable remote real-time diagnosis, the proposed combines capabilities devices, such smartphones or wearable cameras, with advanced techniques. uses cameras built into devices capture high-resolution images affected areas. After that, securely transmitted central server cloud-based platform analysis. framework's image-processing component employs cutting-edge algorithms enhancement, feature extraction, Deep learning techniques, convolutional neural networks (CNNs), automatically extract relevant features from images. These characteristics then classify accurately. incorporates robust encryption authentication mechanisms during data transmission storage ensure privacy security sensitive medical data. Patient consent anonymization techniques also address concerns. several advantages over traditional methods diagnosing diseases. It enables by leveraging reducing need patients travel facilities. analysis allows prompt intervention treatment planning. Extensive experiments carried out using diverse dataset assess performance framework. findings show is highly classifying various