The primary goal of developing a smart city is to enhance the quality of lives of its citizens by providing infrastructure and offering smart healthcare. Smart Healthcare plays a significant role in achieving this objective of developing smart cities. Here, in this proposal our objective is to develop a smart health care system which uses artificial intelligence for the development of a decision support system in the medical field for the detection and segmentation of lung cancer. The proposed system is consisting of two phases, First phase will be consisting of various stages like Pre-processing, feature extraction, feature selection, classification and finally segmentation of the tumor. Input CT image is sent through the pre-processing phase where noise removal will be taken care and then texture features are extracted from the pre-processed image, and in the next stage features will be selected by making use of Crow Search Optimization Algorithm, later Artificial Neural Network is used for the classification of the normal lung images from abnormal images. Finally, abnormal images will be processed through the Fuzzy K-Means algorithm for segmenting the tumors separately. In the second phase, SVM classifier is used for the reduction of false positives. This methodology delivers a 96% of accuracy, 100% specificity and sensitivity of 99%. The accuracy of the decision taken by the Smart Health Care System exceed when compared to the accuracy of the decision taken by the doctors.
