A remarkable innovation in healthcare system presided to production of data of diabetes mellitus and cardio vascular diseases. Majority of population over the globe is suffering from one or the other kind of health issues. To visualize medical problems globally and to connect medical centre and patient all together, information technology contributes to excel in modern healthcare services. One, such advance IT field is Internet of things (IoT). IoT is step ahead in all aspects and so in healthcare. Health sort of area is something wherein IoT plays an important role. Inspite of that, IoT is not in mainstream adoption in healthcare sector, therefore it is required to develop enhanced version of traditional healthcare system that can facilitate to process data received from IoT healthcare devices. In this paper, (cardiac+diabetes) healthcare framework has been proposed to diagnose effects of diabetes over cardiac patients. Patient’s data is investigated on the basis of findings of (diabetes + cardiac) clinical diagnosis profile. Novel framework consists of two methodologies, first is GEETN technique (pre-processing method) and the other is Advanced Hoeffding to train and test model). Novelty of work is to pre-process (cardiac+diabetes) dataset using GEETN. The accumulated comparison is based on outcomes that consist of various algorithm with Advanced Hoeffding lincasingan accuracy of 98.99% Precision (92.99%), recall (97.56 %) and f1 score (95%) that helps in early detection of patients’ health condition to reduce the rate of death cases, cardiodibet healthcare systems helps in providing better monitoring, communication and early diagnosis of diabetes and cardiac health of patients. The proposed method identify the preliminary status of diabetes and cardiac vascular diseases parameters of patient through Normal, Moderate and high risk further message is generated for critical or emergency cases. It also helps to identify the possibilities of silent heart attack of patients at early stage, consequently reducing the can reduce the number of death cases.