The Internet of Things (IoT) is inter communication of embedded devices using various network technologies. The IoT technology is all set to become the upcoming trend in the future. We are proposing a healthcare monitoring system consisting of ECG Sensors. The parameters which are having a significant amount of importance are sensed by the ECG sensors which are vital for remote monitoring of patient. A mobile app observation is used to continuously monitor the ECG of the patient and various data extraction techniques are performed on the ECG wave to extract attributes to correctly predict heart diseases. .Data mining with its various algorithms reduce the extra efforts and time required to conduct various tests to detect diseases.. Data is collected from ECG sensors. The data is stored onto s storage medium where data mining algorithms are performed on the data collected. These algorithms predict whether the patient has any heart disease. The results can be referred by the doctors for diagnosis purpose. By using IOT technology and data mining algorithms the predication of heart disease is going to do in system

A Wireless ad-hoc network is an autonomous, self-organize distributed, peer to peer network of fix, nomadic or mobile user that communicates over bandwidth constrained wireless links. Energy Consumption and Network Connectivity are two of the most important issue that yet to be resolve in MANET's. Broadcasting, in context of ad-hoc networks is a costly operation and thus topology control has been proposed to achieve efficient broadcasting with low interference and energy consumption. By using topology control each node optimizes its transmission power, by maintaining network connectivity by localize manner. In this paper, we propose Local Tree-Based Reliable Topology (LTRT), which is mathematically proven to guarantee k-edge connectivity while preserving the feature of Local Minimum Spanning Tree (LMST).while applying topology control technology into Manet, it is important to address the issue of performance degradation due to node mobility. In the network each node contain the topology information to maintain the connectivity with neighbors for that it needs to be frequently and appropriately update its information according to its moving speed. In our mechanism, each node determines exact value of topology control update interval according to topology information of its neighbors. By simulation results using network simulator (NS2) we achieve better dynamic topology update mechanism.

The Internet of Things (IoT) is inter communication of embedded devices using  various network technologies. The IoT technology is all set to become the upcoming trend in the future. We are proposing a healthcare monitoring system consisting of ECG Sensors. The parameters which are having a significant amount of importance are sensed by the ECG sensors which are vital for remote monitoring of patient. A mobile app observation is used to continuously monitor the ECG of the patient and various data extraction techniques are performed on the ECG wave to extract attributes to correctly predict heart diseases. .Data mining with its various algorithms reduce the extra efforts and time required to conduct various tests to detect diseases.. Data is collected from ECG sensors. The data is stored onto s storage medium where data mining algorithms are performed on the data collected. These algorithms predict whether the patient has any heart disease. The results can be referred by the doctors for diagnosis purpose. By using IOT technology and data mining algorithms the predication of heart disease is going to do in system.