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With the tremendous development in the field of Internet of Things (IoT), huge amount of data is being continuously generated. This data is termed as the big data. Processing of big data is a crucial task as it may be helpful for inferring useful information. The big data generated by IoT devices are processed using data analytics techniques that helps to analyse and explore the hidden information behind the big data. This system is especially useful in remote health monitoring systems in which data collected by medical sensors are processed and explored. In this research, we propose a new algorithm called IoT-based automatic remote health monitoring algorithm (IARHM), that can be used for monitoring the health conditions of patients from remote locations. In this framework, sensors like temperature sensor, pressure sensor, pulse rate sensor, cholesterol level sensor and sugar level sensor are used for collecting the medical data of the patients. These data are then transmitted to the cloud. In the cloud, these data are processed using the proposed IARHM algorithm to identify the health conditions of the patients. Any kind of abnormalities are immediately reported to the care takers so that immediate actions can be taken. The performance of the proposed algorithm is validated using metrics like accuracy, F-score, recall and latency. It was observed that, the proposed system achieved very high performance with minimal latency and hence can be easily implemented for real-time monitoring purposes. The main advantage of this framework is the remote monitoring capability of the system i.e., the patients can be monitored by the caretakers from remote locations. The proposed algorithm achieves a maximum recall of 97.59% and a maximum F-score of 96.83%.
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