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Monitoring is a process of continuously gathering data and performing real-time analysis, monitoring can improve the assessment of the current state, optimization of the business processes, identification of the critical situation, new opportunities, and assisted in decision support and planning. Traditional healthcare monitoring and services are usually offered within hospitals or medical centers, patient's vital signs measurements is conducted by traditional measurements approach. This is costly, inefficient and inconvenient for the people with the need of routine check. Thus addressing issues pertinent to healthcare monitoring. This work is focusing on the investigation of Ambient Intelligence (AmI) assisted healthcare monitoring model. The data set was constructed by simulation of patients wearable sensors from the environment of Baraha Medical City in Shambat, Khartoum North, Sudan. In connection, with this, we defined and developed proposed integrated AmI healthcare monitoring architecture framework. This research followed a research scientific design approach employing specific methods, including literature review, qualitative data analysis, and data mining (DM) techniques.
About the author
Dr. Abdelhamid Salih works in the field of healthcare monitoring using ambient intelligence, data mining and computational intelligence. Dr. Ajith Abraham works in the field of machine intelligence and has numerous publications. He is the Director of Machine Intelligence research Labs (MIR Labs).
