الفهرس 
AbstractOnly 14 pages are availabe for public view
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Abstract
A huge amount of terabytes of data is generated each day from modern information systems and digital technologies such as the Internet of things (IoT) that can be considered as one of the forms of modern development of Wireless Sensor Network (WSN) and cloud computing that can be integrated into many systems forms such as the Healthcare Systems. Healthcare is one of the important fields that need efforts to evaluate it, Development in this field brings us many benefits that help protect humans from diseases and try to find better protocols for treatment and also provide a better environment for scientific research. There is a huge need to process data immediately to make useful decision rapidly, this data has a very large size and have many numbers of features, there are many attempts spotted this point and introduce many solutions with drawbacks in processing time and performance. This Thesis introduces a new framework for processing data and predicts useful information with minimum computational cost by performing features selection technique on data by using Whale Optimization Algorithm (WOA) then processing data using Naïve Bayes (NB) classifier that can be performed in real-time, this method is useful in improving accuracy by 4%, and reducing processing time by 9%. Furthermore, the framework can accept several types of data.