Description
In a healthcare environment, we usually get the patient's health information in an idle state. The collected data is then managed and analyzed in the healthcare server, so that a care giver can study the patient's physiological state. In order to get the patient's health information while performing his daily tasks, we need a ubiquitous device. The goal of this thesis is to design an "Intelligent HealthCare Data Management System" for mobile environments that will handle the healthcare data of the patient and also converts it into a globally used standard for exchange of healthcare data and information. Intelligent healthcare data management system (IHDMS) has an intelligent algorithm similar to genetic algorithm that can find an optimal solution within an acceptable time, and is faster and more dynamic than greedy algorithms in assigning tasks. It processes and transmits sensor data in a way such that it minimizes the system end to-end delay, while guaranteeing required system battery lifetime and availability of the mobile device. This system also converts raw data of the user from sensors to HL7 (Health Level Seven) format and transmits the encrypted HL7 data to a remote healthcare server. The device battery lifetime is potentially increased by more than 200%, the memory usage is less than 100 KB and it processes all data by utilizing very few resources. Apart from this, the system also reduces the time latency in transferring the data and also server load on the healthcare center side by transferring data in HL7 format through a secured channel. The IHDMS on a ubiquitous device is dynamic, efficient, fast, secure and reduces load on end systems compared to other system. It addresses most needs of the modern day ubiquitous devices in managing the patient's healthcare data.
