IoT Microsoft access based database management system for health care and clinical settings / Sultan Mahmud - Sultan, Mahmud (2019)
The “things” in Internet of Thing can refer to a wide variety of devices – implants, sensors, automobiles, etc. The IoT has a variety of application domains, including health care and clinical environment. The expended sensing and communicational capabilities of these “things” is a harbinger of new business possibilities in the hospital and different health care organizations. The IoT revolution is remodeling recent health care with promising technological, social, and economical prospects. This project advances in IoT-based health care technologies using Microsoft access and reviews the state-of-the-art platforms, applications, and industrial trends in health care solutions. In addition, it analyzed distinct IoT security and privacy features, including security requirements, threat models from the health care perspective and proposes a collaborative security model to minimize security risk. It also discussed how different innovations such as big data, application of access based healthcare platform and artificial intelligence can be leveraged in a health care technology context. Additionally, it addressed different IoT and eHealth regulations and policies to decide how they can facilitate societies and economies in terms of sustainable improvement. Hence, this research involved in organization and collection of sensitive health related data from clinical environments, built health database on Microsoft access, stored and retrieval of data from the cloud for easy access and interpretation of those data whenever required. The results from the interpretations can be used to analyze data to make concise decisions about the patient conditions. After the data storage had built from different sources like hospital and clinics on the access database, payer data, patient responses, consumer health data has been integrated into a unified data structure, the IoT would show the results of the various health status based on the data input related to the different physical and mental conditions and other associated parameters. Followed by implementation of artificial intelligence, which yield meaningful insights to make predictive recommendations about the patient health conditions, suggest possible treatment plan based on what happened in those other related situations to improve overall patient’s experiences and excel health care environments.