دانلود کتاب تشخیص ناهنجاری و پردازش رویداد پیچیده از طریق جریان داده های اینترنت اشیا با کاربرد در سلامت الکترونیک و پایش داده های بیمار

Internet-of-Things (IoT) is being fast established as the new computing paradigm, which is bound to change the ways of our everyday working and living. With the ever-increasing number of connected devices, the IoT devices have become a primary source of data generation in the form of Big Data or Big Data streams. Few years following the introduction of the IoT concept, significant hype was generated as a result of the proliferating number of IoT-enabled devices, which are expected to amount to several billion in the next years. During recent years, this hype has been turning to reality, as a wave of IoT applications with significant social and economic has been emerging. In most cases, these applications rely on the processing of IoT data in order to optimize operations and facilitate decision making. IoT analytics applications will ensure the proper exploitation of huge volumes of IoT data for a variety of nontrivial purposes, involving not only the production of simple data-driven insights on operations but also the prediction of events and build the basis for prescriptive analytics. Healthcare domain is one such field of activity where IoT computing is envisioned to play a revolutionary change. Indeed, healthcare is at its core driven by data. Research needs to conduct studies to get data for further inferences of reasons and treatments for illnesses. Based on this knowledge, a healthcare professional observes the patient (in other words gets information/data) and sets the diagnosis and treatment accordingly. Data gathering is an expensive process for researchers, doctors, and patients in terms of time, space, cost and staffing requirements. This is a constraint that finally leads to less insight which could be used to react quickly to critical situations, detect health issues or provide more accurate data for research on diagnosis and treatment. Due to the nonavailability of ready to access healthcare data, many health problems may remain undetected in conventional healthcare systems.