Diabetes mellitus is a serious health problem affecting the entire population all over the
world for many decades. It is a group of metabolic disorder characterized by chronic disease …

The cloud and fog computing paradigms are developing area for storing, processing, and
analysis of geospatial big data. Latest trend is mist computing which boost fog and cloud …

Deep learning has recently gained high interest in ophthalmology due to its ability to detect
clinically significant features for diagnosis and prognosis. Despite these significant …

The use of wearable and Internet-of-Things (IoT) for smart and affordable healthcare is
trending. In traditional setups, the cloud backend receives the healthcare data and performs …

The advent and consolidation of the Massive Internet of Things (MIoT) comes with a need for
new architectures to process the massive amount of generated information. A new …

Objectives Telehealth monitoring applications are latency-sensitive. The current fog-based
telehealth monitoring models are mainly focused on the role of the fog computing in …

Many of the interesting and important applications of machine learning are seen in a
medical organization. The notion of machine learning has swiftly become very appealing to …

The IoT cloud-based infrastructure has some drawbacks with latency, delays, availability,
distribution, and more. To avoid these kinds of issues, Fog Computing (FC) integrates as a …

Today, internet of things (IoT) has become an important paradigm. Everyday increasing
number of IoT applications and services emerge. Smart devices connected by the IoT …

In today's information age, the Internet of Spatial Things (IoST) is rapidly gaining
prominence. Massive amounts of geospatial data are generated by IoST and cloud …