Deep Learning (DL) and Machine Learning (ML) are effectively utilized in various
complicated challenges in healthcare, industry, and academia. The Internet of Drones (IoD) …

Abstract The Internet of Things (IoT) is a communication paradigm and a collection of
heterogeneous interconnected devices. It produces large-scale distributed, and diverse data …

With opportunities brought by the Internet of Things (IoT), it is quite a challenge to maintain
concurrency and privacy when a huge number of resource-constrained distributed devices …

The military environment generates a large amount of data of great importance, which
makes necessary the use of machine learning for its processing. Its ability to learn and …

Abstract Geospatial Data Analytics (GDA) is a futuristic platform for analyzing and
processing volumetric data in remote sensing and GIS applications. GDA utilizes the Internet …

The architecture employed by most of the researchers for the deployment of latency‐
sensitive Internet of Things (IoT) applications is fog computing. Fog computing architecture …

The IoT and cloud environment renders enormous quantities of geospatial information. Fog
and mist computing is the scaling technology that handles geospatial data and sends it to …

Deep Learning models' performance strongly correlate with availability of annotated data;
however, massive data labeling is laborious, expensive, and error-prone when performed by …

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 …

The center of human settlements is in the cities, which must have high‐quality habitats for
their inhabitants. Many megachallenges of urbanization, population development, global …