Geographic spaces is a vast and complex system involving multiple elements and nonlinear
interactions of these elements, and rich in geographical phenomena, processes and …

Artificial Intelligence (AI) is an emerging technology that finds its application in various
industries. Integration of AI in Unmanned Aerial Vehicles (UAVs) can lead to tremendous …

The quality inspection of industrial products is a fundamental step in large-scale production
as it boosts the yield and reduces the costs. Intelligent embedded platforms with built-in tiny …

Abstract Mobile Edge Computing (MEC) is a modern paradigm that involves moving
computing and storage resources closer to the network edge, reducing latency, and …

In the Machine Learning (ML) era, faced with challenges, including exponential multi-sensor
data, an increasing number of actuators, and data-intensive algorithms, the development of …

Tiny machine learning (TinyML) in IoT systems exploits MCUs as edge devices for data
processing. However, traditional TinyML methods can only perform inference, limited to …

Unmanned aerial vehicles (UAVs) are widely utilized in myriad domains due to their low
infrastructure cost and flexibility in deployment. Hostile and unsafe networking environments …

Highlights Lightweight deep learning models were trained on an edge device to identify
weeds in aerial images. A customized configuration file was setup to train the models. These …

The development of safe and reliable autonomous unmanned aerial vehicles relies on the
ability of the system to recognise and adapt to changes in the local environment based on …

Research interest in autonomous control of unmanned aerial vehicles (UAVs) has increased
rapidly over the past decade. They are now widely used in civilian, military, and private …