The rapid growth in miniaturization of low-power embedded devices and advancement in
the optimization of machine learning (ML) algorithms have opened up a new prospect of the …

The advancements in machine learning (ML) opened a new opportunity to bring intelligence
to the low-end Internet-of-Things (IoT) nodes, such as microcontrollers. Conventional ML …

Edge intelligence refers to a set of connected systems and devices for data collection,
caching, processing, and analysis proximity to where data are captured based on artificial …

The artificial intelligence (AI) revolution offers significant opportunities to capitalise on the
growth of digitalisation and has the potential to enable the 'system of systems' approach …

Recent advancements in ultra-low-power machine learning (TinyML) hardware promises to
unlock an entirely new class of smart applications. However, continued progress is limited …

Currently, Machine Learning (ML) is becoming ubiquitous in everyday life. Deep Learning
(DL) is already present in many applications ranging from computer vision for medicine to …

The emergence of Tiny Machine Learning (TinyML) has positively revolutionized the field of
Artificial Intelligence by promoting the joint design of resource-constrained IoT hardware …

The emerging field of artificial intelligence of things (AIoT, AI+ IoT) is driven by the
widespread use of intelligent infrastructures and the impressive success of deep learning …

Edge intelligence refers to a set of connected systems and devices for data collection,
caching, processing, and analysis in locations close to where data is captured based on …

The main problems with several existing Information and Communication Technology (ICT)
power footprint investigations are: too limited (geographical and temporal) system boundary …