New technologies bring opportunities to deploy AI and machine learning to the edge of the
network, allowing edge devices to train simple models that can then be deployed in practice …

Accurate detection of transportation objects is pivotal for enhancing driving safety and
operational efficiency. In the rapidly evolving domain of transportation systems, the …

There is a rapid increase in the number of edge devices in IoT solutions, generating vast
amounts of data that need to be processed and analyzed efficiently. Traditional cloud-based …

In the scope of smart cities, the sensors scattered throughout the city generate information
that supplies intelligence mechanisms to learn the city's mobility patterns. These patterns are …

Artificial intelligence and big data computing are developing at a fast pace, which has
resulted in the creation of several software service systems that use different machine …

Intent detection and slot filling are two main tasks in natural language understanding and
play an essential role in task-oriented dialogue systems. The joint learning of both tasks can …

Artificial intelligence holds significant potential for addressing various real-world challenges
in fields like healthcare and transportation. Nevertheless, existing avenues for disseminating …

This chapter explores the integration of applied artificial intelligence (AI), machine learning
(ML), and edge computing in cloud environments, with a focus on leveraging these …