Multimedia, as an information-diffusion domain, is one of the most rapidly evolving areas in information technology today. It has practical applications across many fields, including education and health.

Nowadays, society is bombarded with vast amounts of information—sound, images, text—and their combinations. We therefore need new methods for managing it.

Managing multimedia data—i.e., multimodal information—enables the effective presentation and storage of both raw and processed information.

Accordingly, multimedia applies to everything related to the structure of such data and, in particular, to how it is categorized across different informational domains—for example, recordings of vehicle sounds on public roads.

As we process information, patterns emerge from which we must derive knowledge. We do this through data mining. By organizing databases and applying grouping (clustering) algorithms, we aim to extract information from data (sound, images, text) and present it in a structure that users can interpret to make appropriate decisions.

Our goal is to automatically analyze large volumes of data and generate models across multiple datasets that help a decision-support system produce more accurate results.

Furthermore, the Internet of Things (IoT) refers to a network of physical objects connected to the internet. Such objects can produce sound, images, and text—and, in general, any data that can be processed as a live stream (streaming data)—thereby generating information that contributes to knowledge.