Lifelong learning is the constant pursuit of knowledge, for either professional or personal reasons, inside and outside of formal educational institutes, such as schools and universities. In the modern world, technology evolves rapidly and there is the risk of being left behind; lifelong learning is greatly important as a way to avoid this threat. Although it is not an easy task, it can be supported with hardware and software systems, which can be seen as enablers for lifelong learning. Also, people might need different types of enablers to achieve lifelong learning, and an important guideline for this is contained in Article 24 of the Convention on the Rights of Persons with Disabilities. It states that “States Parties shall ensure that persons with disabilities are able to access general tertiary education, vocational training, adult education and lifelong learning without discrimination and on an equal basis with others”, highlighting the needing for enablers tools to remove barriers for all kinds of users.

The specific systems heavily depend on the domain under consideration and the skills that are learnt, and usually a single system is not effective on multiple domains. Crucially, both hardware and software systems can be used, often with very different scopes: with hardware systems aimed to provide access to information in every situation and environment, while software systems aimed to provide the best suitable form of information, as continuously needed by the user.

Such systems generally need large amounts of data to be effective, and we need tools of various kinds to organize and manage this data: from dedicated devices to new algorithms, able to provide the right form of the information in the right moment. In this sense, the very process of creating, curating and managing personal knowledge bases can be extremely helpful for lifelong learning, regardless of how such data will be used downstream.

As for software systems, there are many different forms of interaction between users and enablers. From virtual assistants able to provide previously unknown data to gamification-based platforms aimed to produce user engagement during some learning process.

In support of these projects, hardware systems play a fundamental role. Today, edge devices are able to collect and process large amounts of data both on site and online (in connection with the cloud or with local gateways). The development of ad hoc hardware systems (FPGA) and the use of communication architectures (IoT, M2M) can allow the development of specialized supports for lifelong learning activities.