Greening smart learning environments with artificial intelligence of things
This article investigates the functionality and applications of an Artificial Intelligence of Things (AIoT) system specifically designed for learning purposes. It presents three compelling case studies that pilot the AIoT system in various educational contexts. The first case study focuses on primar...
| Autores: | , , , , , , |
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| Formato: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2024 |
| País: | España |
| Recursos: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repositorio: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:10230/70671 |
| Acesso em linha: | http://hdl.handle.net/10230/70671 http://dx.doi.org/10.1016/j.iot.2023.101051 |
| Access Level: | acceso abierto |
| Palavra-chave: | Artificial intelligence Avatar Plant biosensors Environmental education Internet of things Learning activities Predictive models Smart learning environments |
| Resumo: | This article investigates the functionality and applications of an Artificial Intelligence of Things (AIoT) system specifically designed for learning purposes. It presents three compelling case studies that pilot the AIoT system in various educational contexts. The first case study focuses on primary education and the use of a smart dashboard to monitor the state of plants in environmental awareness activities. In the second case study, conducted in higher education, variables such as levels, light intensity, and temperature are monitored to generate personalised recommendations for creating an optimal learning environment through tailored adjustments. The third case study explores the potential of plants to identify human presence and activity patterns in learning environments. By utilising the AIoT system’s capabilities, plant data is analysed to infer human presence and interactions. This innovative approach offers insights into understanding student behaviour and optimising learning environments based on real-time feedback from the plant ecosystem. Analysing these studies, the article deliberates on implications and future research opportunities in the realm of AI and IoT. It underscores the potential of AIoT systems in enhancing learning experiences, engaging students, and refining educational settings. The findings not only pave the way for future investigations, including model enhancements and privacy considerations but also emphasise AIoT’s potential in reshaping the educational landscape. This article serves as a valuable resource for researchers and practitioners keen on leveraging the synergy of AI and IoT in educational contexts. |
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