ISEP - DM – Engenharia de Inteligência Artificial
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Browsing ISEP - DM – Engenharia de Inteligência Artificial by Sustainable Development Goals (SDG) "10:Reduzir as Desigualdades"
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- Leveraging generative artificial intelligence and wearable technology for adaptive health and conversational interventions in the elderlyPublication . Crista, Vítor Rafael Palmeiro; Martinho, Diogo Emanuel PereiraAging is often associated with an increase in loneliness and social isolation, factors that have significant consequences for health. The lack of social interactions can lead to a decline in emotional well-being, the deterioration of cognitive conditions, and a higher risk of physical health problems. Therefore, it is relevant to develop solutions that facilitate interaction and promote the quality of life of the elderly population, encouraging regular physical activity and improving their physical and psychological well-being. Technology attends as an effective tool to address these challenges, enabling the creation of systems that provide continuous support and interactions adapted to individual needs. This dissertation explores the development of a conversational system that uses wearable technology to collect information about users' health levels, aiming to create proactive interactions, encourage healthy habits, and promote active aging. The system also incorporates artificial intelligence, specifically generative artificial intelligence, with the main objective of developing advanced communication mechanisms between the system and the user. These mechanisms allow the system to learn from past interactions to improve the quality of future ones. The work included designing the system architecture, which integrates a Multi-Agent approach, providing a scalable structure that enables continuous improvements in the quality of the communication strategies used by the system. The solution was developed based on a domain model aligned with the common needs of elderly users and includes a detailed description of the essential components for its implementation. To evaluate the system, a study was conducted with five users, providing valuable insights into the system’s performance and impact. The study was conducted with five participants over a week, and to assess the system’s impact, indicators were defined to measure the key objectives of the research. The results indicate a positive impact on user participation and physical activity, with an average acceptance rate of proposed activities at 63.6%. Additionally, the average number of steps increased by 42.93% throughout the study, and the frequency of conversations recorded an average growth of 20.14%.