ADEPT Framework: Optimizing Data Flow in Dynamic Environments for Ambient Assisted Living

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URI: http://hdl.handle.net/10498/37643

DOI: 10.1007/978-3-031-83117-1_12

URL: https://link.springer.com/chapter/10.1007/978-3-031-83117-1_12

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Author/s
Balderas Díaz, SaraAuthority UCA; Guerrero Contreras, Gabriel JoséAuthority UCA
Date
2025-02-27
Department
Ingeniería Informática
Source
Ambient Intelligence – Software and Applications – 15th International Symposium on Ambient Intelligence. ISAmI 2024. Lecture Notes in Networks and Systems, vol 1279. Springer, Cham.
Abstract
The ADEPT framework integrates Ambient Intelligence (AmI) technologies into Ambient Assisted Living (AAL) and Ubiquitous Computing to improve the quality of life for the elderly and those needing special care, particularly as populations in developed nations age. ADEPT addresses the complexities of data transmission and gathering within dynamic networks by utilizing edge computing for near-source data preprocessing, which enhances responsiveness and reduces network load. Its effectiveness is validated through simulations focusing on nursing home scenarios using the ns-3 network simulator and BonnMotion. The framework’s architecture facilitates efficient data handling by dynamically managing and prioritizing data flow through its network of nodes. Evaluations show that data prioritization significantly boosts data gathering success rates across different network setups, underscoring ADEPT’s potential to enhance data management in AmI applications and meet the changing needs of AAL environments.
Subjects
Ambient Intelligence; Ambient Assisted Living; Edge Computing; Adaptive Systems; Sensor Networks
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