Edge optimized and personalized lifelogging framework using ensembled metaheuristic algorithms

• Published in: Computers & electrical engineering Vol. 100; p. 107884
• Main Authors: Agarwal, Preeti, Alam, Mansaf
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier Ltd 01.05.2022; Elsevier BV
• Subjects: Activity recognition; Algorithms; Big Data Analytics (BDA); Classifiers; Cloud Computing (CC); Communications traffic; Customization; Data transmission; Decision trees; Edge Computing (EC); Edge intelligence; Energy consumption; Feature recognition; Heuristic methods; Human Activity Recognition (HAR); Internet of Things (IoT); Metaheuristic algorithms; Internet of Things (IoT); Human Activity Recognition (HAR); Cloud Computing (CC); Big Data Analytics (BDA); Edge intelligence; Metaheuristic algorithms; Edge Computing (EC)

•A four-layer edge optimized and user-personalized framework for life-logging human activities is proposed.•A lightweight edge intelligence module requiring low computation is designed, which reduces data transmission to the cloud.•A novel Max Score Pooling (MSP) algorithm based on ensembled metaheu...