Practical Insights on Incremental Learning of New Human Physical Activity on the Edge
Edge Machine Learning (Edge ML), which shifts computational intelligence from cloud-based systems to edge devices, is attracting significant interest due to its evident benefits including reduced latency, enhanced data privacy, and decreased connectivity reliance. While these advantages are compelling, they introduce unique challenges absent in traditional cloud-based approaches. In this paper, we delve into the intricacies of Edge-based learning, examining the interdependencies among: (i) constrained data storage on Edge devices, (ii) limited computational power for training, and (iii) the number of learning classes. Through experiments conducted using our MAGNETO system, that focused on learning human activities via data collected from mobile sensors, we highlight these challenges and offer valuable perspectives on Edge ML.
Code (0)
등록된 구현이 없습니다.
Tasks
Incremental LearningSimilar Papers 제목 키워드 기반
On Handling Catastrophic Forgetting for Incremental Learning of Human Physical Activity on the Edge
Human activity recognition (HAR) has been a classic research problem. In particular, with recent machine learning (ML) techniques, the recognition task has been largely investigated by companies and integrated into their…
Activity RecognitionHuman Activity RecognitionIncremental LearningIncremental Learning Techniques for Online Human Activity Recognition
Unobtrusive and smart recognition of human activities using smartphones inertial sensors is an interesting topic in the field of artificial intelligence acquired tremendous popularity among researchers, especially in rec…
Activity RecognitionHuman Activity RecognitionIncremental LearningLifelong Adaptive Machine Learning for Sensor-based Human Activity Recognition Using Prototypical Networks
Continual learning, also known as lifelong learning, is an emerging research topic that has been attracting increasing interest in the field of machine learning. With human activity recognition (HAR) playing a key role i…
Activity Recognitionclass-incremental learningClass Incremental LearningContinual Learning+3Incremental Activity Modeling and Recognition in Streaming Videos
Most of the state-of-the-art approaches to human activity recognition in video need an intensive training stage and assume that all of the training examples are labeled and available beforehand. But these assumptions are…
Active LearningActivity RecognitionHuman Activity RecognitionConSense: Continually Sensing Human Activity with WiFi via Growing and Picking
WiFi-based human activity recognition (HAR) holds significant application potential across various fields. To handle dynamic environments where new activities are continuously introduced, WiFi-based HAR systems must adap…
Activity Recognitionclass-incremental learningClass Incremental LearningExemplar-Free+2