Discriminating sensor activation in activity recognition within multi-occupancy environments based on nearby interaction
This work presents a computer model to discriminate sensor activation in multi-occupancy environments based on proximity interaction. Current proximity-based and indoor location methods allow the estimation of the positions or areas where inhabitants carry out their daily human activities. The spatial-temporal relation between location and sensor activations is described in this work to generate a sensor interaction matrix for each inhabitant. This enables the use of classical HAR models to reduce the complexity of the multi-occupancy problem. A case study deployed with UWB and binary sensors is presented.
Code (0)
등록된 구현이 없습니다.
Tasks
Activity RecognitionSimilar Papers 제목 키워드 기반
MARAuder's Map: Motion-Aware Real-time Activity Recognition with Layout-Based Trajectories
Ambient sensor-based human activity recognition (HAR) in smart homes remains challenging due to the need for real-time inference, spatially grounded reasoning, and context-aware temporal modeling. Existing approaches oft…
Human Activity RecognitionAttend And Discriminate: Beyond the State-of-the-Art for Human Activity Recognition using Wearable Sensors
Wearables are fundamental to improving our understanding of human activities, especially for an increasing number of healthcare applications from rehabilitation to fine-grained gait analysis. Although our collective know…
Activity RecognitionHuman Activity RecognitionGeXSe (Generative Explanatory Sensor System): An Interpretable Deep Generative Model for Human Activity Recognition in Smart Spaces
We introduce GeXSe (Generative Explanatory Sensor System), a novel framework designed to extract interpretable sensor-based and vision domain features from non-invasive smart space sensors. We combine these to provide a …
Activity RecognitionHuman Activity RecognitionUsing Language Model to Bootstrap Human Activity Recognition Ambient Sensors Based in Smart Homes
Long Short Term Memory LSTM-based structures have demonstrated their efficiency for daily living recognition activities in smart homes by capturing the order of sensor activations and their temporal dependencies. Neverth…
Activity RecognitionHuman Activity RecognitionLanguage ModelingLanguage Modelling+1UMSNet: An Universal Multi-sensor Network for Human Activity Recognition
Human activity recognition (HAR) based on multimodal sensors has become a rapidly growing branch of biometric recognition and artificial intelligence. However, how to fully mine multimodal time series data and effectivel…
Activity RecognitionHuman Activity RecognitionTime SeriesTime Series Analysis+1