Human activity recognition based on multienvironment sensor data

•Sensor data contribution analysis method based on status frequency-inverse frequency.•Spatial distance matrix for context-awareness of cross-activities.•Novel wide time-domain convolutional neural network (WCNN, powerful parallel feature extraction).•The proposed method can save time and attain comparatively good performance.