Movement and floor-sensor research
Several studies use floor-based sensors to record walking and movement as spatial and temporal signals. The research examines gait activities, footstep recognition, and models that classify measurements from optical-fiber carpets, footprint systems, and tomography sensors.
These studies address different questions, including movement classification and biometric recognition. Their individual publication pages describe the datasets, methods, and evaluation results for each study.
Spatial and environmental sensing
Other projects use wireless and spectral measurements for spatial or environmental analysis. A Wi-Fi fingerprinting paper studies indoor positioning, estimating where a device is from the pattern of wireless signal strengths it receives, while a spectral-data study applies unsupervised learning to measurements associated with rodent infestation in urban environments.
The Micro Atlas project used a drone-based system to detect crop disease, drought, pests, and nutrient shortages.
Sensing in robotics and applied systems
Other robotics projects explored sensor-guided navigation, mapping, and cooperation between autonomous systems. They include an RGB-D SLAM project using a Kinect camera for indoor mapping and localization, and a University of North Texas research-experience report on two NXT robots coordinating over Bluetooth.
Across these studies and projects, sensing supports movement research, environmental monitoring, indoor positioning, agriculture, and robotics.