Distributed radar fusion and recurrent networks for classification of continuous human activities

Continuous Human Activity Recognition (HAR) in arbitrary directions is investigated in this paper using a network of five spatially distributed pulsed Ultra-Wideband radars. While activities performed continuously and in unconstrained trajectories provide a more realistic and natural scenario for HAR, the network of radar sensors is proposed...

Measurement of Air Pollution by Measurement of Traffic Density

The areas of many cities in the Netherlands are covered by a network of stationary sensors, measuring special components of air pollution such as CO2, NO2, PM2.5 and PM10. The pollution with fine dust along roads, surrounding and crossing the city is primarily related to traffic density. To measure traffic density, we used a license plate...

Approximately Optimal Radar Resource Management for Multi-Sensor Multi-Target Tracking: A First Step Towards a Distributed Solution for Radar Resource Management in a Sensor Network

The Radar Resource Management (RRM) problem in a multi-sensor multi-target scenario is considered. The problem is defined as a constrained optimization problem in which the predicted error covariance is minimized subject to resource budget constraints. By applying Lagrangian Relaxation (LR) the problem is decoupled into multiple sub-optimization...

Distributed optical sensor surface concept for planar object detection: Using optical fibers as a vision distributor

With the ever-increasing demand for a more efficient production process, the thickness of silicon wafers for the solar cell industry has shown a decreasing trend over the years. This makes the substrates more and more fragile, with an increasing breakage rate as a result. Research at the TU Delft has been done on contactless handling, using air...

Approximately Optimal Radar Resource Management for Multi-Sensor Multi-Target Tracking

Radar Resource Management in a multi-sensor multi-target scenario is considered. A dynamic resource balancing algorithm is proposed which optimizes target task parameters assuming an underlying partially observable Markov decision process (POMDP). By applying stochastic optimization methods, such as policy rollout, the POMDP is solved non...