2 Oct - 2019

Good water quality is important to humans and to nature. In a country with as much water as the Netherlands has, ensuring water quality is a very labour-intensive undertaking. To address this issue, researchers from TU Delft have developed a 'pelican drone’: a drone capable of taking water samples quickly, in combination with a measuring instrument that immediately analyses the water quality. The drone was tested last week at the new Marker Wadden nature area ‘Living Lab’.

Currently, water samples are taken by hand from the waterside or from a vessel and sent to the laboratory for microscopic examination. Transporting a sample to the laboratory can negatively affect its quality. In addition, this method is relatively expensive and labour intensive. What's more, water quality often changes so fast that it really should be measured more often.

Quicker and more often
To enable us to sample water quicker and more often without it having to cost more, researchers from TU Delft are developing a watertight drone capable of landing on and even diving under water automatically.

A hyperspectral camera is mounted on this ‘Pelican drone’. This camera takes aerial shots which are used to determine the points where the samples need to be taken. The drone then lands at these points on the water to take a number of samples.

As soon as the drone returns, these samples are immediately and automatically analysed in a CytoSense, a flow cytometer that scans and photographs algae and other microorganisms. Tens of thousands of microorganisms are scanned and thousands photographed within a few minutes. These data are automatically processed and uploaded to an online portal. This process prevents deterioration of the sample as far as possible. After returning the drone charges itself on a charging station.

“The Pelican drone can vastly improve the monitoring of water quality and reduce costs"

Kevin van Hecke of the Micro Air Vehicle Lab (MAVLab) of TU Delft: “The Pelican drone can vastly improve the monitoring of water quality and reduce costs. It is much faster and more efficient at checking for blue-green algae, for example. The combination of a drone and flow cytometry allows us to monitor water quality autonomously and in real time. Our plan is ultimately to use the drone for underwater sampling as well, which is why we have called it the Pelican drone.”

Plankton in water sample (image: Cytobuoy)

Living Lab
Various flights were run in a small lake near Leiden during the summer of 2019, and today, the Pelican drone undertook sampling in the Markermeer lake, near the newly established Marker Wadden artificial archipelago. Scientists are validating the data from these tests with those from other sources.

Marker Wadden is a Living Lab in which scientists of the Marker Wadden Knowledge and Innovation Programme (KIMA) can perform practical experiments. Water quality management is still the subject of investigation in this newly established nature area, which makes it a unique environment in which to develop the new Pelican drone technology.

About the Pelican drone project
The Pelican drone project is an initiative of Rijkswaterstaat (national public works agency), TU Delft's MAVLab and the CytoBuoy company, and aims at the far-reaching automation of the process of water sampling. The charging station is provided by Mapture.AI.

The drone can currently only take samples from the surface, but the intention is for the drone eventually to be submersible. The problem of blue-green algae is the specific object of this project, but the technology has a wide range of applications.

More information

MAVLab TU Delft
CytoBuoy website
KIMA website

Contact information
Bart Remes (MAVLab TU Delft), +31 15 278 3707, B.D.W.Remes@tudelft.nl
Ilona van den Brink (Press Communications TU Delft), +31 15 278 4259, i.vandenbrink@tudelft.nl
Press office Rijkswaterstaat: +31 611 845 846, wvl-pers@rws.nl
George Dubelaar (CytoBuoy) +31 348 688101 info@cytobuoy.com



This website uses cookies to enhance user experience and to provide us with visitor analytics.