CatFish global presence

CatFish provides comprehensive real-time water quality monitoring using a system of interconnected drones. These drones—The Cat, The Fish, and The Bird—enable the collection of high-resolution data to improve environmental assessments and help authorities make informed decisions.

How we measure

Our unmanned surface vehicle USV drives on the water surface of inland water bodies. It is equipped with several sensors which continuously measure a range of water quality parameters. A water sampler unit on the USV can automatically collect up to 4 separated samples per mission. The extension of the USV is a gondola that can be lowered to any depth of the water body. The gondola is equipped with light, sensors and a camera. It forwards data via a tether to the USV. An unmanned aerial vehicle UAV that flies above the water surface is the third pillar of our integrated approach. It is equipped with a multispectral camera and captures images around the USV. With the help of machine learning the water quality data can be read from the images. All data is automatically saved in a cloud and can be downloaded for water quality analysis

What we measure

Why we measure

Water quality monitoring was and will always be the foundation of informed decision-making. The Aquality USV generates high resolution measurements by time and area with a high degree of autonomy. These can complement existing monitoring programs where data is generated based on standardized procedures. Our USV is furthermore suitable for specific cases and research questions that require high resolution data in shorter time with lower labour intensity. The current global trend to incorporate remote sensing for environmental monitoring requires reliable ground truth data. This is accurate and trustworthy data we actually measure with the Aquality USV and its gondola. We are actively developing the connectivity to remote sensing devices through deployment of an UAV

Performance calculation with Python

In this section, we dive into the performance data of different water bodies using Python for advanced calculations. By analyzing key metrics such as speed, distance, and mission duration, we can gain insights into how each environment affects overall performance. Let's explore the results below.

  • Total driven distance (m): 4242.53 (River Nissan)

  • Maximum speed (m/s): 1.80 (River Nissan)

  • Average speed (m/s): 0.79 (River Nissan)

  • Mission duration (hh): 1.46 (River Nissan)

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Let’s Transform Aquatic Research Together

Unlock the future of water-based data collection with Aquality

Let’s Transform Aquatic Research Together

Unlock the future of water-based data collection with Aquality

Let’s Transform Aquatic Research Together

Unlock the future of water-based data collection with Aquality

© 2024 Aquality Halmstad. All rights reserved.

Designed by AuRacy

© 2024 Aquality Halmstad. All rights reserved.

Designed by AuRacy

© 2024 Aquality Halmstad. All rights reserved.

Designed by AuRacy