EyeOnWater Raspberry Pi: a do-it-yourself maker sensor system project to measure and classify natural water colour based on the Forel–Ule scale

Abstract. The EyeOnWater Raspberry Pi (EOW–RPI) is a do-it-yourself maker project for citizen science to measure and classify the natural colour of water. It describes the systematic development (from concept to the prototype and application) and evaluation of a replicable optical sensor system that enables the automatic determination of water's colour according to the Forel–Ule colour scale using a Raspberry Pi and associated camera. Within the framework of image data processing, the system was automated in accordance with the criteria of scientific methods such that application errors were minimised from the initial image acquisition to the colour analysis. The overarching purpose of this project was to promote the independence of scientifically interested and technically skilled laypersons in building their own research device and collecting and providing their own data through a community website. Furthermore, the project can serve as inspiration for the maker community with respect to the development of enhanced extensions. For this purpose, it is crucial that the documentation of software and hardware is made available as open-source information. In this project, we follow a systemic methodology that extends from the requirement analysis and conceptualisation phase through to the system architecture, with the aim of developing suitable hardware and software. To this end, the sensor system was implemented as a prototype and its technical feasibility; handling; and the scientific quality of data acquisition, processing, and Forel–Ule colour analysis were evaluated.

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Publication Details

Journal
Journal of sensors and sensor systems
Published
2025-10-07
DOI
https://doi.org/10.5194/jsss-14-203-2025
Primary Topic
Water Quality Monitoring Technologies
Type
article
Field-Weighted Citation Impact
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article

EyeOnWater Raspberry Pi: a do-it-yourself maker sensor system project to measure and classify natural water colour based on the Forel–Ule scale

Nick Rüssmeier, Frederic Stahl, F. Becker
Journal of sensors and sensor systems
Water Quality Monitoring Technologies
article

EyeOnWater Raspberry Pi: a do-it-yourself maker sensor system project to measure and classify natural water colour based on the Forel–Ule scale

Nick Rüssmeier, Frederic Stahl, F. Becker
article en

Abstract

Abstract. The EyeOnWater Raspberry Pi (EOW–RPI) is a do-it-yourself maker project for citizen science to measure and classify the natural colour of water. It describes the systematic development (from concept to the prototype and application) and evaluation of a replicable optical sensor system that enables the automatic determination of water's colour according to the Forel–Ule colour scale using a Raspberry Pi and associated camera. Within the framework of image data processing, the system was automated in accordance with the criteria of scientific methods such that application errors were minimised from the initial image acquisition to the colour analysis. The overarching purpose of this project was to promote the independence of scientifically interested and technically skilled laypersons in building their own research device and collecting and providing their own data through a community website. Furthermore, the project can serve as inspiration for the maker community with respect to the development of enhanced extensions. For this purpose, it is crucial that the documentation of software and hardware is made available as open-source information. In this project, we follow a systemic methodology that extends from the requirement analysis and conceptualisation phase through to the system architecture, with the aim of developing suitable hardware and software. To this end, the sensor system was implemented as a prototype and its technical feasibility; handling; and the scientific quality of data acquisition, processing, and Forel–Ule colour analysis were evaluated.

Journal of sensors and sensor systemsVol. 14(2)
Jade University of Applied Sciences (DE), German Research Centre for Artificial Intelligence (DE)
Openalex Percentile: Top 74%
Water Quality Monitoring Technologies
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EyeOnWater Raspberry Pi: a do-it-yourself maker sensor system project to measure and classify natural water colour based on the Forel–Ule scale — Nick Rüssmeier, Frederic Stahl, et al. · Journal of sensors and sensor systems (2025) | TGRS Research Map | TGRS