CITIZEN SCIENCE TOOLS

Empowering Citizens to Monitor Our Oceans

One way in which NAUTILOS project advances marine research is by bridging the gap between science and society through the development of innovative citizen science tools. From user-friendly mobile apps to cutting-edge sensors and kits, these tools enable individuals, school students, divers and marine enthusiasts to actively participate in gathering and analyzing environmental data.

Explore the range of technologies developed within NAUTILOS on this page and discover how you can contribute to protecting our oceans.

What is included:

Citizen Science App
CS App Plastic Classifier
NIR scanner
AlgaWarning Kit

CITIZEN SCIENCE APP

The Citizen Science dedicated App is one of the cool tools that has been designed, implemented, and integrated into the NAUTILOS data infrastructure. It allows for the uploading and analyzing data gathered during various Citizen Science campaigns.

Data acquisition, management, and visualization work as a common entry-point to operate as a bridge towards NAUTILOS data infrastructure, with which they are fully integrated.

App main areas for data upload:

CS plastics-related campaigns (WP12)
Divers’ campaigns (WP10)
Crowdsourcing for visual marine image annotations (WP10)
Algal bloom related campaign (WP10)

IMPORTANT NOTE:

Using the CS App requires an approved registration!

The primary goal of the developed App is to support citizen science activities with various focus that NAUTILOS project partners and other ocean-related professional organizations arrange.

The acquired data is exported to the web platform, which provides for the sharing of data collection in a standardised way and guarantees a straightforward access to the collected scientific data.

We welcome new partnering projects or initiatives that want to work in synergy with NAUTILOS.

To request access to the App, fill out the contact form.

Download the CS App User Guide here.

APP PLASTIC CLASSIFIER

The NAUTILOS Citizen Science App is hosting the Plastic Classifier – an artificial intelligence algorithm based on automated detection and classification of plastic litter using aerial photos. This tool can be used to assess the amounts, types, and locations of plastic waste using an AI system on images derived mainly from remote sensing operations. The Plastic Classifier software was installed on an Ubuntu-based Linux system inside a virtual container using the DOCKER method, and was then integrated into the CS App.

Photos of plastic waste collected by citizen scientists within the framework of NAUTILOS Citizen Science activities can also be used as a data pool and form the basis for establishing the basic framework of an AI system, which will be further trained and tested using the data. The result will be a graphical representation of the current distribution of plastic waste in maps, along with information on its composition. In the long term, this concept could be used to monitor the main sources and distribution routes of plastic litter that is ending up in the aquatic environment, as well as for the coordination of measures to reduce plastic pollution.

For more information, contact Carolin Leluschko at carolin.leluschko@dfki.de

NIR SCANNER

The smartphone Near Infra-Red (NIR) scanner is developed from an available off-the-shelf commercial product (SCiO Consumer Physics) to obtain a tool that differentiates the polymer type of plastic fragments. The scanner is well suited for the identification of the meso litter (2.5 cm – 5 mm), which is often mistaken for food by marine organisms, thus entering the marine trophic chain. The polymer identification of plastic litter pieces gives an additional insight on potential sources, when shape and colour do not give any information on likely sources or usage.

A plastic litter database was developed within NAUTILOS after scanning 7 virgin polymers and 400 household articles that were focused on the most-used plastic polymers (PE, PA, PC, PET, PP, PS and PVC). The raw spectra were treated to obtain as much information as possible for matching the polymer spectra. The final model was not able to clearly distinguish between high-density and low-density polyethylene, which are chemically very similar.

The scanner is very easy to use by just placing it on the plastic fragment. The result is displayed, and the polymer type is given. A minimum of 3 scans per item is recommended in order to reduce false identifications.  A user manual is available on request.

The smartphone NIR scanner has been tested on several occasions during beach cleaning campaigns and cruises organised with students and citizen scientists under the framework of NAUTILOS project. More information on these activities can be found in the News section. Currently, a collaboration with the Department of Mechanical, Electrical and Chemical engineering of the OsloMet University and the Plastic Pirates is in progress aiming to develop a low cost open-source version of the NIR scanner which could be assembled even by the students.

Detailed information about the NIR CS tool can be requested from Bert Van Bavel; for the open-source version, contact Artur Piotr Zolich.

AlgaWarning – Citizen Science against Harmful Algal Blooms

AlgaWarning is a tool for monitoring Harmful Algal Blooms (HABs) in aquatic environments. These blooms represent a growing threat to human health and marine ecosystems, causing damage to biodiversity, fisheries, tourism and water quality. The project aims to collect scientific data at European level, fostering collaboration between citizens and researchers to monitor and prevent the impacts of such blooms in real time.

Thanks to its ease of use, the system allows citizens to actively participate in data collection. Observations are sent to a central server and displayed on an interactive map, accessible to all, to monitor the progress of blooms on a European scale.

AlgaWarning Kit

AlgaWarning is a portable kit designed for environmental monitoring of algal blooms in the field, allowing citizens to collect scientific data in real time. It is composed of the following components:

1. DIPLE® Micrometric Lens

Designed for low-cost microscopy via smartphone. It allows users to acquire high-quality microscopic images of microalgae in water samples. The DIPLE® is compatible with most smartphones, offering an affordable solution for anyone who wants to participate in the project without having to use professional equipment.

2. Sedgewick-Rafter Counting Chamber

This device allows you to visualize and count algal cells in water samples. It facilitates the determination of the concentration of algal cells, a key aspect for assessing the intensity of blooms.

3. @lgawarning App

The app allows you to create geo-localized reports, manually count algal cells in microscopic images and send the data to the web platform with the map viewer. Thanks to its simple and intuitive interface, the app is accessible even to those who do not have scientific expertise.

The citizen scientists can collect seawater samples from the field and observe them using the microscopic counting chambers and the objective lenses included in the kit. Using their smartphones, they can take photos of algal cells and upload them to the NAUTILOS Data Portal using the NAUTILOS CS App. This gives the citizen scientists the opportunity to transmit reports on the anomalous presence of microalgae in aquatic environments directly from the detection site. The reports include photos, geo-located coordinates, name of location, sample characteristics (taxon name, volume), habitat attributes (sea zone, sea bottom type), weather conditions and other useful details.

This tool has been designed to be accessible even to individuals without specific scientific expertise, such as citizens, students, water sports enthusiasts and everyone else who frequently visit aquatic environments. This inclusive approach promotes widespread and continuous data collection, contributing to forecasting models and improving environmental monitoring protocols at the European level.

For more information, contact Antonio Novellino at antonio.novellino@grupposcai.it.