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Article ? AI-assigned paper type based on the abstract. Classification may not be perfect — flag errors using the feedback button. Tier 2 ? Original research — experimental, observational, or case-control study. Direct primary evidence. Environmental Sources Marine & Wildlife Policy & Risk Sign in to save

Living Organisms as Sensors for Biohybrid Monitoring Systems

Lecture notes in computer science 2023 4 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 35 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Wiktoria Rajewicz, Nikolaus Helmer, Thomas Schmickl, Ronald Thenius

Summary

Researchers designed a biohybrid aquatic monitoring system that integrates living organisms with mechanical and electronic components, presenting calibration methodology and preliminary results demonstrating that organism behavior can serve as a real-time sensor for detecting water quality changes.

Abstract Many aquatic habitats have become vulnerable to rapid and long-term changes induced by industrialism, air pollution, tourism, fishing activities etc. These factors created an urgent need for extensive water monitoring and conservation. By observing the behaviour of lifeforms, we can monitor the state of the environment. Here, we present the methodology, calibration approaches and preliminary results of designing a biohybrid entity for aquatic monitoring. Biohybrid robots combine mechanical and electronic elements with living organisms or tissues. This biohybrid consists of several modules, each hosting or attracting different species and communities. We focus on animals such as Daphnia sp., zebra mussel Dreissena polymorpha and various representatives of the plankton community. The first results showed that 1) both Daphnia and D. polymorpha show no clear signs of confinement-induced stress, 2) the designed structures are examples of suitable tools for hosting the organisms, observing their behaviour and collecting and storing data and 3) their behaviour can be calibrated under laboratory conditions to be able to extrapolate the field data into environmental data.

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