Advancing environmental intelligence through novel approaches in soft bioinspired robotics and allied technologies: I-Seed project position paper for Environmental Intelligence in Europe

dc.bibliographicCitation.firstPage265
dc.bibliographicCitation.lastPage268
dc.contributor.authorMazzolai, Barbara
dc.contributor.authorKraus, Tobias
dc.contributor.authorPirrone, Nicola
dc.contributor.authorKooistra, Lammert
dc.contributor.authorDe Simone, Antonio
dc.contributor.authorCottin, Antoine
dc.contributor.authorMargheri, Laura
dc.date.accessioned2023-02-24T06:43:46Z
dc.date.available2023-02-24T06:43:46Z
dc.date.issued2022
dc.description.abstractThe EU-funded FET Proactive Environmental Intelligence project "I-Seed"(Grant Agreement n. 101017940, https://www.iseedproject.eu/) targets towards the development of a radically simplified and environmentally friendly approach for environmental monitoring. Specifically, I-Seed aims at developing a new generation of self-deployable and biodegradable soft miniaturized robots, inspired by the morphology and dispersion abilities of plant seeds, able to perform low-cost, environmentally responsible, in-situ measurements. The natural functional mechanisms of seeds dispersal offer a rich source of robust, highly adaptive, mass and energy efficient mechanisms, and behavioral and morphological intelligence, which can be selected and implemented for advanced, but simple, technological inventions. I-Seed robots are conceived as unique in their movement abilities because inspired by passive mechanisms and materials of natural seeds, and unique in their environmentally friendly design because made of all biodegradable components. Sensing is based on a chemical transduction mechanism in a stimulus-responsive sensor material with fluorescence-based optical readout, which can be read via one or more drones equipped with fluorescent LiDAR technology and a software able to perform a real time georeferencing of data. The I-Seed robotic ecosystem is envisioned to be used for collecting environmental data in-situ with high spatial and temporal resolution across large remote areas where no monitoring data are available, and thus for extending current environmental sensor frameworks and data analysis systems.eng
dc.description.versionpublishedVersioneng
dc.identifier.urihttps://oa.tib.eu/renate/handle/123456789/11514
dc.identifier.urihttp://dx.doi.org/10.34657/10548
dc.language.isoeng
dc.publisherNew York,NY,United States : Association for Computing Machinery
dc.relation.doihttps://doi.org/10.1145/3524458.3547262
dc.relation.isbn978-145039284-6
dc.relation.ispartofProceedings of the 2022 ACM Conference on Information Technology for Social Good
dc.relation.ispartofseriesACM Digital Library
dc.rights.licenseCC BY 4.0 Unported
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectaerial roboticseng
dc.subjectbiodegradable technologieseng
dc.subjectBioinspired roboticseng
dc.subjectchemical transduction sensingeng
dc.subjectenvironmental intelligenceeng
dc.subjectLiDAReng
dc.subjectmulti-functional materialseng
dc.subjectplant biologyeng
dc.subjectsoft roboticseng
dc.subjectUnmanned Aerial Vehicles (UAVs)eng
dc.subjectKonferenzschriftger
dc.subject.ddc620
dc.subject.ddc333.7
dc.titleAdvancing environmental intelligence through novel approaches in soft bioinspired robotics and allied technologies: I-Seed project position paper for Environmental Intelligence in Europeeng
dc.typebookPart
dc.typeText
dcterms.bibliographicCitation.journalTitleACM Digital Library
tib.accessRightsopenAccess
tib.relation.conference2nd ACM Conference on Information Technology for Social Good (GoodIT 2022), 7–9 September 2022, Limassol, Cypruseng
wgl.contributorINM
wgl.subjectIngenieurwissenschaftenger
wgl.subjectUmweltwissenschaftenger
wgl.typeBuchkapitel / Sammelwerksbeitragger
Files
Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Advancing_environmental_intelligence.pdf
Size:
416.94 KB
Format:
Adobe Portable Document Format
Description: