Pretražite po imenu i prezimenu autora, mentora, urednika, prevoditelja

Napredna pretraga

Pregled bibliografske jedinice broj: 1143006

Honeybee-based biohybrid system for landmine detection


Filipi, Janja; Stojnić, Vladan; Muštra, Mario; Gillanders, Ross N.; Jovanović, Vedran; Gajić, Slavica; Turnbull, Graham A.; Babić, Zdenka; Kezić, Nikola; Risojević, Vladimir
Honeybee-based biohybrid system for landmine detection // Science of the total environment, 803 (2022), 150041, 9 doi:10.1016/j.scitotenv.2021.150041 (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 1143006 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Honeybee-based biohybrid system for landmine detection

Autori
Filipi, Janja ; Stojnić, Vladan ; Muštra, Mario ; Gillanders, Ross N. ; Jovanović, Vedran ; Gajić, Slavica ; Turnbull, Graham A. ; Babić, Zdenka ; Kezić, Nikola ; Risojević, Vladimir

Izvornik
Science of the total environment (0048-9697) 803 (2022); 150041, 9

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
REST sampling, Organic semiconductors, Unmanned aerial vehicles, Convolutional neural networks, Humanitarian demining

Sažetak
Legacy landmines in post-conflict areas are a non-discriminatory lethal hazard and can still be triggered decades after the conflict has ended. Efforts to detect these explosive devices are expensive, time- consuming, and dangerous to humans and animals involved.While methods such as metal detectors and sniffer dogs have successfully been used in humanitarian demining, more tools are required for both site surveying and accurate mine detection. Honeybees have emerged in recent years as efficient bioaccumulation and biomonitoring animals. The system reported here uses two complementary landmine detection methods: passive sampling and active search. Passive sampling aims to confirm the presence of explosive materials in a mine-suspected area by the analysis of explosive material brought back to the colony on honeybee bodies returning from foraging trips. Analysis is performed by light-emitting chemical sensors detecting explosives thermally desorbed from a preconcentrator strip. The active search is intended to be able to pinpoint the place where individual landmines are most likely to be present. Used together, both methods are anticipated to be useful in an end-to-end process for area surveying, suspected hazardous area reduction, and post- clearing internal and external quality control in humanitarian demining.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo, Tehnologija prometa i transport, Interdisciplinarne biotehničke znanosti



POVEZANOST RADA


Ustanove:
Fakultet prometnih znanosti, Zagreb,
Sveučilište u Zadru

Profili:

Avatar Url Mario Muštra (autor)

Avatar Url Nikola Kezić (autor)

Avatar Url Janja Filipi (autor)

Poveznice na cjeloviti tekst rada:

doi www.sciencedirect.com

Citiraj ovu publikaciju:

Filipi, Janja; Stojnić, Vladan; Muštra, Mario; Gillanders, Ross N.; Jovanović, Vedran; Gajić, Slavica; Turnbull, Graham A.; Babić, Zdenka; Kezić, Nikola; Risojević, Vladimir
Honeybee-based biohybrid system for landmine detection // Science of the total environment, 803 (2022), 150041, 9 doi:10.1016/j.scitotenv.2021.150041 (međunarodna recenzija, članak, znanstveni)
Filipi, J., Stojnić, V., Muštra, M., Gillanders, R., Jovanović, V., Gajić, S., Turnbull, G., Babić, Z., Kezić, N. & Risojević, V. (2022) Honeybee-based biohybrid system for landmine detection. Science of the total environment, 803, 150041, 9 doi:10.1016/j.scitotenv.2021.150041.
@article{article, author = {Filipi, Janja and Stojni\'{c}, Vladan and Mu\v{s}tra, Mario and Gillanders, Ross N. and Jovanovi\'{c}, Vedran and Gaji\'{c}, Slavica and Turnbull, Graham A. and Babi\'{c}, Zdenka and Kezi\'{c}, Nikola and Risojevi\'{c}, Vladimir}, year = {2022}, pages = {9}, DOI = {10.1016/j.scitotenv.2021.150041}, chapter = {150041}, keywords = {REST sampling, Organic semiconductors, Unmanned aerial vehicles, Convolutional neural networks, Humanitarian demining}, journal = {Science of the total environment}, doi = {10.1016/j.scitotenv.2021.150041}, volume = {803}, issn = {0048-9697}, title = {Honeybee-based biohybrid system for landmine detection}, keyword = {REST sampling, Organic semiconductors, Unmanned aerial vehicles, Convolutional neural networks, Humanitarian demining}, chapternumber = {150041} }
@article{article, author = {Filipi, Janja and Stojni\'{c}, Vladan and Mu\v{s}tra, Mario and Gillanders, Ross N. and Jovanovi\'{c}, Vedran and Gaji\'{c}, Slavica and Turnbull, Graham A. and Babi\'{c}, Zdenka and Kezi\'{c}, Nikola and Risojevi\'{c}, Vladimir}, year = {2022}, pages = {9}, DOI = {10.1016/j.scitotenv.2021.150041}, chapter = {150041}, keywords = {REST sampling, Organic semiconductors, Unmanned aerial vehicles, Convolutional neural networks, Humanitarian demining}, journal = {Science of the total environment}, doi = {10.1016/j.scitotenv.2021.150041}, volume = {803}, issn = {0048-9697}, title = {Honeybee-based biohybrid system for landmine detection}, keyword = {REST sampling, Organic semiconductors, Unmanned aerial vehicles, Convolutional neural networks, Humanitarian demining}, chapternumber = {150041} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus
  • MEDLINE


Citati:





    Contrast
    Increase Font
    Decrease Font
    Dyslexic Font