Robotic vision based automatic pesticide sprayer for infected citrus leaves using machine learning

• Autorzy: Mohammed Emad A. , Mohammed Ghasaq H.

Identyfikatory

DOI

10.15199/48.2023.08.16

Warianty tytułu

PL

Zrobotyzowany automatyczny opryskiwacz pestycydów oparty na technologii wizyjnej do zainfekowanych liści cytrusowych z wykorzystaniem uczenia maszynowego

• Języki publikacji: EN

Abstrakty

EN

Smart farming has become a cutting-edge technology to address contemporary issues related to agricultural sustainability. Machine learning (ML) is the engine that powers this evolving technology. The study aims to develop a smart prototype robot to diagnose citrus trees (healthy or infected) using a convolutional neural network (CNN) algorithm. The results of the classification accuracy were 96%. And then, after spraying the affected areas with the pesticide, all farmers in the country can use it to protect themselves from the dangers of pesticides. The results were good and promising.

PL

Inteligentne rolnictwo stało się najnowocześniejszą technologią rozwiązującą współczesne problemy związane ze zrównoważonym rolnictwem. Uczenie maszynowe (ML) to silnik napędzający tę rozwijającą się technologię. Badanie ma na celu opracowanie inteligentnego prototypu robota do diagnozowania drzew cytrusowych (zdrowych lub zainfekowanych) za pomocą algorytmu konwolucyjnej sieci neuronowej (CNN). Wyniki trafności klasyfikacji wyniosły 96%. Następnie, po spryskaniu dotkniętych obszarów pestycydami, wszyscy rolnicy w kraju mogą go użyć do ochrony przed niebezpieczeństwami związanymi z pestycydami. Wyniki były dobre i obiecujące.

Słowa kluczowe

EN

CNN; agri-Robot; citrus dieases; Jetson nano

PL

robot ogrodowy; opryskiwanie; przetwarzanie obrazu

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2023
• Tom: R. 99, nr 8
• Strony: 98--101
• Opis fizyczny: Bibliogr. 25 poz., rys., tab.

Twórcy

autor

Mohammed Emad A.

• Department of Computer Techniques Engineering, Technical Engineering College, Northern Technical University, Mosul, Iraq

autor

Mohammed Ghasaq H.

• Department of Computer Techniques Engineering, Technical Engineering College, Northern Technical University, Mosul, Iraq

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).