WEED DETECTION ON CARROTS USING CONVOLUTIONAL NEURAL NETWORK AND INTERNET OF THING BASED SMARTPHONE

Lintang Patria


Universitas Terbuka (Indonesia)

Aceng Sambas


Universitas Muhammadiyah Tasikmalaya (Indonesia)

Ibrahim Mohammed Sulaiman


Universiti Utara Malaysia (Malaysia)

Mohamed Afendee Mohamed


Universiti Sultan Zainal Abidin (Malaysia)

Volodymyr Rusyn

rusyn_v@ukr.net
Yuriy Fedkovych Chernivtsi National University, Department of Radio Engineering and Information (Ukraine)
https://orcid.org/0000-0001-6219-1031

Andrii Samila


Yuriy Fedkovych Chernivtsi National University (Ukraine)

Abstract

This study proposes a method based on Convolutional Neural Network (CNN) for automated detection of weed in color image format. The image is captured and transmitted to the Internet of Thing (IoT) server following an HTTP request made through the internet which is made available using the GSM based modem connection. The IoT Server save the image inside server drive and the results are displayed on the smartphone (Vision app). The results show that carrot and weed detection can be monitored accurately. The results of the study are expected to provide assistance to farmers in supporting smart farming technology in Indonesia.


Keywords:

weed detection, convolutional neural network, Internet of Thing, smartphone

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Published
2024-09-30

Cited by

Patria, L., Sambas, A., Sulaiman, I. M., Mohamed, M. A., Rusyn, V., & Samila, A. (2024). WEED DETECTION ON CARROTS USING CONVOLUTIONAL NEURAL NETWORK AND INTERNET OF THING BASED SMARTPHONE. Informatyka, Automatyka, Pomiary W Gospodarce I Ochronie Środowiska, 14(3), 96–100. https://doi.org/10.35784/iapgos.5968

Authors

Lintang Patria 

Universitas Terbuka Indonesia

Authors

Aceng Sambas 

Universitas Muhammadiyah Tasikmalaya Indonesia

Authors

Ibrahim Mohammed Sulaiman 

Universiti Utara Malaysia Malaysia

Authors

Mohamed Afendee Mohamed 

Universiti Sultan Zainal Abidin Malaysia

Authors

Volodymyr Rusyn 
rusyn_v@ukr.net
Yuriy Fedkovych Chernivtsi National University, Department of Radio Engineering and Information Ukraine
https://orcid.org/0000-0001-6219-1031

Authors

Andrii Samila 

Yuriy Fedkovych Chernivtsi National University Ukraine

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