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Rice disease identiﬁcation through leaf image and iot based smart rice fieldmonitoring system

Rice disease identification in early-stage, proper medication in case of disease affection and managing irrigation at the appropriate time is the most consequential phenomena to increase the production level of the rice. In this paper, a novel technique to diagnose the rice diseases and smart medica...

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Main Authors:	Islam, Md Nahidul, Ahmed, Fahim, Ahammed, Md Tanvir, Rashid, Mamunur, Bari, Bifta Sama
Format:	Conference or Workshop Item
Language:	English English
Published:	Springer Science and Business Media Deutschland GmbH 2022
Subjects:	T Technology (General) TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://umpir.ump.edu.my/id/eprint/39454/1/Rice%20Disease%20Identification%20Through%20Leaf%20Image%20and%20IoT%20Based%20Smart.pdf http://umpir.ump.edu.my/id/eprint/39454/2/Rice%20disease%20identi%EF%AC%81cation%20through%20leaf%20image%20and%20iot%20based%20smart%20rice%20fieldmonitoring%20system_ABS.pdf http://umpir.ump.edu.my/id/eprint/39454/ https://doi.org/10.1007/978-981-19-2095-0_45
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spelling	my.ump.umpir.394542023-12-01T01:05:34Z http://umpir.ump.edu.my/id/eprint/39454/ Rice disease identiﬁcation through leaf image and iot based smart rice fieldmonitoring system Islam, Md Nahidul Ahmed, Fahim Ahammed, Md Tanvir Rashid, Mamunur Bari, Bifta Sama T Technology (General) TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering Rice disease identification in early-stage, proper medication in case of disease affection and managing irrigation at the appropriate time is the most consequential phenomena to increase the production level of the rice. In this paper, a novel technique to diagnose the rice diseases and smart medication prescription system have been proposed. Furthermore, the internet of things (IoT) based smart rice field monitoring system has also been proposed. To identify rice diseases, the leaf image dataset (consists of healthy and three different diseases) has been analyzed through the convolutional neural network (CNN). The obtained rice disease diagnosis accuracy of the proposed system was 98.7%. In a real-time system, the leaf image data has been collected remotely using Raspberry Pi and the data has been sent to a server to be tested by a trained CNN model. Some sensors including soil moisture sensor, pressure sensor, humidity sensor, and temperature sensor have been implanted in the targeted field which aims to record the current scenario of the rice field and send the sensors data to the server. On a web page, proper medications have been displayed if any rice disease identified. Moreover, the user may monitor his field remotely which facilitates irrigation in opportune time. Springer Science and Business Media Deutschland GmbH 2022 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/39454/1/Rice%20Disease%20Identification%20Through%20Leaf%20Image%20and%20IoT%20Based%20Smart.pdf pdf en http://umpir.ump.edu.my/id/eprint/39454/2/Rice%20disease%20identi%EF%AC%81cation%20through%20leaf%20image%20and%20iot%20based%20smart%20rice%20fieldmonitoring%20system_ABS.pdf Islam, Md Nahidul and Ahmed, Fahim and Ahammed, Md Tanvir and Rashid, Mamunur and Bari, Bifta Sama (2022) Rice disease identiﬁcation through leaf image and iot based smart rice fieldmonitoring system. In: Lecture Notes in Electrical Engineering; Innovative Manufacturing, Mechatronics and Materials Forum, iM3F 2021, 20 September 2021 , Gambang. pp. 529-539., 900 (277979). ISSN 1876-1100 ISBN 978-981192094-3 https://doi.org/10.1007/978-981-19-2095-0_45
institution	Universiti Malaysia Pahang Al-Sultan Abdullah
building	UMPSA Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaysia Pahang Al-Sultan Abdullah
content_source	UMPSA Institutional Repository
url_provider	http://umpir.ump.edu.my/
language	English English
topic	T Technology (General) TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	T Technology (General) TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering Islam, Md Nahidul Ahmed, Fahim Ahammed, Md Tanvir Rashid, Mamunur Bari, Bifta Sama Rice disease identiﬁcation through leaf image and iot based smart rice fieldmonitoring system
description	Rice disease identification in early-stage, proper medication in case of disease affection and managing irrigation at the appropriate time is the most consequential phenomena to increase the production level of the rice. In this paper, a novel technique to diagnose the rice diseases and smart medication prescription system have been proposed. Furthermore, the internet of things (IoT) based smart rice field monitoring system has also been proposed. To identify rice diseases, the leaf image dataset (consists of healthy and three different diseases) has been analyzed through the convolutional neural network (CNN). The obtained rice disease diagnosis accuracy of the proposed system was 98.7%. In a real-time system, the leaf image data has been collected remotely using Raspberry Pi and the data has been sent to a server to be tested by a trained CNN model. Some sensors including soil moisture sensor, pressure sensor, humidity sensor, and temperature sensor have been implanted in the targeted field which aims to record the current scenario of the rice field and send the sensors data to the server. On a web page, proper medications have been displayed if any rice disease identified. Moreover, the user may monitor his field remotely which facilitates irrigation in opportune time.
format	Conference or Workshop Item
author	Islam, Md Nahidul Ahmed, Fahim Ahammed, Md Tanvir Rashid, Mamunur Bari, Bifta Sama
author_facet	Islam, Md Nahidul Ahmed, Fahim Ahammed, Md Tanvir Rashid, Mamunur Bari, Bifta Sama
author_sort	Islam, Md Nahidul
title	Rice disease identiﬁcation through leaf image and iot based smart rice fieldmonitoring system
title_short	Rice disease identiﬁcation through leaf image and iot based smart rice fieldmonitoring system
title_full	Rice disease identiﬁcation through leaf image and iot based smart rice fieldmonitoring system
title_fullStr	Rice disease identiﬁcation through leaf image and iot based smart rice fieldmonitoring system
title_full_unstemmed	Rice disease identiﬁcation through leaf image and iot based smart rice fieldmonitoring system
title_sort	rice disease identiﬁcation through leaf image and iot based smart rice fieldmonitoring system
publisher	Springer Science and Business Media Deutschland GmbH
publishDate	2022
url	http://umpir.ump.edu.my/id/eprint/39454/1/Rice%20Disease%20Identification%20Through%20Leaf%20Image%20and%20IoT%20Based%20Smart.pdf http://umpir.ump.edu.my/id/eprint/39454/2/Rice%20disease%20identi%EF%AC%81cation%20through%20leaf%20image%20and%20iot%20based%20smart%20rice%20fieldmonitoring%20system_ABS.pdf http://umpir.ump.edu.my/id/eprint/39454/ https://doi.org/10.1007/978-981-19-2095-0_45
_version_	1822923893056208896
score	13.232414

Rice disease identiﬁcation through leaf image and iot based smart rice fieldmonitoring system

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