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Title: :  CITRUS PEST DISEASE RECOGNITION APP
PaperId: :  23093
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 10 Issue 2 2024
DUI:    16.0415/IJARIIE-23093
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
ATHISH S RBannari Amman Institute of Technology
RAAGAVENDIRAN M Bannari Amman Institute of Technology
PRITHVI RAJ L Bannari Amman Institute of Technology
KALAIVANI EBannari Amman Institute of Technology

Abstract

Computer Engineering
Deep Learning, Citrus Pests, Recurrent Neural Network, Convolutional Neural Network, Flutter , Dart 
Citrus crops play a crucial role in global agriculture and economy, but they are constantly threatened by various pests and diseases, posing significant challenges to growers. Early detection and accurate identification of pest diseases are crucial for effective management and mitigation strategies. This abstract presents a mobile application designed to address this pressing issue by leveraging the power of artificial intelligence (AI) and image recognition technology. The Citrus Pest Disease Recognition App utilizes advanced machine learning algorithms to identify and classify common pests and diseases affecting citrus crops. Through the integration of image recognition technology, users can simply capture images of affected citrus plants using their smartphones or tablets. The captured images are then processed by the app, which employs a trained AI model to analyze the symptoms and patterns indicative of specific pests or diseases. The app provides real-time feedback, promptly alerting users to the presence of potential threats in their citrus orchards. By accurately identifying the pest or disease, growers can swiftly implement appropriate management measures, such as targeted pesticide application or cultural practices, thus minimizing crop damage and ensuring optimal yield and quality. Furthermore, the Citrus Pest Disease Recognition App offers additional features such as pest and disease information, management recommendations, and integration with existing agricultural databases. This comprehensive tool empowers growers with valuable knowledge and resources to effectively combat pest infestations and disease outbreaks, ultimately contributing to the sustainability and resilience of citrus cultivation worldwide. In conclusion, the Citrus Pest Disease Recognition App represents a significant advancement in agricultural technology, providing growers with a user-friendly and efficient solution for early pest and disease detection. By harnessing the capabilities of AI and image recognition, this app has the potential to revolutionize citrus crop management practices, promoting sustainable agriculture and safeguarding global citrus production.

Citations

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IJARIIE ATHISH S R, RAAGAVENDIRAN M , PRITHVI RAJ L , and KALAIVANI E. "CITRUS PEST DISEASE RECOGNITION APP" International Journal Of Advance Research And Innovative Ideas In Education Volume 10 Issue 2 2024 Page 2519-2528
MLA ATHISH S R, RAAGAVENDIRAN M , PRITHVI RAJ L , and KALAIVANI E. "CITRUS PEST DISEASE RECOGNITION APP." International Journal Of Advance Research And Innovative Ideas In Education 10.2(2024) : 2519-2528.
APA ATHISH S R, RAAGAVENDIRAN M , PRITHVI RAJ L , & KALAIVANI E. (2024). CITRUS PEST DISEASE RECOGNITION APP. International Journal Of Advance Research And Innovative Ideas In Education, 10(2), 2519-2528.
Chicago ATHISH S R, RAAGAVENDIRAN M , PRITHVI RAJ L , and KALAIVANI E. "CITRUS PEST DISEASE RECOGNITION APP." International Journal Of Advance Research And Innovative Ideas In Education 10, no. 2 (2024) : 2519-2528.
Oxford ATHISH S R, RAAGAVENDIRAN M , PRITHVI RAJ L , and KALAIVANI E. 'CITRUS PEST DISEASE RECOGNITION APP', International Journal Of Advance Research And Innovative Ideas In Education, vol. 10, no. 2, 2024, p. 2519-2528. Available from IJARIIE, http://ijariie.com/AdminUploadPdf/CITRUS_PEST_DISEASE_RECOGNITION_APP_ijariie23093.pdf (Accessed : ).
Harvard ATHISH S R, RAAGAVENDIRAN M , PRITHVI RAJ L , and KALAIVANI E. (2024) 'CITRUS PEST DISEASE RECOGNITION APP', International Journal Of Advance Research And Innovative Ideas In Education, 10(2), pp. 2519-2528IJARIIE [Online]. Available at: http://ijariie.com/AdminUploadPdf/CITRUS_PEST_DISEASE_RECOGNITION_APP_ijariie23093.pdf (Accessed : )
IEEE ATHISH S R, RAAGAVENDIRAN M , PRITHVI RAJ L , and KALAIVANI E, "CITRUS PEST DISEASE RECOGNITION APP," International Journal Of Advance Research And Innovative Ideas In Education, vol. 10, no. 2, pp. 2519-2528, Mar-App 2024. [Online]. Available: http://ijariie.com/AdminUploadPdf/CITRUS_PEST_DISEASE_RECOGNITION_APP_ijariie23093.pdf [Accessed : ].
Turabian ATHISH S R, RAAGAVENDIRAN M , PRITHVI RAJ L , and KALAIVANI E. "CITRUS PEST DISEASE RECOGNITION APP." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 10 number 2 ().
Vancouver ATHISH S R, RAAGAVENDIRAN M , PRITHVI RAJ L , and KALAIVANI E. CITRUS PEST DISEASE RECOGNITION APP. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2024 [Cited : ]; 10(2) : 2519-2528. Available from: http://ijariie.com/AdminUploadPdf/CITRUS_PEST_DISEASE_RECOGNITION_APP_ijariie23093.pdf
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