“AgriVision” A Flutter -Based Application for RealTime Detection of Pesticides Residues on Fruits

“AgriVision” is a Flutter-based mobile application designed to address the critical issue of pesticide contamination on fruits. The application utilizes real-time image processing and machine learning techniques to detect pesticide residues on the surface of various fruits, ensuring food safety and healthstandards. By capturing and analyzing images through a smartphone camera, the app provides instant and reliablefeedback on the presence of harmful chemicals. The user-friendly interface, combined with the portability of the solution, offers farmers, consumers, and vendors a practical tool to assess fruit quality and promote safer agricultural practices. This project aims to contribute to healthier food choices and enhance consumer safety. Key Words: AgriVision , Flutter application , Real-time detection , Pesticide residues , Fruits , Agricultural technology , Pesticide detection , Mobile app , Food safety , AgriTech , Image processing , Machine learning , Smart agriculture , Fruit quality analysis.

Authors

Publication Details

Journal
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Published
2024-11-06
DOI
https://doi.org/10.55041/ijsrem38435
Primary Topic
Spectroscopy and Chemometric Analyses
Type
article
Field-Weighted Citation Impact
0.00
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article

“AgriVision” A Flutter -Based Application for RealTime Detection of Pesticides Residues on Fruits

A. M. Sonkamble, S. D. Biradar, Vaishnavi Thombare, Sayali Thopate
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Spectroscopy and Chemometric Analyses
article

“AgriVision” A Flutter -Based Application for RealTime Detection of Pesticides Residues on Fruits

A. M. Sonkamble, S. D. Biradar, Vaishnavi Thombare, Sayali Thopate
article en

Abstract

“AgriVision” is a Flutter-based mobile application designed to address the critical issue of pesticide contamination on fruits. The application utilizes real-time image processing and machine learning techniques to detect pesticide residues on the surface of various fruits, ensuring food safety and healthstandards. By capturing and analyzing images through a smartphone camera, the app provides instant and reliablefeedback on the presence of harmful chemicals. The user-friendly interface, combined with the portability of the solution, offers farmers, consumers, and vendors a practical tool to assess fruit quality and promote safer agricultural practices. This project aims to contribute to healthier food choices and enhance consumer safety. Key Words: AgriVision , Flutter application , Real-time detection , Pesticide residues , Fruits , Agricultural technology , Pesticide detection , Mobile app , Food safety , AgriTech , Image processing , Machine learning , Smart agriculture , Fruit quality analysis.

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTVol. 08(11)
Zero hunger
Openalex Percentile: Top 82%
Spectroscopy and Chemometric Analyses
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