AgriAid: Android-based Crop Disease Detection and Advisory System

Agriculture faces mounting threats from plant diseases that significantly reduce yields and incomes for smallholder farmers. AgriAid is an Android-based application that provides offline, on-device crop leaf disease diagnosis using multiple optimized TensorFlow Lite (TFLite) models. The application supports several crops and executes real-time inference on resource-constrained devices, delivering high accuracy and low latency under varied field conditions. This paper presents the system design, model integration approach, implementation details, and empirical performance metrics obtained through extensive testing.

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Publication Details

Journal
Iconic Research and Engineering Journals
Published
2025-12-20
DOI
https://doi.org/10.64388/irev9i6-1713011
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.00
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article

AgriAid: Android-based Crop Disease Detection and Advisory System

Md Zulquar Nain, Tasaduque Ullah, Mohd Ayman Khan, Mrs. Mumtaj K P et al.
Iconic Research and Engineering Journals
Smart Agriculture and AI
article

AgriAid: Android-based Crop Disease Detection and Advisory System

Md Zulquar Nain, Tasaduque Ullah, Mohd Ayman Khan, Mrs. Mumtaj K P, Muhammad Umar Maniyar
article en

Abstract

Agriculture faces mounting threats from plant diseases that significantly reduce yields and incomes for smallholder farmers. AgriAid is an Android-based application that provides offline, on-device crop leaf disease diagnosis using multiple optimized TensorFlow Lite (TFLite) models. The application supports several crops and executes real-time inference on resource-constrained devices, delivering high accuracy and low latency under varied field conditions. This paper presents the system design, model integration approach, implementation details, and empirical performance metrics obtained through extensive testing.

Iconic Research and Engineering JournalsVol. 9(6)
Openalex Percentile: Top 25%
Smart Agriculture and AI
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