Ai Based Plant Disease Diagnosis

• Author(s):

  Suguna M | Prakash N | Prasanna Hari V | Rajesh R | Rathish S

• Keywords:

• Abstract:

  In The Agricultural Sector, Early And Accurate Detection Of Plant Diseases Plays A Vital Rolein Preventing Crop Loss And Ensuring Sustainable Food Production. However, Conventional Manual Diagnosis Methods Are Time-consuming, Error-prone, And Often Depend On Expert Availability, Which Is Limited In Rural Areas. The Plant Disease Diagnosis System Bridges This Gap Through An AI-driven, Image-based Diagnostic Platform That Utilizes Machine Learning (ML) And Deep Learning (DL) Techniques To Identify And Classify Plant Leaf Diseases With High Precision. The System Leverages Convolutional Neural Networks (CNNs) For Image Recognitionand Integrates Them Into A User-friendly Web Application Built Using The MERN (MongoDB, Express.js, React.js, Node.js) Stack. Users Can Upload Plant Leaf Images Directly From The Interface, And The Model Instantly Predicts The Disease Type Along With Possible Remedies. In Addition, Real-time Data Visualization And An Intuitive Dashboard Enable Agricultural Experts To Monitor Disease Trends Across Regions. From A Technological Standpoint, The Platform Ensures Secure Data Handling And Scalable Architecture, Allowing Seamless Deployment For Farmers, Agricultural Institutions, And Research Centers. By Merging AI Capabilities With A Human-centered Design, This Project Empowers Users To Take Proactive Decisions, Minimizing Crop Damage And Maximizing Yield. In Essence, The Plant Disease Diagnosis System Redefines Modern Agriculture By Combining Artificial Intelligence, Predictive Analytics, And Cloud Integration To Provide An Efficient, Accessible, And Sustainable Solution To Crop Disease Management. In The Modern Agricultural Landscape, Plant Health Monitoring And Early Disease Detection Have Become Critical To Ensuring Food Security, Minimizing Economic Losses, And Promoting Sustainable Farming Practices. Traditional Disease Identification Methods Rely Heavily On Expert Knowledge And Manual Inspection, Which Are Often Time-consuming, Expensive, And Inaccessible To Farmers In Remote Or Resource-limited Areas. To Address These Challenges, The Plant Disease Diagnosis System (PDDS) Presents An AI-powered, Image-based Diagnostic Solution That Leverages Machine Learning (ML) And Deep Learning (DL) Techniques To Automatically Detect And Classify Plant Leaf Diseases From Digital Images. Beyond Disease Detection, PDDS Supports Data-driven Agricultural Intelligence By Analyzing Disease Trends And Generating Regional Health Statistics, Which Can Aid Researchers And Government Bodies In Monitoring Outbreaks. By Integrating Ethical AI Principles, Data Privacy Protocols, And Responsive Design, The System Ensures Both Accuracy And Inclusivity For Farmers, Researchers, And Agricultural Stakeholders.

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Other Details

• Paper id:

  IJSARTV11I9104050

• Published in:

  Volume: 11 Issue: 9 September 2025

• Publication Date:

  2025-09-23

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