How much is PoultryGuard AI?

PoultryGuard AI is listed for sale at $500 USD.

PoultryGuard AI - Sell Project

Name: PoultryGuard AI
Price: 500 USD
Availability: InStock

Listed June 21, 2025

About PoultryGuard AI

AI tool that detects poultry diseases early using image-based diagnosis.

PoultryGuard AI – End-to-End MLOps for Poultry Disease Detection PoultryGuard AI is a fully operational, end-to-end machine learning project that detects poultry diseases using computer vision and deep learning. Deployed on Render and powered by transfer learning, it helps poultry farmers identify illnesses early from images—saving time, money, and livestock. Project Highlights: End-to-End MLOps Workflow: Covers the full pipeline—from data ingestion to deployment—with CI/CD, model tracking, and automated version control. Transfer Learning: Utilizes pre-trained CNN models to improve accuracy on limited poultry disease datasets. DVC Integration: Ensures reproducible experiments with tracked data, model versions, and pipeline stages. Modular & Scalable Architecture: Built with clean, reusable code for easy scaling or extension to other livestock. Dockerized & Production Ready: Served via Gunicorn, containerized with Docker, and deployed seamlessly to the cloud. User-Friendly Web App: Upload an image and get a prediction in seconds, with no technical setup required. Limitations & Future Potential: While the current model performs well, its generalization is limited by the size and diversity of the training dataset. With more annotated images and fine-tuning, this tool can be scaled into a reliable digital vet assistant for farms and agri-tech platforms.

Project details

Built with: Render,AI Powered,Python (Flask),python,ML,"HTML5",CSS/HTML,Asp.NET Core

Website: https://poultryguard-ai.onrender.com/

Next step: <h3>1. <strong>Improve Model Accuracy</strong></h3><ol><li data-list="bullet"><span class="ql-ui" contenteditable="false"></span>Collect and label a larger, more diverse poultry image dataset.</li><li data-list="bullet"><span class="ql-ui" contenteditable="false"></span>Train with data augmentation and fine-tuning strategies for better generalization.</li><li data-list="bullet"><span class="ql-ui" contenteditable="false"></span>Introduce multi-label classification for co-infections or early-stage symptoms.</li></ol><h3>2. <strong>Expand to Mobile & Offline Access</strong></h3><ol><li data-list="bullet"><span class="ql-ui" contenteditable="false"></span>Convert the model using TensorFlow Lite or TensorFlow.js for mobile or edge deployment.</li><li data-list="bullet"><span class="ql-ui" contenteditable="false"></span>Build a mobile app to allow farmers to capture images and get predictions in the field—even offline.</li></ol><h3>3. <strong>Integrate with Farm Management Systems</strong></h3><ol><li data-list="bullet"><span class="ql-ui" contenteditable="false"></span>Add features like disease history tracking, prescription suggestions, or vet alerts.</li><li data-list="bullet"><span class="ql-ui" contenteditable="false"></span>Offer integration with existing agri-tech tools or IoT-based monitoring platforms.</li></ol><h3>4. <strong>Commercialize as SaaS or B2B Tool</strong></h3><ol><li data-list="bullet"><span class="ql-ui" contenteditable="false"></span>Launch as a subscription-based service for poultry farms, cooperatives, or veterinary clinics.</li><li data-list="bullet"><span class="ql-ui" contenteditable="false"></span>Offer API access for agricultural startups or NGOs.</li></ol><h3>5. <strong>Participate in Competitions or Grants</strong></h3><ol><li data-list="bullet"><span class="ql-ui" contenteditable="false"></span>Use the project to enter AI-for-Good or agri-tech competitions (e.g., Zindi, Omdena, XPRIZE).</li><li data-list="bullet"><span class="ql-ui" contenteditable="false"></span>Seek funding or grants from agricultural innovation organizations.</li></ol><h3>6. <strong>Add More Disease Categories or Species</strong></h3><ol><li data-list="bullet"><span class="ql-ui" contenteditable="false"></span>Extend the classifier to include additional bird diseases or other livestock.</li><li data-list="bullet"><span class="ql-ui" contenteditable="false"></span>Build a modular system to support multiple animal types.</li></ol><p><br></p>

For sale

Asking price: $500 USD

What's included

Source code, All related data

Full Source Code: Complete backend (FastAPI + TensorFlow) and frontend (HTML/CSS/Bootstrap) codebase with clear documentation. Trained Model Files: Exported TensorFlow/Keras models used in production. DVC Configuration: Data and model versioning setup for reproducibility. Deployment Setup: Dockerfile, Gunicorn config, and Render deployment instructions. CI/CD Pipeline: GitHub Actions workflow for automated testing and deployment. Sample Dataset (or link): Small labeled dataset for testing or retraining purposes. Documentation: README, API usage instructions, and architecture overview. Future Expansion Notes: Suggestions for mobile integration, model improvement, and scaling. If desired, I can also provide: Onboarding Session (1 hour) to walk the buyer through the codebase and deployment setup. Optional Support Period (e.g., 2 weeks of limited technical Q&A) after purchase.

Reason for selling

I am busy with other things and no longer have time to maintain this project.

Project metrics

Average Monthly Revenue: Undisclosed