YieldAI – AI-Powered Tomato Yield Prediction Mobile Application

YieldAI – AI-Powered Tomato Yield Prediction Platform

Project Overview

We are looking for experienced freelance developers and AI engineers to develop YieldAI, an intelligent mobile application designed to predict tomato crop yields using agricultural data, historical production records, and climatic conditions.

The platform will leverage Artificial Intelligence, Machine Learning, Deep Learning, and Data Science to provide accurate yield predictions and help farmers make better agricultural decisions.

1. Mobile Application – Frontend

Technology: React Native + TypeScript

Requirements:

- Cross-platform Android and iOS application.
- Modern and user-friendly interface.
- Farmer registration and authentication.
- Agricultural data collection and management.
- Integration with weather and climate data.
- Interactive dashboards and data visualization.
- Display of AI-based tomato yield predictions.
- Integration with backend microservices through REST APIs.

2. AI & Machine Learning Microservices

Technology: Python

We will develop independent Python microservices dedicated to AI, Machine Learning, Deep Learning, and Data Science.

Required expertise:

- Python and Data Science.
- Machine Learning and Predictive Modeling.
- Deep Learning and Neural Networks.
- LightGBM.
- XGBoost.
- Neural Network architectures.
- Feature Engineering and Data Preprocessing.
- Model Training, Validation, and Evaluation.
- Model Optimization and Fine-Tuning.
- Predictive analytics using agricultural and climatic datasets.

The objective is to build and compare different prediction models to identify the most accurate approach for estimating tomato crop yields.

3. Backend Architecture

Technology: Laravel + Microservices

Requirements:

- Laravel backend services.
- RESTful API development.
- Authentication and authorization.
- Communication between microservices.
- Agricultural data management.
- Integration with Python AI services.
- Secure and scalable backend architecture.

4. Database

Technology: MongoDB

Requirements:

- Database architecture and data modeling.
- Storage of agricultural and climatic datasets.
- Management of farmer profiles and farm information.
- Storage of historical crop production data.
- Efficient querying and data processing.

5. DevOps & Deployment

Technologies: Docker and Kubernetes

Requirements:

- Docker containerization.
- Kubernetes orchestration.
- Microservices deployment.
- CI/CD automation.
- Automated testing and deployment pipelines.
- Monitoring, scalability, and system reliability.

6. Expected Deliverables

- Fully functional React Native mobile application.
- Laravel backend microservices.
- Python AI/ML microservices.
- Trained and evaluated tomato yield prediction models.
- MongoDB database integration.
- Dockerized application components.
- Kubernetes deployment infrastructure.
- Technical documentation and source code.

7. Required Freelancer Profiles

We are interested in developers with expertise in one or more of the following areas:

1. React Native / TypeScript Mobile Developer.
2. Python AI / Machine Learning Engineer.
3. Data Scientist specializing in predictive modeling.
4. Laravel Backend / Microservices Developer.
5. DevOps Engineer specializing in Docker and Kubernetes.

Candidates should provide their technical experience, relevant projects, GitHub profile or portfolio, and estimated hourly rates.

We are looking for serious technical collaborators interested in building a scalable AI-powered agricultural technology platform. Long-term collaboration opportunities are available.