AI/ML Research Support for Smart Irrigation Project – Completion by 14 August

I am developing an AI-based smart irrigation prototype for Dubai conditions. The system will combine soil-moisture sensor data with historical weather, current weather and forecast data from APIs to predict irrigation requirements. I am looking for your support primarily on the AI/ML and research side, including: * Designing the AI/ML architecture * Collecting and preparing historical and forecast weather data * Building models such as XGBoost, Random Forest and LSTM/GRU * Predicting soil moisture and irrigation requirements * Implementing evapotranspiration and soil-water balance calculations * Developing an LLM/RAG layer to explain irrigation recommendations * Comparing rule-based, ML-based and LLM-assisted approaches * Evaluating results and preparing clear technical documentation * Integrating the models into a basic Streamlit dashboard A separate IoT engineer will handle the ESP32, sensors, pump and physical hardware. Your role would be to lead the data science, modelling, LLM integration and research evaluation. The target completion date is 14 August 2026. Please let me know whether this scope matches your experience, your availability, proposed approach and estimated cost.