~/projects/smart-irrigation2023IoTMachine LearningPython
IoT-enabled Smart Irrigation in Aquaponics
Real-time sensor-driven crop optimization
research.pdf
Role
Lead Researcher & Engineer
Timeline
6 months
Year
2023
Type
Research
// Key Results
37%
Water Savings
12+
Sensors Deployed
94%
Prediction Accuracy
01 // The Problem
What was broken
Traditional irrigation in aquaponic systems wastes water and doesn't adapt to plant needs in real time, leading to inefficient yields and resource overuse.
02 // The Approach
How I thought about it
Designed a sensor network measuring soil moisture, pH, temperature, and water nutrient levels. Piped the data into a Python service that trains a regression model to predict optimal irrigation schedules.
03 // The Solution
What I built
A closed-loop irrigation controller that triggers watering only when multiple weighted sensor inputs cross a model-derived threshold. Paired with a live dashboard for researchers.
04 // The Impact
Outcomes & learnings
Published in Springer's Smart Trends in Computing and Communications series. The prototype reduced water consumption by 37% while maintaining equivalent crop yield.
// Tech Stack
PythonArduinoRaspberry PiTensorFlowMQTTGrafana