Agri-pHLy UAV on stage at EIT Food Challenge Labs Macedonia 2025
Engineering Project EIT Food Grant Winner 2024–2025

Agri-pHLy

A precision agricultural UAV system combining real-time soil pH sensing, onboard telemetry, and automated lime-application flight paths — introducing data-driven precision agriculture to North Macedonia.

UAV Engineering Arduino / Embedded Precision Agriculture EIT Food Grant Python · MATLAB LoRa Telemetry
±0.2
pH measurement accuracy
EIT
Food competitive grant winner
1st
UAV precision agriculture in North Macedonia
Full
Autonomous flight path optimisation
Live
Real-time LoRa telemetry & dashboard

The problem

Soil pH is one of the most critical factors in crop productivity — yet conventional monitoring methods are slow, expensive, and spatially limited. Traditional land analysis costs over €100/ha and produces only sporadic, non-continuous data. Lime broadcasting is uniform and wasteful. Neither approach supports intelligent, field-specific intervention.

Agri-pHLy was designed to solve this: a complete UAV-based system that measures soil pH continuously across a field, maps the variation spatially, and autonomously applies corrective treatment only where needed.

What was built

The system integrates three core engineering layers into a single flight-capable platform:

  • pH sensing module — Arduino UNO with custom pH sensor integration, calibrated against professional reference instruments to achieve ±0.2 pH accuracy. The probe is mounted to make contact with the soil during low-altitude passes.
  • UAV platform — a custom-built heavy-lift hexacopter designed and assembled from carbon-fibre components, with a custom flight controller stack, GPS/magnetometer fusion for waypoint navigation, and a payload bay for the sensing and lime-application modules.
  • Telemetry & ground station — bidirectional 915 MHz LoRa link transmitting real-time pH readings, GPS position, altitude, and battery state to a Python Flask ground station dashboard. Live anomaly detection and post-flight analytics.
  • Autonomous flight path optimisation — MATLAB-based path planning algorithm that generates variable-rate application routes based on the pH heatmap, minimising input usage and maximising field coverage efficiency.

The Agri-pHLy team

The project was co-developed by Mario Blazevski (engineering lead — UAV design, embedded systems, flight controller, telemetry) and Iva Aleksovska (agronomy and sensor calibration lead), with mentorship from Vita Nova Consulting. The team presented the full working prototype — drone, sensor module, live dashboard, and autonomous path data — at the EIT Food Challenge Labs Macedonia 2025 Demo Day.

EIT Food grant & recognition

Agri-pHLy was selected as one of three winning startups at the EIT Food Challenge Labs Macedonia 2025 competition, organised by Vita Nova Consulting in partnership with EIT Food and co-funded by the European Union. The team was awarded a €500 innovation voucher to accelerate development.

The project is cited on the EIT Food website as a standout example of student-led agri-tech innovation in the Western Balkans region.

Impact

Agri-pHLy is the first UAV-based precision agriculture system demonstrated in North Macedonia — establishing a proof of concept for data-driven, variable-rate soil amendment that reduces input costs by an estimated 20–40% compared to uniform application methods while improving crop yield consistency.

Built from the
ground up

Sensing
pH Measurement System
Arduino UNOpH Sensor ModuleCalibration Ref.±0.2 Accuracy
Airframe
Custom UAV Platform
CFRP ArmsHexacopterCustom FC StackPayload Bay
Navigation
Autonomous Flight
GPS FusionMagnetometerWaypoint NavPure Pursuit
Telemetry
Ground Station Link
LoRa 915 MHzESP32Flask DashboardLive Anomaly Detect.
Path Planning
Variable Rate Application
MATLABpH HeatmapRoute OptimisationVRA Algorithm
Analysis
Data & Simulation
PythonNumPy / PandasMATLABSolar Irradiance

Solar irradiance
heatmap analysis

Seasonal and hourly solar irradiance data (kWh/m²) — used to optimise drone operational windows, solar-hybrid energy modelling, and flight campaign scheduling throughout the year.

Agri-pHLy solar irradiance heatmap — seasonal and hourly data analysis

Solar irradiance by hour and month — Agri-pHLy operational data. Peak values reach 64+ kWh/m² in July (10–12h). Annual operational window spans March–November.

Need a UAV system
built for your application?

We design and build custom UAV platforms — from sensor integration and embedded control to autonomous flight and telemetry. Get in touch to discuss your requirements.