Grow More. Waste Less.
Decide with Data.
Drone-imagery crop health analysis, yield prediction, automated irrigation, and market-linked planting recommendations. AI tuned for variable field, weather, and market conditions.
Research-Grade Agriculture AI.
Real-world research projects and production deployments demonstrating our depth in precision farming, closed-loop ecosystems, and machine learning for agriculture.
AI-Driven Integrated Modern Farming Ecosystem
Leveraging Emotional and Artificial Intelligence in the Workplace as an Inclusive Decision-Making Tool for Boosting Food and National Security
Designed a closed-loop smart agriculture platform during the 2026 Istanbul training hosted by Prospect Development Services (UK) and WOFAN (Nigeria), aligning aquaculture, poultry, and vertical farming under unified AI automation.
- Mapped interconnected aquaculture, poultry, and vertical farming subsystems with shared water, nutrient, and data cycles
- Implemented edge and cloud AI pipelines using CNN, LSTM, XGBoost, and reinforcement learning for predictive operations
- Engineered 90–95% water reuse through centralized mechanical, bio, UV, and RO filtration loops
- Created circular nutrient flows leveraging fish waste, crop residues, and black soldier fly cultivation for feed
- Delivered a modular deployment roadmap covering feasibility, infrastructure rollout, and commercial production milestones
Intelligent Agricultural Decision-Support Platform
Crop and fertilizer recommendation systems with plant disease detection from leaf imagery
Development of an intelligent agricultural decision-support platform integrating crop and fertilizer recommendation systems with plant disease detection — deployed as a production-ready web application.
- Built crop and fertilizer recommendation models using scikit-learn trained on soil composition and climate features
- Implemented a plant disease detection module from leaf images using CNNs (ResNet-9, PyTorch) with high classification accuracy across multiple crop types
- Deployed within a Flask web application for accessible, browser-based inference
- Achieved high accuracy in disease classification across multiple crop types
What Slows Smart Farming Today.
Variable Conditions
Field, weather, and market variability defeat static planting and irrigation plans.
Late Stress Detection
Crop stress visible from the ground is already days behind drone-detectable signals.
Margin Pressure
Input costs rise faster than commodity prices in most cycles.
Where AI Earns Its Place.
Deploy precision instruments across your entire operation, fully integrated with the NovaFekra platform.
Drone Imagery Crop Health
Multispectral analysis flags stress, disease, and irrigation gaps.
Yield Prediction
Field-level yield forecasts driven by phenology, weather, and history.
Automated Irrigation
Soil-moisture and ET-driven irrigation control with manual override.
Market-Linked Planting
Recommendations consider input costs, expected yield, and forward prices.
Every Zone. Every Variable.
Interactive field console providing real-time data at the meter level.
Before. After. Measured.
1,400-Hectare Operation Transition.
A 1,400-hectare operation enabled drone analysis and predictive irrigation.
Before
Irrigation followed a fixed weekly schedule across the entire farm.
After
Per-zone irrigation responded to soil moisture and ET. Water use dropped while yield rose.
Your Fields Are Already Sending Signals.
Join operations already powered by NovaFekra intelligence. Talk to an agronomist and deploy in as little as 48 hours.
Talk to an Agronomist Serving operations across North Africa, Europe, and beyond.