Turning Egypt's field data into decisions
An applied research unit at the Faculty of Agriculture, Kafrelsheikh University, bringing AI, IoT and computer vision to the farm, and incubating startups led by local graduates.
Agritech-AI
The Agritech-AI platform
The operational platform that takes the Unit's models to the field: irrigation and drainage scheduling on saline soils, aquaculture, and partner station data. Try the demo with simulated data.
Our targets
Figures from the strategic plan. They move to the achievements list once evidenced.
- 10
Specialised departments
Target by 2026
- 62
Specialists
Target by 2027
- 50
IoT stations on the research farm
Target by 2027
- 10feddan
Experimental field area
Target by 2027
- 200
Trainees per year
Target by 2027
- 6
Spin-off startups
Target by 2027
Startups spun out of the Unit
View all- Rewaa AgritechUnder evaluation
Smart irrigation and drainage management for saline soils.
- Cold-Chain StartupPlanned
Linking smallholder fruit and vegetable growers to exporters through a data-managed cold chain.
Managing farmer contracts with sugar factories and beet supply without conflicts between factories.
Early detection of red palm weevil with acoustic and thermal sensing.
- Digital Platform StartupPlanned
Building and operating the Unit's digital platform and offering its services to the farm sector.
- Smart Greenhouses StartupPlanned
Designing and managing smart greenhouses with climate control and automated irrigation.
Models that run on field data
Every model states its method, its data source and its status. Experimental models are never presented as operational.
- A1Leaching requirementAvailable
- A2Soil salinity forecastExperimental
- A3Water table forecast & drainage triggerExperimental
- A4Irrigation schedulingAvailable
- A5Salt-stress detection from imagesPlanned
- A6Field salt balanceAvailable
Ten departments, one system
Research departments
- AI & Machine Learning
Builds and trains the models that turn field data into precise, explainable farm decisions, across three units: deep learning, Arabic agricultural NLP, and data analytics.
- Computer Vision
Machine vision for plant disease detection, drone imaging, remote sensing (Sentinel-2, Landsat) and smart cameras for livestock monitoring.
- IoT & Embedded Systems
Designs and deploys the sensor networks that collect soil, water and climate data in real time, across four units: hardware, networks, power and firmware.
- App Development & Software
Turns research outputs into digital tools for farmers, researchers and decision-makers: mobile apps, web platforms and databases.
- Field Applications
The Unit's field arm: runs the research farm's experimental fields, greenhouses, aquaculture pond and livestock unit, and tests solutions under real field conditions.
Support departments
- Administration & Finance
Human resources, finance, procurement and contracts that keep the research departments running.
- Training & Capacity Building
Specialised AI and IoT training for students, engineers and farmers, in partnership with Navera.
- Partnerships & International Cooperation
Builds local and international partnerships and follows funding opportunities and MoUs.
- Media & Scientific Publishing
Supports publication in peer-reviewed journals and media coverage of the Unit's work.
- IT Infrastructure & Private Cloud
Runs the Unit's servers, platforms and cybersecurity, building towards a university private cloud.