Honey.AI
Objective:
Honey fraud—such as fake origin labels, misdeclared flower sources, or adulteration with sugar syrups—is a serious problem in Europe. Current methods to detect such frauds are expensive, slow, and require high-tech lab equipment and trained specialists. This leaves small-scale beekeepers, packers, and traders with limited tools to verify the authenticity of their honey or to protect themselves from fraud in the supply chain.
Solution:
The TITAN project is developing Honey.AI, a low-cost, AI-powered, IoT-enabled microscope that automates pollen analysis—a traditional method for identifying the origin and type of honey. By using computer vision and neural networks, Honey.AI can quickly analyze pollen in honey, helping detect fraud in real time and on-site, without the need for costly lab services. It can also flag unusual pollen types to detect possible mislabelling or imported (non-EU) honeys.
Benefits for Practitioners:
- Faster decisions: Get results in minutes instead of waiting 1–2 weeks for lab reports.
- Cost-effective: Avoid spending €150–€400 per sample for complex lab tests; Honey.AI is a more affordable screening option.
- On-site usability: Beekeepers, traders, and customs agents can test honey directly at their facilities.
- Consumer trust: Each tested batch can be linked to a QR code on the product label, giving consumers verified information about the honey’s origin and authenticity.
- Fraud prevention: Helps protect EU beekeepers from counterfeit imports and ensures fair pricing for genuine products.
- Future features: Honey.AI will also soon help diagnose bee diseases like Nosemosis, supporting hive health and long-term farm productivity.
Recommendation:
Practitioners across the honey value chain are encouraged to adopt this fast, user-friendly technology to increase transparency, reduce fraud, and support EU sustainable apiculture. Widespread use of Honey.AI could create a new benchmark in traceability and quality assurance for the honey sector.
Additional information
Author: Iratxe Perales
Microfy Systems (www.microfy.ai)
Transparency solutions for transforming the food system
Ongoing | 2022-2026
- Main funding source
- Horizon Europe (EU Research and Innovation Programme)
- Geographical location
- Belgium, Netherlands, Italy, Germany, Greece, Portugal, Spain, France, Finland, Poland, United Kingdom, Norway, Switzerland, Serbia