GreenBee

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Inspiration

GreenBee was born from a deep concern about the global decline of bee populations and its direct impact on food security and biodiversity. One of our co-founders comes from a family of beekeepers, which gave us firsthand insight into the challenges faced by the apiculture industry—especially in rural areas. We were inspired to merge technology with tradition to create a solution that supports both the environment and local communities.

What it does

GreenBee is a smart beekeeping solution that integrates AI, IoT, and satellite imaging to help beekeepers monitor hive health in real time, detect diseases early, and optimize hive placement. It also includes a biological pest control system using natural fungi, allowing for chemical-free protection of colonies. All data and recommendations are accessible through an easy-to-use web and mobile application.

How we built it

We started by developing a prototype smart hive equipped with sensors (temperature, humidity, weight, sound) and connected it to a microcontroller with GSM capabilities for real-time data transmission. We trained AI models to detect anomalies in hive behavior, integrated a biological control module using natural fungi, and added a satellite data layer to optimize hive locations. Our mobile/web platform was built to give beekeepers direct access to alerts and insights.

Challenges we ran into

• Accessing reliable environmental and satellite data to feed our AI models.
• Ensuring compatibility between electronic components in rural settings with limited connectivity.
• Making our system affordable while integrating high-end features.
• Educating beekeepers unfamiliar with digital tools on how to use the platform effectively.

Accomplishments that we're proud of

• Representing Morocco this Year in HultPrize Digital incubator (We Got Selected from 15000 Project)
• Successfully building and testing a full working prototype.
• Being selected in innovation programs such as Capgemini Tech Talent and WEF Nexus Tangier.

What we learned

We learned how powerful technology can be when applied to grassroots challenges, and how important it is to build solutions that are not only innovative but also practical and accessible. We also gained experience in hardware integration, machine learning model training, and user-centered design.

What's next for GreenBee

Next, we aim to run large-scale pilot programs with cooperatives and government partners, refine our AI algorithms with more data, and scale production. We're also planning to expand into other African and Mediterranean countries, develop a subscription-based model, and continue improving the environmental and economic impact of our solution.

Built With

• arduino
• css
• express.js
• html5
• iot
• javascript
• machine-learning
• node.js
• python
• react-native
• vue