I’m a curious and driven student from Bénin with a deep passion for AI, machine learning, engineering, and Arduino. I love exploring how intelligent systems can solve real-world problems, especially in underserved communities. I’ve worked with TensorFlow Lite for Microcontrollers and enjoy blending software with hardware to create smart, efficient solutions. I’m inspired by innovation and eager to learn from others while sharing my own ideas. Being part of WaterTank is a chance for me to connect globally, grow technically, and contribute meaningfully to a more sustainable world.

In Benin, the water used for irrigation on several market gardening sites often comes from contaminated sources, such as unprotected wells, wastewater basins, or marshes. This water, sometimes laden with fecal coliforms, is then used to grow vegetables consumed raw, thus exposing consumers to invisible yet very real health risks.

One key solution for a sustainable future lies in making a low-cost water quality predictable and understandable especially for farmers who irrigate vegetables eaten raw. When those who grow our food can receive clear, timely information based on local water conditions, they move from uncertainty to confidence, from risk to responsibility. This kind of accessible, intelligent support system empowers producers to protect not only consumer health but also their own peace of mind. It turns invisible threats into visible knowledge, and everyday farming into a source of trust, pride, and safety.