As climate change threatens the survival of green areas in cities, parks must be watered frequently. However, accurately identifying areas that require watering is difficult and requires costly sensors. Excessive watering leads to a waste of both money and clean water. Therefore, efficient and precise watering strategies are necessary to ensure the sustainability of green areas in urban environments while also conserving water resources. Check out the Amsterdam Tree Map (maps.amsterdam.nl/bomen/) to get an idea of how many trees there are in a city.
Our proposed solution is to predict soil moisture in parks using machine learning, which will eliminate the need for expensive sensors. We plan to train the algorithm on past moisture levels from both sensors and satellites, allowing for accurate and efficient prediction. This approach will provide a cost-effective and reliable solution for identifying areas that need watering in parks, which will ultimately contribute to the sustainability of green areas in urban environments and conserve water resources. See our pitch deck here: https://tinyurl.com/treetune or below!