Proland

Proland is a machine learning solution aimed to solve inefficiency problem on agriculture and agriculture related activities. As a team who has a lot of farmer relatives, we observed that many farmers decide what to plant without considering what is more appropriate for their land, both economically and environmentally. Usually, they select one of the most profitable crops of last year or they regularly plant the same plant across generations without realizing effects of global warming on their soil and climate. Moreover, since almost everyone focuses on planting same products on small villages due to economic concerns or habits, lots of crops are wasted or sold to incredibly low prices and many products are transported from far regions even though their own farms are convenient to produce these products. Our ML model is built on Azure Machine Learning Studio using historical temperature, precipitation and ton/acre yield values. We tested our current model for different regions of Turkey and predicted the quantity harvested with 92.5 accuracy for different crops. Our cross-platform (UWP-Android and iOS) mobile application is currently developed using Xamarin.Forms. Visit our web page: www.prolandfarming.com

Our team consists of Eren Limon, Mediha Meltem Gunay and Ahmet Uysal. We all study computer and electrical-electronics engineering at Koç University. Our friendship originates from the IEEE Koc University Student Branch, where we took part in several activity and organizations together. Since Eren and Meltem took the related AI course at the university, they are mainly responsible from the Machine Learning part of the project. Ahmet’s passion for developing applications helps us to turn our dynamic ideas to a product in a short time. As 3, we took part in and won the HackFest at Koc University, which was organized by Microsoft Turkey. Our idea “Proland” arises from the experiences of families of our team members and this enables us to observe the issue in the field and to communicate directly with the population who experience the same problem.