The idealcrop system

Date
2021-12
Authors
Amutuhaire, Mujaidu
Kwizera, Nicholas
Nakasango, Shariffa
Wangota, Felix Daniel
Journal Title
Journal ISSN
Volume Title
Publisher
Makerere University
Abstract
This report is for the implementation of the IdealCrop System, from its design to completion. It is a web-based machine learning application that provides a service to farmers or farm managers, enabling them to make informed decisions on crop selection and care, and crop variety options to choose from while considering climatic factors, NPK soil nutrients, and best crop yield on a Ugandan district level.
Description
A project report submitted to the School of Computing and Informatics Technology for the study leading to a project in partial fulfillment of the requirements for the award of the Degree of Bachelor of Science in Software Engineering of Makerere University.
Keywords
Machine Learning, Farming, Crop
Citation
Amutuhaire, M., Kwizera, N., Nakasango, S., & Wangota, F. D. (2021). The idealcrop system. (Unpublished undergraduate dissertation). Makerere University, Kampala, Uganda.
URI
http://hdl.handle.net/20.500.12281/11824
Collections
School of Computing and Informatics Technology Collection