Page 214 - AI for Good-Innovate for Impact Final Report 2024
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AI for Good-Innovate for Impact



                      50�2� Use-case Description


                      50�2�1� Description


                      Our use case focuses on revolutionising crop monitoring in agriculture by combining satellite
                      imagery and artificial intelligence (AI). Traditional methods of crop monitoring are time-
                      consuming, labour intensive, and prone to human error, limiting farmers' ability to detect and
                      address issues in a timely manner. In leveraging satellite imagery and AI algorithms, we aim
                      to provide farmers with accurate and timely information to optimise their farming enterprises.


                      The use case addresses the problem of inefficient and inadequacy of crop monitoring methods.
                      Manual observation and sampling techniques are limited in their coverage and can miss crucial
                      information. This leads to reduced yields and economic losses due to undetected crop diseases,
                      nutrient deficiencies, or pest infestations. Our solution aims to overcome these limitations by
                      utilising satellite imagery and AI to provide a comprehensive and bird's eye view of crop fields.

                      The benefits are significant. Real-time and continuous monitoring of crop health across
                      large farming areas is made possible. This enables farmers to detect early signs of possible
                      challenges and take prompt action. Furthermore, AI algorithms can analyse complex satellite
                      imagery data and extract valuable insights that may not be apparent to the human eye. This
                      empowers farmers to make data-driven decisions regarding irrigation, fertiliser application,
                      and pest control, resulting in improved crop yields and resource management.

                      However, there are certain drawbacks to consider. The effectiveness of the AI-based approach
                      relies on the availability of high-quality satellite imagery and accurate ground truth data for
                      training the AI models. Limited access to such data, particularly in remote and underdeveloped
                      regions like Zimbabwe, can be a challenge. There are also initial setup and implementation
                      costs associated with acquiring satellite data and developing AI models, which may pose a
                      barrier for some farmers.

                      In conclusion, our use case aims to address the limitations of existing crop monitoring methods
                      by providing farmers with accurate and timely information. We aim to optimise farming, increase
                      yields, and contribute to sustainable food production. While there are challenges, the potential
                      benefits for farmers and the agricultural industry as a whole make it a promising solution for
                      improving crop monitoring and management.

                      UN Goals:

                      •    SDG 1: No Poverty,
                      •    SDG 2: Zero Hunger,
                      •    SDG 8: Decent Work and Economic Growth,
                      •    SDG 9: Industry, Innovation and Infrastructure,
                      •    SDG 13: Climate Action,
                      •    SDG 14: Life Below Water,
                      •    SDG 15: Life on Land,
                      •    SDG 17: Partnerships to achieve the Goal

                      Justification UN Goals selection: SDG 1 (No Poverty): The use of satellite imagery and AI in
                      crop monitoring enhances agricultural productivity and income opportunities for farmers.
                      By providing timely insights on crop health and management, the technology helps farmers
                      protect their crops from diseases and optimize yields, thereby reducing economic losses and



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