Page 155 - AI for Good-Innovate for Impact

AI for Good-Innovate for Impact

modeling, our system forecasts potential disease outbreaks, enabling farmers to take proactive
measures to safeguard their flocks' health. By preemptively addressing disease threats, we
mitigate risks to food production, thereby contributing to SDG 2's goal of ensuring access to
safe, nutritious, and sufficient food for all. 35-CMU Africa

Furthermore, utilizing AI-powered insights enables farmers to improve feed management,
ultimately boosting the efficiency of meat and egg production. Through harnessing data on
environmental conditions and indicators of poultry health, our system enables farmers to make
informed decisions, leading to increased productivity and optimized resource utilization.
This approach is in line with SDG 12's objective of promoting sustainable consumption and
production patterns by reducing food waste and enhancing resource efficiency in agricultural
operations.

By integrating AI into poultry farming practices, our initiative not only addresses immediate
nutritional needs but also fosters long-term sustainability, advancing progress towards
achieving SDGs 2 and 12. Through collaboration with stakeholders and leveraging digitalization
technologies, we aspire to transform poultry farming in Rwanda, promoting food security,
sustainable practices, and responsible consumption.

35�2�2� Future work

Data collection, Model development, Create new variations/extensions to the same use case,
Standards development related to the use case Elaborate proposal: The sequence diagram
illustrates the data flow originating from sensors positioned at nodes within poultry houses.
It depicts the intermittent transmission of this data to a database, alongside the triggering of
alert SMS (using a GSM module connected to the microcontroller) notifications to farmers in
the event of critical conditions. The green blocks in the diagram denote areas earmarked for
future development. Our future work will encompass initial system design, prototype testing in
collaboration with the Poultry Association Rwanda and the Agriculture and Animal Resources
Development Board (RAB), as well as data analysis and model training tailored to the needs of
indigenous and exotic poultry farming. We aspire to promote structured poultry farm systems
integrated with digitalization technologies, leveraging insights from existing digitalized farms
and expertise from governmental agencies, agricultural associations, and health professionals.
Through this collaborative effort, we aim to revolutionize poultry farming in Rwanda, enhancing
productivity, sustainability, and ultimately, food security. Our goal is to provide healthy poultry
products to safeguard the health of children and others who rely on poultry farms.

This use case is designed to seamlessly integrate with the farmers' current infrastructure,
minimizing the need for extensive modifications. This is important to reduce the cost of
implementation for local chicken farmers. By leveraging existing setups, the objective is to
foster rapid adoption and implementation.

35�3� Use case requirements

• ECN-UC35-REQ-001: It is critical that the Empowering Childhood Nutrition project
addresses the availability of quality poultry products for children's development and
nutritional deficiencies, especially in developing countries like Rwanda. The project
should also address challenges in poultry farming such as disease outbreaks, heat stress,
theft, and predation.

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