Page 157 - AI for Good-Innovate for Impact Final Report 2024

AI for Good-Innovate for Impact

• ECN-UC35-REQ-002: It is critical that the project integrates sensor technology into poultry
farming practices. This includes monitoring environmental parameters (temperature,
humidity, ammonia gas levels) and capturing and analyzing chicken sounds for early
detection of threats and health monitoring.
• ECN-UC35-REQ-003: It is critical that the project leverages data-driven predictions and 35-CMU Africa
machine learning algorithms to optimize poultry farm management and increase the
productivity of poultry farms.
• ECN-UC35-REQ-004: It is critical that the project provides alert notifications to
farmers for timely interventions. This includes the use of a GSM module connected to
the microcontroller to trigger alert SMS notifications to farmers in the event of critical
conditions.
• ECN-UC35-REQ-005: It is critical that the project uses open-source chicken language
datasets (GitHub repositories), Kaggle, and both private and public data for model
training and fine-tuning. This includes temperature data, humidity data, ammonia gas
content data, and chicken sound recordings.

35�4� Sequence diagram

35�5� References

[1] Open source Chicken language dataset: link

[2] Google research- Chicken language dataset - link

[3] Audio set link / https:// research .google .com/ audioset/ dataset/ chicken _rooster .html

[4] Mendeley Data- link

[5] Open sourc animale sound dataset link

[6] Google search link

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