Smart poultry farm using internet of things and machine learning project

Abstract

This paper offers a detailed investigation into poultry health monitoring utilizing an Internet of Things (IoT) platform and Machine Learning (ML) approaches. This article offers a detailed investigation into poultry health monitoring utilizing an Internet of Things (IoT) platform and Machine Learning (ML) approaches. The rising availability of low-cost processing resources, IoT sensors, and standard algorithms has made it appealing to use current technology to continually monitor big farms with millions of birds and enhance overall production. This model collects temperature, humidity, gasses, luminosity, and wind speed data and stores them in a cloud database. Using the dataset, the machine learning classification algorithms Nave Bias (NB), Support Vector Machine (SVM), and Random Forest (RF) perform and predict poultry health properly. This model predicts the best option for the birds' comfort throughout their life cycle and can use IoT to control lights, fans, sprinklers, and curtains automatically. By applying modern technologies in the poultry farm it can reduce bird problems like contagious diseases and identify more quickly. As a result, it yields better-quality poultry meat and eggs. Also, poultry farm diseases are communicable and contagious, this automation system protects the health of human workers.