Development of Smart Poultry Farm Management System Using Geo-IoT

Abstract

Currently, poultry farmers from small-scale to industrial levels are well aware that
the problem of misshapen or spoiled eggs may be caused by unstable environmental conditions in the poultry house, such as excessive temperature or humidity. However, there is no alert system to notify farmers or farm managers of abnormal conditions so that they can promptly address these issues. This research aims to employ Internet of Things (IoT) technology to monitor and measure the environmental conditions within a poultry house measuring 17 meters in width and 80 meters in length. It uses spatial estimation techniques within the geographic information system (GIS) framework, specifically the Inverse Distance Weighting (IDW) method, to analyze the distribution of four parameters throughout the farm. The results of this research found that high temperature and humidity were related to the quality of farm eggs. The most common problem eggs are pale eggs and deformed eggs, and high ammonia gas levels are not related to the quality of farm eggs. High ammonia gas levels do not affect egg production, as problematic eggs were mostly found in areas with low ammonia gas levels, with pale eggs being the most common issue. Light intensity was used normally and influenced the hens' egg production, as adequate lighting is crucial for growth and stimulates the anterior pituitary gland in laying hens to secrete hormones necessary for egg production.