Performance Analysis of an Innovative Duct-Based Automatic Forced Air Chicken Egg Incubator Using Predictive Analytics

Abstract

The demand for the high-performance automatic chicken egg incubator models is high in the small-scale poultry farm sector. There are reasons to avoid conventional incubator models and in turn gives rise to innovative machines. It was identified that the percentage of hatching is average in the existing small-scale conventional incubators. This article is about performance analysis of an innovative duct-based automatic forced air chicken egg incubator using predictive analytics. It employs multiple regression, Chi-square test, and paired t test models and analyzes the performance of an innovative incubator in which we use an artificial hatching process of 40 to 50 fertile chicken eggs and its performance is compared with conventional model of hatching. The conventional artificial model and the innovative duct model were used for the complete analysis during the incubation period of 21 days. The hatching parameters, such as incubation temperature and relative humidity, were maintained throughout the hatching process. The major issue of any existing incubator models is the hatching rate. It is resolved using the innovative duct-based model whereas the optimum incubation temperature is received by all the eggs present inside the incubator for 21 days. Automation is performed using embedded system for monitoring and control. The mathematical analysis on the hatching percentage of the two models based on the distance of the eggs placed from the heat source inside the incubator offers better results that the duct-based model is efficient in hatching healthy day-old chicks.