Egg Incubation Automated Hatching System Naïve Bayesian

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Dr. Somu. K; Dhevika.P; Jayalakshmi.R; Sneha.M; Subashini.S

Egg Incubation Automated Hatching System Naïve Bayesian

Authors: Dr. Somu. K, Dhevika.P, Jayalakshmi.R, Sneha.M, Subashini.S

Unique Paper ID: 179941
Volume: 11
Issue: 12
PageNo: 8852-8857

Keywords: Naïve Bayesian data preprocessing data normalization Estimation of dew-point temperature data classification.

Abstract:
In recent times, efficient egg incubation has become crucial to ensuring the success of poultry breeding operations. Early detection and continuous monitoring of egg automatic detection using Artificial Intelligence (AI) can be costly. To address the challenges related to the Naïve Bayes Classification Method, early detection and automation of egg incubation yield more accurate results, and the collection of documents is more secure. Moreover, Min Max Normalization eliminates duplicate data, minimizes unknown data, and maximizes valuable data during the preprocessing phase. Additionally, the Estimation of dew-point temperature measures humidity and vapor and tests the ratio between the processes. Ultimately, the proposed method classifies data, tests it, and validates the predicted data for performance. Calculation is a training process, while the testing data is multi-level in the classification process. Each type of data is given for the individual network connection of the classification data. It calculates comprehensive monitoring based on input data from video testing of the training data. Initially, it identifies nearby objects, children, and other elements to assess the effectiveness of these activities. The process offers greater reliability and achieves high performance while maintaining standard scalability. These techniques reduce time complexity, and performance remains within an accurate range of 91%.

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Cite This Article

ISSN: 2349-6002
Volume: 11
Issue: 12
PageNo: 8852-8857

Egg Incubation Automated Hatching System Naïve Bayesian

Available:https://ijirt.org/article?manuscript=179941

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