Analysis of Honey Production with Environmental Variables

Atagün, Ercan; Aalbayrak, Ahmet

doi:10.1109/ubmk52708.2021.9558933

Cited by 1 publication

(1 citation statement)

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“…Analysis of honey production with environmental variables [42] SVM, Multi-layer perceptron regressor, Random forest regressor, K-neighbors regressor, Voting regressor, Ada boost regressor, Gradient boosting regressor.…”

Section: Random Tree Regression Algorithmmentioning

confidence: 99%

A review on internet of things-based stingless bee's honey production with image detection framework

Rohafauzi,

Kassim,

Ja’afar

et al. 2024

IJECE

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Honey is produced exclusively by honeybees and stingless bees which both are well adapted to tropical and subtropical regions such as Malaysia. Stingless bees are known for producing small amounts of honey and are known for having a unique flavor profile. Problem identified that many stingless bees collapsed due to weather, temperature and environment. It is critical to understand the relationship between the production of stingless bee honey and environmental conditions to improve honey production. Thus, this paper presents a review on stingless bee's honey production and prediction modeling. About 54 previous research has been analyzed and compared in identifying the research gaps. A framework on modeling the prediction of stingless bee honey is derived. The result presents the comparison and analysis on the internet of things (IoT) monitoring systems, honey production estimation, convolution neural networks (CNNs), and automatic identification methods on bee species. It is identified based on image detection method the top best three efficiency presents CNN is at 98.67%, densely connected convolutional networks with YOLO v3 is 97.7%, and DenseNet201 convolutional networks 99.81%. This study is significant to assist the researcher in developing a model for predicting stingless honey produced by bee's output, which is important for a stable economy and food security.

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Section: Random Tree Regression Algorithmmentioning

confidence: 99%