Year: 2018
Type: article
Abstract: Honeybees provide great benefits for people both with the foods they produce and as a pollinator.It is known that they pass the whole year with the foods they collect in spring and summer months.Beekeepers also benefit from the honey produced in these periods.Whether a beehive works adequately or not and its status of development can be understood through the observations by beekeepers.In this study, an Arduino-supported neural network model was developed in order to obtain information about the general situations of beehives.The three-input and three-output neural networks were embedded in a board after the training and testing stage.While temperature, humidity, and weight refer to inputs, good situation, stable situation, and bad situation represent outputs.The real-time model has an accuracy of 99.84%.
Authors: Bayir, Raif, Albayrak, Ahmet
Institutions: Karabük University, Karadeniz Technical University
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: gold
Estimated APC paid: $431
OpenAlex ID: W2953401291