Apiculture plays a critical role in agricultural sustainability and the production of honey products. However, the decline in honey bee populations, largely due to threats from stray animals and harmful insects, necessitates an effective solution for hive protection. This research proposes “NectarGuard,” a costeffective system that integrates MobileNet-SSD, a convolutional neural network model, to provide real-time threat detection and response for honey bee hives. SSDMobileNet $\mathbf{v} 2$ is used in the suggested system because of its lightweight architecture and adaptability for real-time threat detection on devices with limited resources. The system utilizes a 5 MP camera to monitor the surroundings of beehives, focusing on identifying potential threats like insects and stray animals. Upon detecting a threat, repellent audio is automatically generated to deter intruders and minimize physical intervention. This solution not only safeguards bee hives but also enhances beekeeping efficiency by providing remote monitoring capabilities to hive owners. The proposed system aims to contribute significantly to sustainable apiculture by addressing the decline in honey bee populations and providing an intelligent, user-friendly hive protection mechanism.


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    Title :

    NectarGuard: Enhancing Queen Bee Protection and Monitoring with MobileNet-SSD


    Contributors:


    Publication date :

    2024-11-06


    Size :

    658279 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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