Autor:

Wachowicz, Anna ; Pytlik, Jakub ; Małysiak-Mrozek, Bożena ; Tokarz, Krzysztof ; Mrozek, Dariusz

Współtwórca:

Wiśniewski, Remigiusz - ed. ; Gomes, Luis - ed. ; Wan, Shaohua - ed.

Tytuł:

Edge computing in IoT-enabled honeybee monitoring for the detection of "Varroa destructor"

Podtytuł:

.

Tytuł publikacji grupowej:

AMCS, volume 32 (2022)

Temat i słowa kluczowe:

Internet of Things (IoT) ; Varroa destructor ; precision beekeeping ; machine learning ; cloud ; image processing ; edge devices

Abstract:

Among many important functions, bees play a key role in food production. Unfortunately, worldwide bee populations have been decreasing since 2007. One reason for the decrease of adult worker bees is varroosis, a parasitic disease caused by the "Varroa destructor" ("V. destructor") mite. Varroosis can be quickly eliminated from beehives once detected. However, this requires them to be monitored continuously during periods of bee activity to ensure that "V. destructor" mites are detected before they spread and infest the entire beehive. To this end, the use of Internet of things (IoT) devices can significantly increase detection speed. ; Comprehensive solutions are required that can cover entire apiaries and prevent the disease from spreading between hives and apiaries. In this paper, we present a solution for global monitoring of apiaries and the detection of "V. destructor" mites in beehives. Our solution captures and processes video streams from camera-based IoT devices, analyzes those streams using edge computing, and constructs a global collection of cases within the cloud. We have designed an IoT device that monitors bees and detects "V. destructor" infestation via video stream analysis on a GPU-accelerated Nvidia Jetson Nano. Experimental results show that the detection process can be run in real time while maintaining similar efficacy to alternative approaches.

Wydawca:

Zielona Góra: Uniwersytet Zielonogórski

Data wydania:

2022

Typ zasobu:

artykuł

DOI:

10.34768/amcs-2022-0026

Strony:

355-369

Źródło:

AMCS, volume 32, number 3 (2022) ; kliknij tutaj, żeby przejść

Jezyk:

eng

Licencja CC BY 4.0:

kliknij tutaj, żeby przejść

Prawa do dysponowania publikacją:

Biblioteka Uniwersytetu Zielonogórskiego