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Implementing Video Monitoring Capabilities by using hardware-based Encoders of the Raspberry Pi Zero 2 W

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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Implementing Video Monitoring Capabilities by using hardware-based Encoders of the Raspberry Pi Zero 2 W. / Ederer, Thomas; Ivkic, Igor.
In: SoftwareX, Vol. 31, 102274, 30.09.2025.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Ederer, T & Ivkic, I 2025, 'Implementing Video Monitoring Capabilities by using hardware-based Encoders of the Raspberry Pi Zero 2 W', SoftwareX, vol. 31, 102274. https://doi.org/10.1016/j.softx.2025.102274

APA

Ederer, T., & Ivkic, I. (2025). Implementing Video Monitoring Capabilities by using hardware-based Encoders of the Raspberry Pi Zero 2 W. SoftwareX, 31, Article 102274. Advance online publication. https://doi.org/10.1016/j.softx.2025.102274

Vancouver

Ederer T, Ivkic I. Implementing Video Monitoring Capabilities by using hardware-based Encoders of the Raspberry Pi Zero 2 W. SoftwareX. 2025 Sept 30;31:102274. Epub 2025 Aug 25. doi: 10.1016/j.softx.2025.102274

Author

Ederer, Thomas ; Ivkic, Igor. / Implementing Video Monitoring Capabilities by using hardware-based Encoders of the Raspberry Pi Zero 2 W. In: SoftwareX. 2025 ; Vol. 31.

Bibtex

@article{2159639df1474e72a69766f178ef0785,
title = "Implementing Video Monitoring Capabilities by using hardware-based Encoders of the Raspberry Pi Zero 2 W",
abstract = "Single-board computers, with their wide range of external interfaces, provide a cost-effective solution for studying animals and plants in their natural habitat. With the introduction of the Raspberry Pi Zero 2 W, which provides hardware-based image and video encoders, it is now possible to extend this application area to include video surveillance capabilities. This paper demonstrates a solution that offloads video stream generation from the Central Processing Unit (CPU) to hardware-based encoders. The flow of data through an encoding application is described, followed by a method of accelerating image processing by reducing the number of memory copies. The paper concludes with an example use case demonstrating the application of this new feature in an underwater camera.",
keywords = "Raspberry Pi, GPU, Video, Encoder, Monitoring",
author = "Thomas Ederer and Igor Ivkic",
year = "2025",
month = aug,
day = "25",
doi = "10.1016/j.softx.2025.102274",
language = "English",
volume = "31",
journal = "SoftwareX",
issn = "2352-7110",
publisher = "Elsevier Science B.V.",

}

RIS

TY - JOUR

T1 - Implementing Video Monitoring Capabilities by using hardware-based Encoders of the Raspberry Pi Zero 2 W

AU - Ederer, Thomas

AU - Ivkic, Igor

PY - 2025/8/25

Y1 - 2025/8/25

N2 - Single-board computers, with their wide range of external interfaces, provide a cost-effective solution for studying animals and plants in their natural habitat. With the introduction of the Raspberry Pi Zero 2 W, which provides hardware-based image and video encoders, it is now possible to extend this application area to include video surveillance capabilities. This paper demonstrates a solution that offloads video stream generation from the Central Processing Unit (CPU) to hardware-based encoders. The flow of data through an encoding application is described, followed by a method of accelerating image processing by reducing the number of memory copies. The paper concludes with an example use case demonstrating the application of this new feature in an underwater camera.

AB - Single-board computers, with their wide range of external interfaces, provide a cost-effective solution for studying animals and plants in their natural habitat. With the introduction of the Raspberry Pi Zero 2 W, which provides hardware-based image and video encoders, it is now possible to extend this application area to include video surveillance capabilities. This paper demonstrates a solution that offloads video stream generation from the Central Processing Unit (CPU) to hardware-based encoders. The flow of data through an encoding application is described, followed by a method of accelerating image processing by reducing the number of memory copies. The paper concludes with an example use case demonstrating the application of this new feature in an underwater camera.

KW - Raspberry Pi

KW - GPU

KW - Video

KW - Encoder

KW - Monitoring

U2 - 10.1016/j.softx.2025.102274

DO - 10.1016/j.softx.2025.102274

M3 - Journal article

VL - 31

JO - SoftwareX

JF - SoftwareX

SN - 2352-7110

M1 - 102274

ER -