Implementing video monitoring capabilities by using hardware-based encoders of the Raspberry Pi Zero 2 W

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.

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Publication Details

Journal
SoftwareX
Published
2025-08-25
DOI
https://doi.org/10.1016/j.softx.2025.102274
Primary Topic
Water Quality Monitoring Technologies
Type
article
Field-Weighted Citation Impact
0.00
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article

Implementing video monitoring capabilities by using hardware-based encoders of the Raspberry Pi Zero 2 W

Igor Ivkić, Thomas Ederer
SoftwareX
Water Quality Monitoring Technologies
article

Implementing video monitoring capabilities by using hardware-based encoders of the Raspberry Pi Zero 2 W

Igor Ivkić, Thomas Ederer
article en

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.

SoftwareXVol. 31
University of Applied Sciences Burgenland (AT), Lancaster University (GB)
Affordable and clean energy
Openalex Percentile: Top 79%
Water Quality Monitoring Technologies
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