A Rapid Review on the Use of Free and Open Source Technologies and Software Applied to Precision Agriculture Practices

Cited by 9 publications

(2 citation statements)

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“…Graphical user interfaces (GUIs) are software tools or applications that enable users to interact with hardware, data, and models, which are important for prototyping and the evaluation of machine vision systems in precision agriculture [22]. GUIs can provide a user-friendly interface that allows individuals, such as researchers, developers, and end-users, to easily access and utilize machine vision tools [23].…”

Section: Introductionmentioning

confidence: 99%

OpenWeedGUI: An Open-Source Graphical Tool for Weed Imaging and YOLO-Based Weed Detection

Xu,

Lu,

Deng

2024

Electronics

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Weed management impacts crop yield and quality. Machine vision technology is crucial to the realization of site-specific precision weeding for sustainable crop production. Progress has been made in developing computer vision algorithms, machine learning models, and datasets for weed recognition, but there has been a lack of open-source, publicly available software tools that link imaging hardware and offline trained models for system prototyping and evaluation, hindering community-wise development efforts. Graphical user interfaces (GUIs) are among such tools that can integrate hardware, data, and models to accelerate the deployment and adoption of machine vision-based weeding technology. This study introduces a novel GUI called OpenWeedGUI, designed for the ease of acquiring images and deploying YOLO (You Only Look Once) models for real-time weed detection, bridging the gap between machine vision and artificial intelligence (AI) technologies and users. The GUI was created in the framework of PyQt with the aid of open-source libraries for image collection, transformation, weed detection, and visualization. It consists of various functional modules for flexible user controls and a live display window for visualizing weed imagery and detection. Notably, it supports the deployment of a large suite of 31 different YOLO weed detection models, providing flexibility in model selection. Extensive indoor and field tests demonstrated the competencies of the developed software program. The OpenWeedGUI is expected to be a useful tool for promoting community efforts to advance precision weeding technology.

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Section: Introductionmentioning

confidence: 99%

OpenWeedGUI: An Open-Source Graphical Tool for Weed Imaging and YOLO-Based Weed Detection

Xu,

Lu,

Deng

2024

Electronics

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“…The recent advancements in the Internet of Things (IoT) have resulted in a multitude of diverse and innovative applications. These advancements have expanded the potential use cases of IoT technology, enabling its implementation in various industries and domains [1][2][3][4][5]. Millions of people worldwide depend on the agriculture industry, which is a crucial part of the economy.…”

Section: Introductionmentioning

confidence: 99%

Smart Irrigation for Sustainable Farming: Low- Cost IoT Solution

Akhtar,

Sinha,

Kumar

et al. 2024

Preprint

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This article presents a low-cost irrigation system that harnesses the power of IoT technologies to revolutionize water management practices and enhance agricultural productivity. The system uses soil moisture sensors, climate sensors, and temperature sensors that communicate with a central controlling mechanism. The data collected from the sensors is handled with the help of machine learning algorithms to make automated decisions about irrigation. This system is useful for small-scale farmers who lack access to expensive irrigation technology. The system has undergone field trials and has shown encouraging results. The soil moisture sensors have an average error rate of below 5%, saying that the system can precisely recognize soil moisture levels. The crops grown with the smart irrigation system had a 10% greater yield than the control group, and the system was able to limit water usage by up to 30% in comparison to tradition irrigation techniques. The potential effects of the low-cost smart irrigation system on food security and agriculture in developing countries must be taken into consideration. As water resources become more expensive and scarcer, technology can change irrigation practices and enhance the development of sustainable agriculture. To adapt the system to the unique requirements of small farmers in various regions and to examine the practicality of scaling it up for wider application, more research and development are needed. All things could be done with the low-cost smart irrigation system.

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