Namal Jayasuriya , Malith Weerasekara , Oula Ghannoum , Yi Guo , Wen Hu
{"title":"Spi-VSTL: Image data collection platform using off-the shelf hardware for vertically supported crops in state-of-the-art glasshouses","authors":"Namal Jayasuriya , Malith Weerasekara , Oula Ghannoum , Yi Guo , Wen Hu","doi":"10.1016/j.ohx.2025.e00624","DOIUrl":null,"url":null,"abstract":"<div><div>Horticulture crop growers are moving from conventional to protected crops, aiming for quality food production utilising fewer resources. Skilled labour for monitoring and maintaining crops in these compact environments has been identified as a major cost and can be reduced using automated image-based crop monitoring. There is a range of protected cropping infrastructures targeting different types of crops. Image data collection platforms are needed to be tailored according to the infrastructure and nature of the crop. Available research or commercial-purpose image data collection platforms for indoor crops are mostly targeted at movable and small plants compared to vertically supported tall plants. Customising existing commercial systems for this specific type of crop is costly. This paper proposes a low-cost image data collection platform for monitoring vertically supported tall crops in order to reduce labour costs while expanding the monitoring tasks for maintaining better crop growth. Off-the-shelf hardware and electronic components accessible from Australia are used for this development. The proposed platform runs manually on concrete flow and on pipe rail systems found in state-of-the-art commercial glasshouse settings. The proposed motorised platform has been tested with 30 kg, and speed was measured as an average minimum of 0.06 ms<sup>−1</sup> and an average maximum of 0.47 ms<sup>−1</sup>. The usability of the proposed design has been proved with a published data set and research on plant height estimation. Other use cases and room for further development are also discussed.</div></div>","PeriodicalId":37503,"journal":{"name":"HardwareX","volume":"21 ","pages":"Article e00624"},"PeriodicalIF":2.1000,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"HardwareX","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2468067225000021","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Horticulture crop growers are moving from conventional to protected crops, aiming for quality food production utilising fewer resources. Skilled labour for monitoring and maintaining crops in these compact environments has been identified as a major cost and can be reduced using automated image-based crop monitoring. There is a range of protected cropping infrastructures targeting different types of crops. Image data collection platforms are needed to be tailored according to the infrastructure and nature of the crop. Available research or commercial-purpose image data collection platforms for indoor crops are mostly targeted at movable and small plants compared to vertically supported tall plants. Customising existing commercial systems for this specific type of crop is costly. This paper proposes a low-cost image data collection platform for monitoring vertically supported tall crops in order to reduce labour costs while expanding the monitoring tasks for maintaining better crop growth. Off-the-shelf hardware and electronic components accessible from Australia are used for this development. The proposed platform runs manually on concrete flow and on pipe rail systems found in state-of-the-art commercial glasshouse settings. The proposed motorised platform has been tested with 30 kg, and speed was measured as an average minimum of 0.06 ms−1 and an average maximum of 0.47 ms−1. The usability of the proposed design has been proved with a published data set and research on plant height estimation. Other use cases and room for further development are also discussed.
园艺作物种植者正在从传统作物转向保护作物,目标是利用更少的资源生产高质量的粮食。在这些紧凑的环境中监测和维护作物的熟练劳动力已被确定为主要成本,可以使用基于图像的自动化作物监测来降低成本。有一系列针对不同类型作物的保护性种植基础设施。需要根据作物的基础设施和性质定制图像数据采集平台。与垂直支撑的高大植物相比,现有的研究或商业用途的室内作物图像数据收集平台主要针对可移动的小型植物。为这种特定类型的作物定制现有的商业系统是昂贵的。本文提出了一种低成本的垂直支撑高大作物监测图像数据采集平台,在降低人工成本的同时,扩大监测任务,保持作物更好的生长。从澳大利亚获得的现成硬件和电子元件用于此开发。提议的平台在混凝土流和管道轨道系统上手动运行,这些系统在最先进的商业温室环境中发现。提议的机动平台已经用30公斤的重量进行了测试,速度的平均最小值为0.06 ms - 1,平均最大值为0.47 ms - 1。已发表的数据集和植物高度估计研究证明了所提出设计的可用性。还讨论了其他用例和进一步开发的空间。
HardwareXEngineering-Industrial and Manufacturing Engineering
CiteScore
4.10
自引率
18.20%
发文量
124
审稿时长
24 weeks
期刊介绍:
HardwareX is an open access journal established to promote free and open source designing, building and customizing of scientific infrastructure (hardware). HardwareX aims to recognize researchers for the time and effort in developing scientific infrastructure while providing end-users with sufficient information to replicate and validate the advances presented. HardwareX is open to input from all scientific, technological and medical disciplines. Scientific infrastructure will be interpreted in the broadest sense. Including hardware modifications to existing infrastructure, sensors and tools that perform measurements and other functions outside of the traditional lab setting (such as wearables, air/water quality sensors, and low cost alternatives to existing tools), and the creation of wholly new tools for either standard or novel laboratory tasks. Authors are encouraged to submit hardware developments that address all aspects of science, not only the final measurement, for example, enhancements in sample preparation and handling, user safety, and quality control. The use of distributed digital manufacturing strategies (e.g. 3-D printing) is encouraged. All designs must be submitted under an open hardware license.