Stereovision system for estimating tractors and agricultural machines transit area under orchards canopy

Abstract:
Managing orchards requires delicate agricultural operations being typically carried out in narrow zones where the operators usually drive machineries under stress that could result in poor performance. In such conditions, the use of technology would help manage the machines to reduce the hazardous work and eventual damage to the plants. To safely drive a tractor, the driver needs to be aware of its surroundings, thus a stereovision system can provide helpful information. Stereo imaging has proven to be an effective three-dimensional vision system. Indeed, the range (or third coordinate) information is useful to detect the obstacle distances. Such distances, when detected during agricultural operations, could be used to assist the operator in driving the tractor at regular or variable working speeds and eventually to provide manufacturers useful indications to model the form of ROPS (roll over protection structure). This study aimed to verify the closeness of agreement between manual and stereo-image measurements, and thus to provide helpful information regarding safety and working purposes. The system used a custom low-cost dual web-camera in combination with an image analysis algorithm in order to automatically extract the information needed. Manual independent measurements were carried out using a metric tape (sensitivity 1 cm). A regular structure was used for the analysis: four rows of ten trees each one. Alternated red and blue paper markers were placed on the hazelnut trees (two per tree) of two couples of rows for enhanced visibility. For each couple of trees (one on the right, the other on the left), the four markers formed a trapezoid that was measured. The results of the analysis demonstrated that the stereo vision provided distance measurements with reasonable accuracy (error <5%) in the range of distances lower than 20 m. The resolution assessed for the developed video system is suitable for obtaining distance information in real scenes. This information could be used to assist drivers to operate agricultural machineries through narrow tree rows during work execution. Moreover, such information could be used for safeguarding decision-making and/or for controlling some tractor functions such as continuing moving, changing driving direction, changing 3-point hitch position, reducing transmission speed, halting the tractor. These functions will be necessary before tractors become fully autonomous. Finally, the measured distances, marking the narrow transitions between the tree rows, could be also used to study the ROPS form, both for working safely and for avoiding possible damage caused to the hazel trees laterally. \nKeywords: stereovision, precision agriculture, digital agriculture, hazelnut; canopy, ROPS, orchards \nDOI: 10.25165/j.ijabe.20191201.4123 \n \nCitation: Costa C, Febbi P, Pallottino F, Cecchini M, Figorilli S, Antonucci F, et al. Stereovision system for estimating tractors and agricultural machines transit area under orchards canopy. Int J Agric & Biol Eng, 2019; 12(1): 1–5.
Author Listing: Corrado Costa;Paolo Febbi;Federico Pallottino;Massimo Cecchini;Simone Figorilli;Francesca Antonucci;Paolo Menesatti
Volume: 12
Pages: 1-5
DOI: 10.25165/IJABE.V12I1.4123
Language: English
Journal: International Journal of Agricultural and Biological Engineering

International Journal of Agricultural and Biological Engineering

INT J AGR BIOL ENG

影响因子:2.2 是否综述期刊:否 是否OA:是 是否预警:不在预警名单内 发行时间:- ISSN:1934-6344 发刊频率:- 收录数据库:SCIE/Scopus收录/DOAJ开放期刊 出版国家/地区:PEOPLES R CHINA 出版社:Chinese Society of Agricultural Engineering

期刊介绍

International Journal of Agricultural and Biological Engineering (IJABE, https://www.ijabe.org) is a peer reviewed open access international journal. IJABE, started in 2008, is a joint publication co-sponsored by US-based Association of Agricultural, Biological and Food Engineers (AOCABFE) and China-based Chinese Society of Agricultural Engineering (CSAE). The ISSN 1934-6344 and eISSN 1934-6352 numbers for both print and online IJABE have been registered in US. Now, Int. J. Agric. & Biol. Eng (IJABE) is published in both online and print version by Chinese Academy of Agricultural Engineering.

International Journal of Agricultural and Biological Engineering (IJABE, https://www.ijabe.org) is a peer reviewed open access international journal.IJABE 创刊 于 2008 年 , 是 由 美国 农业 、 生物 与 食品 工程 师 协会 ( AOCABFE ) 和 中国 农业 工程 学会 ( CSAE ) 共同 主办 的 联合 出版 物 。印刷 版 和 在线 版 IJABE 的 ISSN 1934 - 6344 和 eISSN 1934 - 6352 号 已 在 美国 注册 。《 国际 农业 与 生物 工程 杂志 》 ( IJABE ) 由 中国 农业 工程 院 出版 , 目前 有 网络 版 和 印刷 版 。

年发文量 182
国人发稿量 174
国人发文占比 95.65%
自引率 18.2%
平均录取率 -
平均审稿周期 24 Weeks
版面费 $1,000 USD
偏重研究方向 AGRICULTURAL ENGINEERING-
期刊官网 https://www.ijabe.org/index.php/ijabe
投稿链接 -

质量指标占比

研究类文章占比 OA被引用占比 撤稿占比 出版后修正文章占比
97.80% 97.26% 0.00% 0.00%

相关指数

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期刊预警不是论文评价,更不是否定预警期刊发表的每项成果。《国际期刊预警名单(试行)》旨在提醒科研人员审慎选择成果发表平台、提示出版机构强化期刊质量管理。

预警期刊的识别采用定性与定量相结合的方法。通过专家咨询确立分析维度及评价指标,而后基于指标客观数据产生具体名单。

具体而言,就是通过综合评判期刊载文量、作者国际化程度、拒稿率、论文处理费(APC)、期刊超越指数、自引率、撤稿信息等,找出那些具备风险特征、具有潜在质量问题的学术期刊。最后,依据各刊数据差异,将预警级别分为高、中、低三档,风险指数依次减弱。

《国际期刊预警名单(试行)》确定原则是客观、审慎、开放。期刊分区表团队期待与科研界、学术出版机构一起,夯实科学精神,打造气正风清的学术诚信环境!真诚欢迎各界就预警名单的分析维度、使用方案、值得关切的期刊等提出建议!

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时间 预警情况
2025年03月发布的2025版 不在预警名单中
2024年02月发布的2024版 不在预警名单中
2023年01月发布的2023版 不在预警名单中
2021年12月发布的2021版 不在预警名单中
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JCR分区 WOS分区等级:Q2区

版本 按学科 分区
WOS期刊SCI分区
WOS期刊SCI分区是指SCI官方(Web of Science)为每个学科内的期刊按照IF数值排 序,将期刊按照四等分的方法划分的Q1-Q4等级,Q1代表质量最高,即常说的1区期刊。
(2021-2022年最新版)
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关于2019年中科院分区升级版(试行)

分区表升级版(试行)旨在解决期刊学科体系划分与学科发展以及融合趋势的不相容问题。由于学科交叉在当代科研活动的趋势愈发显著,学科体系构建容易引发争议。为了打破学科体系给期刊评价带来的桎梏,“升级版方案”首先构建了论文层级的主题体系,然后分别计算每篇论文在所属主题的影响力,最后汇总各期刊每篇论文分值,得到“期刊超越指数”,作为分区依据。

分区表升级版(试行)的优势:一是论文层级的主题体系既能体现学科交叉特点,又可以精准揭示期刊载文的多学科性;二是采用“期刊超越指数”替代影响因子指标,解决了影响因子数学性质缺陷对评价结果的干扰。整体而言,分区表升级版(试行)突破了期刊评价中学科体系构建、评价指标选择等瓶颈问题,能够更为全面地揭示学术期刊的影响力,为科研评价“去四唯”提供解决思路。相关研究成果经过国际同行的认可,已经发表在科学计量学领域国际重要期刊。

《2019年中国科学院文献情报中心期刊分区表升级版(试行)》首次将社会科学引文数据库(SSCI)期刊纳入到分区评估中。升级版分区表(试行)设置了包括自然科学和社会科学在内的18个大类学科。基础版和升级版(试行)将过渡共存三年时间,推测在此期间各大高校和科研院所仍可能会以基础版为考核参考标准。 提示:中科院分区官方微信公众号“fenqubiao”仅提供基础版数据查询,暂无升级版数据,请注意区分。

中科院分区 查看说明

版本 大类学科 小类学科 Top期刊 综述期刊
农林科学
3区
AGRICULTURAL ENGINEERING
农业工程
2区
2021年12月
基础版
农林科学
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升级版
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旧的升级版
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农业工程
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最新升级版
农林科学
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农业工程
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