Departamento de Informática e Comunicações, Instituto Politécnico de Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal.
Integrated Researcher at Centre in Digitalization and Intelligent Robotics (CeDRI), Polytechnical University of Bragança, Campus Santa Apolónia, 5300-253 Bragança, Portugal.
Sensors (Basel). 2023 Sep 11;23(18):7811. doi: 10.3390/s23187811.
Farm tractors have become a key part of daily routine agriculture, converting complex and time-consuming tasks into tasks that are easier to perform and less dependent on human labor, contributing directly to increasing the economic value generated by this activity sector, either by increasing the productivity or by making certain agricultural crops viable, which otherwise would not be sustainable. However, despite all the advantages, accidents with this type of equipment are common, often with critical and sometimes fatal consequences. The evolution of safety requirements of these machines has occurred at a good level; however, a significant part of the agricultural tractors in use are older models that do not have such solutions. Even in the new models, which contain such solutions, these are not always correctly used, and it is even common that they are turned off or simply not used at all. It is therefore natural that accidents continue to occur, a situation that is aggravated by other factors. Lack of situational awareness of the operators, which can result from advanced age, inadequate training, reduced sensitivity/respect for safety rules, or working on irregular terrain like mountainous areas, contribute to high-risk contexts that end in the loss of human life. The consequences of such accidents are clearly aggravated by the time it takes to assist the victims-either because accidents are simply not identified/reported immediately, or by the time it takes to locate and provide help to the victims. This is a scenario that is more common in mountainous regions and regions with low population density. The current paper, using NB-IoT, a set of sensors, and a web application, presents a conceptual toolset conceived to prevent accidents and minimize consequences (human and material) that can be applied to old and new farm tractors. The development was carried out taking the characterization of the farmers and the land in the region in which the authors' research institution is located into account, which has the highest rate of fatal accidents with agricultural tractors in the country; it is a region of mountainous with a very low population density.
农用拖拉机已经成为日常农业的重要组成部分，将复杂且耗时的任务转化为更容易执行且对人力依赖程度更低的任务，直接有助于增加该活动领域产生的经济价值，无论是通过提高生产力还是使某些农业作物具有可行性，否则这些作物将无法持续。然而，尽管有所有这些优势，此类设备的事故仍然很常见，通常后果严重，有时甚至是致命的。这些机器的安全要求的发展水平相当高；然而，仍有相当一部分正在使用的农用拖拉机是旧型号，它们没有这些解决方案。即使在包含这些解决方案的新型号中，这些解决方案也并非总是被正确使用，甚至常见的情况是它们被关闭或根本未被使用。因此，事故继续发生是很自然的，这种情况因其他因素而加剧。操作人员的情境意识不足，这可能是由于年龄较大、培训不足、对安全规则的敏感性/尊重程度降低，或者在山区等不规则地形上工作等原因造成的，这增加了高风险的情况，最终导致人员伤亡。这种事故的后果因受害者救援所需的时间而明显加剧——无论是因为事故根本没有被立即识别/报告，还是因为找到并向受害者提供帮助所需的时间。这种情况在山区和人口密度低的地区更为常见。本文使用 NB-IoT、一组传感器和一个网络应用程序，提出了一个概念性工具集，旨在预防事故并最小化可能发生的（人员和物质）后果，该工具集可应用于新旧农用拖拉机。该开发是在考虑作者所在研究机构所在地区的农民和土地的特征的情况下进行的，该地区是该国农业拖拉机致命事故发生率最高的地区；这是一个山区，人口密度非常低。
