Aaron James Etienne, William E Field, Shawn G Ehlers, Roger Tormoehlen, Noah Joel Haslett
{"title":"测试选定的商业可穿戴设备在检测农业相关事件中的可行性。","authors":"Aaron James Etienne, William E Field, Shawn G Ehlers, Roger Tormoehlen, Noah Joel Haslett","doi":"10.13031/jash.15985","DOIUrl":null,"url":null,"abstract":"<p><strong>Highlights: </strong>The purpose of this research was to validate a test procedure for using commercially available smart technologies in detecting an agricultural-related incident. A convenient selection of commercially available wearable devices was used to measure the inertial qualities of simulated incidents. Simulated ejections, falls, and upsets were performed to recreate leading causes of agricultural injuries and fatalities using an anthropomorphic test device. Only 2 of 27 simulated incidents triggered detection on the selected wearable devices tested. The results of this study were inconclusive in determining the feasibility of commercially available wearable devices in detecting agricultural-related incidents. More research is needed to develop an improved testing procedure. Additional collaboration is needed with manufacturers of wearable incident detection devices to clearly identify potential applications and limitations of their devices.</p><p><strong>Abstract: </strong>A study was conducted to test a selection of commercially available wearable devices to determine their feasibility for triggering incident detection during a variety of simulated agricultural incidents with high risk of causing injury. The goal was to ultimately increase survivability outcomes for victims by enhancing notification and reducing response time from emergency services. A 50th percentile adult male anthropomorphic test device (ATD). was fitted with a convenient selection of commercially available wearable smart technologies to measure the responsiveness of the technology's incident detection software. Devices used for this testing were: (1) Garmin Vivoactive 4 smartwatch; (2) Apple Watch Series 7 (Bluetooth only and cellular models); and (3) Movesense Active tracking device. A Samsung Galaxy S22 smartphone and an Apple iPhone 12 smartphone were used to connect the wearable devices and measured impact through their internal inertial measurement unit (IMU) sensors. Simulated ejections from equipment, vertical falls, and vehicle overturns were performed with the ATD. Side upsets were simulated with the ATD positioned in the operator station of a 52-drawbar horsepower (dbp), two-wheel drive, standard front axle, diesel tractor, weighing 6500 pounds. The tractor was equipped with an approved ROPS. Side upsets were also simulated using a 22-horsepower zero-turn mower, with the ATD positioned in the operator seat. Falls were simulated from heights of up to 4.57 meters. After each simulated incident, devices were examined to determine whether or not incident detection was successfully triggered. Data was then collected from an internal sensor logging application installed on the selected devices. It was found that the incident detection feature on the identified wearable devices only triggered in specific scenarios. Only 2 of the 27 simulated incidents successfully triggered incident detection on one device. Only the Garmin Vivoactive 4 smartwatch triggered incident detection. No device was triggered during the ATD impact in simulated tractor upset testing or in simulated zero-turn mower upset testing. It was concluded that these devices, in their current form, are not reliable for use in detecting serious agricultural-related injuries, especially considering the lack of adequate cell phone coverage in the areas in which these incidents are most likely to occur.</p>","PeriodicalId":45344,"journal":{"name":"Journal of Agricultural Safety and Health","volume":"30 4","pages":"181-204"},"PeriodicalIF":0.9000,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Testing the Feasibility of Selected, Commercially Available Wearable Devices in Detecting Agricultural-Related Incidents.\",\"authors\":\"Aaron James Etienne, William E Field, Shawn G Ehlers, Roger Tormoehlen, Noah Joel Haslett\",\"doi\":\"10.13031/jash.15985\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Highlights: </strong>The purpose of this research was to validate a test procedure for using commercially available smart technologies in detecting an agricultural-related incident. A convenient selection of commercially available wearable devices was used to measure the inertial qualities of simulated incidents. Simulated ejections, falls, and upsets were performed to recreate leading causes of agricultural injuries and fatalities using an anthropomorphic test device. Only 2 of 27 simulated incidents triggered detection on the selected wearable devices tested. The results of this study were inconclusive in determining the feasibility of commercially available wearable devices in detecting agricultural-related incidents. More research is needed to develop an improved testing procedure. Additional collaboration is needed with manufacturers of wearable incident detection devices to clearly identify potential applications and limitations of their devices.</p><p><strong>Abstract: </strong>A study was conducted to test a selection of commercially available wearable devices to determine their feasibility for triggering incident detection during a variety of simulated agricultural incidents with high risk of causing injury. The goal was to ultimately increase survivability outcomes for victims by enhancing notification and reducing response time from emergency services. A 50th percentile adult male anthropomorphic test device (ATD). was fitted with a convenient selection of commercially available wearable smart technologies to measure the responsiveness of the technology's incident detection software. Devices used for this testing were: (1) Garmin Vivoactive 4 smartwatch; (2) Apple Watch Series 7 (Bluetooth only and cellular models); and (3) Movesense Active tracking device. A Samsung Galaxy S22 smartphone and an Apple iPhone 12 smartphone were used to connect the wearable devices and measured impact through their internal inertial measurement unit (IMU) sensors. Simulated ejections from equipment, vertical falls, and vehicle overturns were performed with the ATD. Side upsets were simulated with the ATD positioned in the operator station of a 52-drawbar horsepower (dbp), two-wheel drive, standard front axle, diesel tractor, weighing 6500 pounds. The tractor was equipped with an approved ROPS. Side upsets were also simulated using a 22-horsepower zero-turn mower, with the ATD positioned in the operator seat. Falls were simulated from heights of up to 4.57 meters. After each simulated incident, devices were examined to determine whether or not incident detection was successfully triggered. Data was then collected from an internal sensor logging application installed on the selected devices. It was found that the incident detection feature on the identified wearable devices only triggered in specific scenarios. Only 2 of the 27 simulated incidents successfully triggered incident detection on one device. Only the Garmin Vivoactive 4 smartwatch triggered incident detection. No device was triggered during the ATD impact in simulated tractor upset testing or in simulated zero-turn mower upset testing. It was concluded that these devices, in their current form, are not reliable for use in detecting serious agricultural-related injuries, especially considering the lack of adequate cell phone coverage in the areas in which these incidents are most likely to occur.</p>\",\"PeriodicalId\":45344,\"journal\":{\"name\":\"Journal of Agricultural Safety and Health\",\"volume\":\"30 4\",\"pages\":\"181-204\"},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2024-10-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Agricultural Safety and Health\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.13031/jash.15985\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Agricultural Safety and Health","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.13031/jash.15985","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
引用次数: 0
摘要
重点:本研究的目的是验证使用商用智能技术检测农业相关事件的测试程序。通过方便地选择市售可穿戴设备来测量模拟事件的惯性质量。模拟弹射,跌倒,和颠覆进行了重建农业伤害和死亡的主要原因使用拟人化的测试装置。27个模拟事件中只有2个触发了选定的可穿戴设备的检测。这项研究的结果在确定商用可穿戴设备在检测农业相关事件方面的可行性方面尚无定论。需要更多的研究来开发改进的测试程序。需要与可穿戴事件检测设备的制造商进行额外的合作,以清楚地识别其设备的潜在应用和局限性。摘要:本研究测试了一系列市售可穿戴设备,以确定其在各种高伤害风险的模拟农业事件中触发事件检测的可行性。目标是通过加强通知和缩短紧急服务的反应时间,最终提高受害者的生存能力。50百分位成年男性拟人化测试装置(ATD)。配备了方便选择的市售可穿戴智能技术,以测量该技术的事件检测软件的响应能力。本次测试使用的设备有:(1)Garmin Vivoactive 4智能手表;(2) Apple Watch Series 7(仅支持蓝牙和蜂窝机型);(3) Movesense主动跟踪装置。使用三星Galaxy S22智能手机和苹果iPhone 12智能手机连接可穿戴设备,并通过其内部惯性测量单元(IMU)传感器测量影响。用ATD模拟了设备弹射、垂直坠落和车辆倾覆。在模拟侧翻时,ATD安装在一个52牵引力马力(dbp)、标准前桥、重6500磅的柴油牵引车的操作台上。该拖拉机配备了经批准的ROPS。使用22马力的零转割草机模拟侧翻,ATD安装在操作员座椅上。从高达4.57米的高度模拟了瀑布。在每个模拟事件之后,检查设备以确定是否成功触发了事件检测。然后从安装在选定设备上的内部传感器日志应用程序收集数据。结果发现,被识别的可穿戴设备上的事件检测功能仅在特定场景下触发。27个模拟事件中只有2个成功触发了同一设备上的事件检测。只有Garmin Vivoactive 4智能手表触发了事件检测。在模拟拖拉机翻倒试验和模拟零转割草机翻倒试验中,ATD冲击时没有触发任何装置。结论是,这些装置目前的形式在检测与农业有关的严重伤害方面是不可靠的,特别是考虑到在最有可能发生这些事件的地区缺乏足够的移动电话覆盖。
Testing the Feasibility of Selected, Commercially Available Wearable Devices in Detecting Agricultural-Related Incidents.
Highlights: The purpose of this research was to validate a test procedure for using commercially available smart technologies in detecting an agricultural-related incident. A convenient selection of commercially available wearable devices was used to measure the inertial qualities of simulated incidents. Simulated ejections, falls, and upsets were performed to recreate leading causes of agricultural injuries and fatalities using an anthropomorphic test device. Only 2 of 27 simulated incidents triggered detection on the selected wearable devices tested. The results of this study were inconclusive in determining the feasibility of commercially available wearable devices in detecting agricultural-related incidents. More research is needed to develop an improved testing procedure. Additional collaboration is needed with manufacturers of wearable incident detection devices to clearly identify potential applications and limitations of their devices.
Abstract: A study was conducted to test a selection of commercially available wearable devices to determine their feasibility for triggering incident detection during a variety of simulated agricultural incidents with high risk of causing injury. The goal was to ultimately increase survivability outcomes for victims by enhancing notification and reducing response time from emergency services. A 50th percentile adult male anthropomorphic test device (ATD). was fitted with a convenient selection of commercially available wearable smart technologies to measure the responsiveness of the technology's incident detection software. Devices used for this testing were: (1) Garmin Vivoactive 4 smartwatch; (2) Apple Watch Series 7 (Bluetooth only and cellular models); and (3) Movesense Active tracking device. A Samsung Galaxy S22 smartphone and an Apple iPhone 12 smartphone were used to connect the wearable devices and measured impact through their internal inertial measurement unit (IMU) sensors. Simulated ejections from equipment, vertical falls, and vehicle overturns were performed with the ATD. Side upsets were simulated with the ATD positioned in the operator station of a 52-drawbar horsepower (dbp), two-wheel drive, standard front axle, diesel tractor, weighing 6500 pounds. The tractor was equipped with an approved ROPS. Side upsets were also simulated using a 22-horsepower zero-turn mower, with the ATD positioned in the operator seat. Falls were simulated from heights of up to 4.57 meters. After each simulated incident, devices were examined to determine whether or not incident detection was successfully triggered. Data was then collected from an internal sensor logging application installed on the selected devices. It was found that the incident detection feature on the identified wearable devices only triggered in specific scenarios. Only 2 of the 27 simulated incidents successfully triggered incident detection on one device. Only the Garmin Vivoactive 4 smartwatch triggered incident detection. No device was triggered during the ATD impact in simulated tractor upset testing or in simulated zero-turn mower upset testing. It was concluded that these devices, in their current form, are not reliable for use in detecting serious agricultural-related injuries, especially considering the lack of adequate cell phone coverage in the areas in which these incidents are most likely to occur.