Testing the Feasibility of Selected, Commercially Available Wearable Devices in Detecting Agricultural-Related Incidents

Abstract

HighlightsThe 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. Keywords: Agricultural incident simulation, ATD, G-force, Incident detection, Sensor fusion, Smart watch.