Theme 3-2: Livestock Production Systems--Poster Sessions

Description

This study investigated the integration of Long Range Wide Area Network (LoRa WAN) communication technology and sensors for use as Internet of Things (IoT) platform for Precision Livestock-Farming (PLF) applications. The research was conducted at New Mexico State University’s Clayton Livestock Research Centre. The functionality of LoRA WAN communication technology and performance of LoRa WAN motion and GPS sensors were tested using static sensors that were placed either, a) outdoors and at incremental distances from the LoRa WAN gateway antenna (Field, n=6), or b) housed indoors and close to the same LoRa WAN gateway antenna (Indoor, n=5). Accelerometer data, reported as motion intensity index, and GPS location were acquired, transmitted and logged at 1 and 15 minute intervals, respectively. We evaluated the tracker's GPS accuracy (GPSBias as the euclidean distance between the actual and projected tracker location) and variables associated with the tracker’s data transmission capabilities. The results indicate that field trackers had a greater accuracy for remote sensing of GPS locations compared to indoor trackers facing increasing communication interference to acquire satellite signals (GPSBias; 5.20 vs. 17.76 m; P< 0.01). Overall, the trackers and deployments appeared to have a comparable GPS accuracy to other tracking devices and systems available in the market. The total data packets that were successfully transmitted were similar between the indoor and field trackers, but the number of data packets that were processed varied between the two deployments (P=0.02). Due to the static deployment of indoor and field trackers, activity data was almost non-existent for most devices. However, same trackers embedded on collars that were mounted on mature cattle showed clear diurnal patterns consistent with time budgets exerted by grazing cattle. The pilot testing of GPS and accelerometer sensors using LoRa WAN technology revealed reasonable sensor sensitivity and reliability for integration in PLF platforms.

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Performance of LoRa-WAN Sensors for Precision Livestock Tracking and Biosensing Applications

This study investigated the integration of Long Range Wide Area Network (LoRa WAN) communication technology and sensors for use as Internet of Things (IoT) platform for Precision Livestock-Farming (PLF) applications. The research was conducted at New Mexico State University’s Clayton Livestock Research Centre. The functionality of LoRA WAN communication technology and performance of LoRa WAN motion and GPS sensors were tested using static sensors that were placed either, a) outdoors and at incremental distances from the LoRa WAN gateway antenna (Field, n=6), or b) housed indoors and close to the same LoRa WAN gateway antenna (Indoor, n=5). Accelerometer data, reported as motion intensity index, and GPS location were acquired, transmitted and logged at 1 and 15 minute intervals, respectively. We evaluated the tracker's GPS accuracy (GPSBias as the euclidean distance between the actual and projected tracker location) and variables associated with the tracker’s data transmission capabilities. The results indicate that field trackers had a greater accuracy for remote sensing of GPS locations compared to indoor trackers facing increasing communication interference to acquire satellite signals (GPSBias; 5.20 vs. 17.76 m; P< 0.01). Overall, the trackers and deployments appeared to have a comparable GPS accuracy to other tracking devices and systems available in the market. The total data packets that were successfully transmitted were similar between the indoor and field trackers, but the number of data packets that were processed varied between the two deployments (P=0.02). Due to the static deployment of indoor and field trackers, activity data was almost non-existent for most devices. However, same trackers embedded on collars that were mounted on mature cattle showed clear diurnal patterns consistent with time budgets exerted by grazing cattle. The pilot testing of GPS and accelerometer sensors using LoRa WAN technology revealed reasonable sensor sensitivity and reliability for integration in PLF platforms.