Using implantable biosensors and wearable scanners to monitor dairy cattle's core body temperature in real-time

A minimally invasive method that involves using implantable biosensors with radio-frequency identification (RFID) capabilities was tested in regard to its ability to continuously measure the ear base subdermal temperature of a dairy cow. An increase in subdermal temperature, reflective of vasodilation, could, we surmised, potentially detect the level of heat stress. This could provide a better way to control dairy-barn cooling systems, which are commonly controlled solely on the basis of either air temperature or some other such non-ideal environmental parameters. Concurrent with the development of new technologies, the Long-Range (LoRa) wireless communication technology and a concept known as the "Internet of Things" (IoT) were utilized to extract temperature data from the base of a cow's ear every 30 s in real-time. To test the method, an implant temperature sensor was injected, at the base of the ear, into three Holstein cows, and each was equipped with a wearable RFID scanner (mounted on an existing collar) for five days during a summer season in Wisconsin. The primary objective was to determine the efficacy of using implantable biosensors and wireless communication technology to monitor the heat-stress levels experienced by these dairy cows, in real-time, over the five days. Overall, the recorded subdermal temperature data obtained from implantable biosensors closely corresponded to the changes that occurred in core (vaginal) body temperature, and the developed wireless communication nodes successfully measured and monitored the temperature readings in real-time. Each cow showed different heat stress responses despite the fact that all three were in virtually the same location and subject to the same temperature-humidity index (THI) throughout the study. The study also found that the temperature readings obtained by the implantable biosensor began to more closely match in value the corresponding core body temperature (CBT) readings as the THI increased. Furthermore, the CBT of a cow could be reasonably predicted by applying a machine-learning (ML) algorithm to measured subdermal-temperature and THI data. The present study also found that the dairy cows tested displayed no obvious adverse effects that could have resulted from the biosensor implanted at the base of the ear. This study's findings should serve as the first step toward any future research and development that may take place in the field of precision agriculture, especially research that considers even smaller and more practical electronics.