RF-Egg: An RF Solution for Fine-Grained Multi-Target and Multi-Task Egg Incubation Sensing

Zehua Sun, Tao Ni, Yongliang Chen, Di Duan, Kai Liu, Weitao Xu

Abstract: Eggs and chickens serve as crucial animal-source proteins in our diets, making large-scale breeding egg incubation an essential undertaking. However, current solutions, i.e., vision-based and sensor-based methods, are primarily designed for egg fertility detection tasks under single-egg settings, which have not yet satisfied the goal of multi-target and multi-task sensing. In this paper, we propose RF-Egg, the first RF-based fine-grained multi-target and multi-task egg incubation sensing system with respect to sensing fertility, incubation status, and early mortality of chicken embryos. RF-Egg leverages the weak coupling effects of RFID tags when interacting with eggs, which induces different impedance changes of RFID tags with the incubation levels of eggs, thereby resulting in a variation of low-level phase readings of the backscatter signals. Regarding the challenge of multi-target profiling interference, we propose a multipath combating algorithm to extract the target-induced signal component based on the built signal model, and address non-uniformity issues across multiple tags. Moreover, we devise three unique feature maps tailored to each task, and then design an Multi-Task Triplet (MTT) network for multitasking. Our evaluation results based on 189 eggs show that RF-Egg achieves an accuracy of 94.4%, 96.1%, and 90.1% for the aforementioned three tasks when supporting 16 targets. Additionally, our extensive field study in a local egg hatchery suggests that RF-Egg presents the potential to be widely deployed in the modern poultry industry.