Towards the Optimal RF Sensing Strategy for IoT Applications: An Ice Sensing Case Study

Remote ice detection has recently emerged as an application of Radio Frequency (RF) sensors. While RF sensing is a feasible approach used for detecting various stimuli, the optimal system architecture and design strategy for RF-based sensing in future Internet of Things (IoT) systems remains unclear. In this paper, we propose a systematic methodology for designing an RF-based sensing system, applicable to a plethora of IoT applications. The proposed methodology is used to design printable antennas as highly-sensitive sensors for detecting and measuring the thickness of ice, demonstrating best-in-class sensory response. Antenna design is investigated systematically for wireless interrogation in the 2.4 GHz band, to support a variety of IoT protocols. Following the proposed methodology, the antenna's realized gain was identified as the optimum parameter-under-test. The developed loop antenna sensor exhibits a high linearity, resilience to interference, and applicability to different real-world deployment environments, demonstrated through over 90% average ice thickness measurement accuracy and at least 5 dB real-time sensitivity to ice deposition.