A Feasibility Study on Using LoRa Link Characteristics to Predict Ambient Air Temperature Conference

Ma, A, Rodriguez, JT, Sha, M et al. (2025). A Feasibility Study on Using LoRa Link Characteristics to Predict Ambient Air Temperature . 10.1109/INFOCOMWKSHPS65812.2025.11152842

cited authors

  • Ma, A; Rodriguez, JT; Sha, M; Luo, D

authors

abstract

  • Air temperature monitoring is essential for many Internet of Things (IoT) applications. Many existing applications rely on the readings provided by the weather stations maintained by federal, regional, or local government agencies. Although the accuracy of the data provided by these weather stations is high, the ability of such data to reflect the temperature variability experienced by urban populations is generally low because the measurements are collected at the mesoscale. In reality, air temperature varies on a micro- and local scale, and the health risks associated with extreme weather are assumed to vary with exposure. In this work, we study the feasibility of using LoRa link characteristics to predict ambient air temperature. Our empirical study shows that there exists a complex nonlinear dependence between air temperature and LoRa link characteristics and it is beneficial to consider multiple link metrics for training instead of solely relying on RSS measurements.

publication date

  • January 1, 2025