Abstract
Radon exposure is the second leading cause of lung cancer worldwide, yet monitoring strategies
remain limited, expensive, and unevenly applied. Recent advances in the Internet of
Things (IoT) offer the potential to change radon surveillance through low-cost, real-time,
distributed sensing networks. This review consolidates emerging research on IoT-based radon
monitoring, drawing from both primary radon studies and analogous applications in environmental
IoT. A search across six major databases and relevant grey literature yielded only five
radon-specific IoT studies, underscoring how new this research field is rather than reflecting a
shortcoming of the review. To enhance the analysis, we delve into sensor physics, embedded
system design, wireless protocols, and calibration techniques, incorporating lessons from
established IoT sectors like indoor air quality, industrial safety, and volcanic gas monitoring.
This interdisciplinary approach reveals that many technical and logistical challenges, such as
calibration drift, power autonomy, connectivity, and scalability, have been addressed in related
fields and can be adapted for radon monitoring. By uniting pioneering efforts within the
broader context of IoT-enabled environmental sensing, this review provides a reference point
and a future roadmap. It outlines key research priorities, including large-scale validation,
standardized calibration methods, AI-driven analytics integration, and equitable deployment
strategies. Although radon-focused IoT research is still at an early stage, current progress
suggests it could make continuous exposure assessment more reliable, affordable, and widely
accessible with clear public health benefits.