Poster: OpenRadon Lab: Democratizing Soil Radon Modeling and Mapping Alireza Marefat ∗ Georgia State University Atlanta, Georgia, USA amrefatvayghani1@gsu.edu Abbaas Alif Mohamed Nishar Georgia State University Atlanta, Georgia, USA amohamednishar1@student.gsu.edu Nikhil Karve Georgia State University Atlanta, Georgia, USA nkarve1@student.gsu.edu Ashwin Ashok Georgia State University Atlanta, Georgia, USA ashok@gsu.edu ABSTRACT The goal of this research is to model the spatio-temporal dependen- cies of radon gas generation and movement underground. In this regard, we have embarked upon an interdisciplinary research efort that involves studying the dependencies of radon gas emanation with soil and environmental parameters. To this end we design, implement and deploy an innovative real-time sensor network, OpenRadon Lab, to develop a radon prediction model that maps its distribution along space and time. This network constitutes a soil-to-cloud wireless computing framework to enable machine learning assisted soil radon prediction, and optimized data ofoad- ing to conserve computing resources on the sensing devices. CCS CONCEPTS · Information systems → Sensor networks; · Hardware → Sensor applications and deployments. KEYWORDS Radon, Measurement, Sensor, Wireless, Cloud, Testbed ACM Reference Format: Alireza Marefat, Abbaas Alif Mohamed Nishar, Nikhil Karve, and Ashwin Ashok. 2022. Poster: OpenRadon Lab: Democratizing Soil Radon Modeling and Mapping. In Proceedings of (MobiSys ’22). ACM, New York, NY, USA, 2 pages. https://doi.org/10.1145/3498361.3538800 1 INTRODUCTION Radon (222Rn) is a noble heavy radioactive gas produced by the uranium (238U) decay series, specifcally by the decay of 226Ra. Exposure to indoor radon is estimated to cause 3 to 20 percent of all lung cancer deaths [1], being the second cause after smoking. It is estimated that over 21,000 deaths occur annually in the United States because of lung cancers attributed to radon exposure, as Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for proft or commercial advantage and that copies bear this notice and the full citation on the frst page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specifc permission and/or a fee. Request permissions from permissions@acm.org. MobiSys ’22, June 27 - July 1, 2022, Portland, OR © 2022 Association for Computing Machinery. ACM ISBN 978-1-4503ś9185-6/22/06. . . $15.00 https://doi.org/10.1145/3498361.3538800 Figure 1: OpenRadon Lab Conceptual Architecture reported by the US Nuclear Regulatory Commission (NRC) in 1999 and the US Environmental Protection Agency (EPA) in 2003 and 2009. Geology is the most important factor controlling the source and distribution of 222Rn [2]. Some rock types, such as granite and felsic volcanic rocks, show high uranium levels. It has been shown that high radon levels are often observed close to geological faults [3]. Soil processes are potentially modulating the geological source of radon. The entire metropolitan area of Atlanta (Georgia, USA) is classifed as a high-risk zone. Recent studies [4] have also shown that soil water content, and soil characteristics, such as texture (particle size distribution), bulk density, and porosity, that exert a strong infuence on soil water content, are highly relevant to radon exhalation through the soil. 593