A distributed and interconnected network of sensors for environmental radiological monitoring

Abstract The W-MON project aims to improve and automatize the control of the presence of radioactive material in conventional waste containers at CERN using a distributed network of interconnected low-power radiation sensors. The key development is the integration of a lightweight but sensitive radiation sensor in a powerful network that allows continuous data recording, transfer and storage in a database for alarm triggering and subsequent data analysis. The Chiyoda D-shuttle personal dosimeter was used as proof-of-concept. Extensive tests performed with the commercial version of the D-shuttle showed that its robustness, stability under variable thermal conditions, high sensitivity and hourly dose logging capabilities make it a strong candidate for the project. To comply with the requirements of remote operation and wireless data transmission to a central server, a customized version of the D-shuttle has been developed. Two additional radiation sensors are also currently being considered. The sensors have been coupled to a custom-made communication board allowing for long-range low-power LoRa wireless data transmission. A centralized IoT (Internet of Things) end-to-end data architecture has been developed for real-time monitoring and visualization of the radiation level in waste containers before the final integration into REMUS, the overall CERN Radiation and Environment Monitoring Unified Supervision service.

[1]  Christer Åhlund,et al.  Propagation Model Evaluation for LoRaWAN: Planning Tool Versus Real Case Scenario , 2019, 2019 IEEE 5th World Forum on Internet of Things (WF-IoT).

[2]  Thomas Frosio,et al.  Classification of radiological objects at the exit of accelerators with a dose-rate constraint. , 2020, Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine.

[3]  Thomas H. Clausen,et al.  A Study of LoRa: Long Range & Low Power Networks for the Internet of Things , 2016, Sensors.

[4]  D. Ekendahl,et al.  Testing of the D-Shuttle personal dosemeter , 2017 .

[5]  S. Mayer,et al.  Use of the D-Shuttle dosimeter for radiation protection of members of the public: Characterization and feasibility study , 2019, Radiation Measurements.

[6]  James E. McLaughlin.  Measurement of Low-Level Radioactivity, ICRU-22 , 1973 .

[7]  G. Knoll.  Radiation detection and measurement , 1979 .

[8]  Fabio Pozzi.  CERN Radiation Protection (RP) calibration facilities , 2016 .

[9]  L. A. Currie,et al.  LIMITS FOR QUALITATIVE DETECTION AND QUANTITATIVE DETERMINATION. APPLICATION TO RADIOCHEMISTRY. , 1968 .

[10]  Md. Shahidul Islam,et al.  Error evaluation of the D-shuttle dosimeter technique in positron emission tomography study , 2019, Radiological Physics and Technology.

[11]  F. Ravotti,et al.  CERN IRRADIATION FACILITIES , 2018, Radiation protection dosimetry.

[12]  Mahesh Sooriyabandara,et al.  Low Power Wide Area Networks: An Overview , 2016, IEEE Communications Surveys & Tutorials.

[13]  N Sato,et al.  Measurement and comparison of individual external doses of high-school students living in Japan, France, Poland and Belarus—the ‘D-shuttle’ project— , 2015, Journal of radiological protection : official journal of the Society for Radiological Protection.

[14]  Graham Roger Stevenson,et al.  Radiological safety aspects of the operation of proton accelerators , 1988 .

[15]  Julie A. McCann,et al.  Demystifying low-power wide-area communications for city IoT applications , 2016, WiNTECH@MobiCom.

[16]  Hiroshi Kawamura,et al.  Intercomparison Exercise at Harshaw 6600, DVG-02TM, and D-Shuttle Dosimeters for the Individual Monitoring of Ionizing Radiation , 2019, Journal of Radiation Protection and Research.

[17]  Wataru Naito,et al.  Relationship between Individual External Doses, Ambient Dose Rates and Individuals’ Activity-Patterns in Affected Areas in Fukushima following the Fukushima Daiichi Nuclear Power Plant Accident , 2016, PloS one.

[18]  Fred L. Drake,et al.  Python 3 Reference Manual , 2009 .

[19]  Konstantin Mikhaylov,et al.  Performance of a low-power wide-area network based on LoRa technology: Doppler robustness, scalability, and coverage , 2017, Int. J. Distributed Sens. Networks.