Abstract
A reliable and highly scalable Internet of Things (IoT) end-to-end data infrastructure has been developed for environmental radiation monitoring at the European Organization for Nuclear Research (CERN) based on a low-power wide-area network (LPWAN). The proposed system, called Waste radiation MONitoring (W-MON), consists of an interconnected network of thousands of highly sensitive and ultralow-power gamma radiation sensors acting as long range (LoRa) transceivers. The aim of the system is to improve and automatize the radiological controls of conventional waste containers. The end devices measure the radiation levels in the waste containers on a continuous basis and send the data periodically to the LoRaWAN network server. The network has been deployed in an outdoor environment covering hundreds of hectares. A set of web-based user applications for real-time monitoring, data visualization, and status control of the devices have been designed based on open-source tools. The data pipeline infrastructure has been designed to allow an easy integration into the overall CERN Radiation and Environment Monitoring Unified Supervision service (REMUS).
Highlights
A reliable and highly scalable Internet of Things (IoT) end-to-end data infrastructure has been developed for environmental radiation monitoring at CERN based on a LowPower Wide-Area Network (LPWAN)
The first level control consists in the routine monitoring of waste containers by radiation protection technicians equipped with a hand-held radiation survey meter
The goal of this paper is to provide a detailed description of the W-MON IoT infrastructure and of the evaluation of the CERN LoRa network within the scope of the W-MON
Summary
N the field of radiation protection, environmental radiation monitoring is essential to control the exposure to ionizing radiation and to protect the people and the environment from potential radiation hazards. Wireless data transmission for real-time monitoring of the radiation levels in standard waste containers. The system proposed in this paper benefits from the potential of IoT networks to monitor large areas [15] for the radiological control of waste containers. The second alternative was based on a master-slave model; seven of the eight individual sensors per container, i.e. slaves, sent the data to the eighth unit that acted as a master collecting all the information for subsequent transfer to the server The latter was proposed to reduce the number of devices sending data simultaneously and reduce the potential number of collisions [27].
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