A highly scalable and autonomous spectroscopic radiation mapping system with resilient IoT detector units for dosimetry, safety and security

Abstract

Technologies utilising radiological materials across power generation, defence, industry, research, and medicine have increased the global inventory of highly active and hazardous materials. Resultantly, an amplified threat exists of illicitly obtained materials being used as part of hostile acts. The potential for intentional releases occurs alongside risks from natural disasters or facility accidents. In any such event, it is crucial to rapidly assess the release composition and extent for response and remediation activities. Therefore, the deployment of an effective, resilient, and autonomous radiation monitoring network is pivotal both during and after an incident. Underpinning this assessment is the detailed understanding of the pre-event, or background, radiation levels, the knowledge of which is also essential in assessing a populations dosimetric exposure to, and impact from, anthropogenic and naturally occurring/varying sources of ionising radiation. Presented here is a fully operational cloud-based spectroscopic radiation mapping platform comprising IoT modules compatible with cellular networks, without modification, in over 180 countries. Combined with locally roaming vehicles, a continuous multi-pass radiological characterisation of an urban environment was performed. Such IoT devices are deployable as either individual sensors, for specific localised temporal events, or integrated over a greater time period (and area) to represent a larger static sensor. Over several months of continued operation, more than one million individual location-referenced gamma-ray spectra were collected and securely uploaded, in real-time, to an online cloud database and automatically characterised via a custom multi-step workflow. Fine-scale local variations in the radiological fingerprint of a 1 km $\times$ 1 km urban area were subsequently rendered in near-real-time to an interactive secure online graphical dashboard for temporal, spatial, and spectral interrogation by the user. Considerations for the automated ‘elastic’ handling of ever-expanding volumes of input data have been carried out, facilitating propagation and expansion of the systems database without human input.

Are the epidemic prevention facilities effective? How cities should choose epidemic prevention facilities: Taking Wuhan as an example

“…In recent decades, more and more cities around the world have been affected by urban disasters, so urban public safety issues have become a big obstacle for urban development (1,2). The suddenness of natural disasters, the frequency of man-made disasters, and the proliferation of public health and safety events have led to a significant increase in the types and contents of disasters, which needs to be considered for urban disaster prevention (3)(4)(5). The current high population density, high population mobility, delayed infrastructure construction, chaotic structural layout, and large building vulnerability in cities have brought a severe test to the safety of cities (6,7).…”

IoT-Enabled System for Detection, Monitoring, and Tracking of Nuclear Materials

“…Vinh Tran-Quang and Hung Dao-Viet reported an Internet of Radiation Sensor System based on the LoRa platform [28]. So, after the literature review [23][24][25][26][27][28][29][30][31][32], it is clear that the Internet of Things is key to improving radiation detection and tracking nuclear material. Thus, in this work, an experimental lowcost IoT system is reported and discussed which sends the detected events to the cloud, with the aim of reducing the lack of reports for IoT radiation detection electronic systems.…”