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

Author:

Hernández-Gutiérrez Carlos A.1ORCID,Delgado-del-Carpio Marcelo2,Zebadúa-Chavarría Lizette A.3,Hernández-de-León Héctor R.1ORCID,Escobar-Gómez Elias N.1ORCID,Quevedo-López Manuel4

Affiliation:

1. Tecnológico Nacional de México Campus Tuxtla, Carretera Panamericana Km 1080, Tuxtla Gutiérrez C.P. 29050, Mexico

2. Electrical Department, Universidad Nacional de San Agustín de Arequipa, Santa Catalina No. 117, Arequipa 04001, Peru

3. Programa de Nanociencias y Nanotecnología, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Av. Instituto Politécnico Nacional 2508, Mexico City C.P. 07360, Mexico

4. Department of Materials Science and Engineering, University of Texas at Dallas, Richardson, TX 75080, USA

Abstract

A low-cost embedded system for high-energy radiation detection applications was developed for national security proposes, mainly to detect nuclear material and send the detection event to the cloud in real time with tracking capabilities. The proof of concept was built with state-of-the-art electronics such as an adequate Si-based photodetector, a trans-impedance amplifier, an ARM Cortex M4 microcontroller with sufficient ADC capture capabilities, an ESP8266 Internet of Things (IoT) module, an optimized Message Queuing Telemetry Transport (MQTT) protocol, a MySQL data base, and a Python handler program. The system is able to detect alfa particles and send the nuclear detection events to the CloudMQTT servers. Moreover, the detection message records the date and time of the ionization event for the tracking application, and due to a particular MQTT-optimized protocol the message is sent with low latency. Furthermore, the designed system was validated with a standard radiation instrumentation preamplifier 109A system from ORTEC company, and more than one node was demonstrated with an internet connection employing a 20,000 bits/s CloudMQTT plan. Therefore, the design can be escalated to produce a robust big data multisensor network.

Funder

TecNM/ITTG

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering

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