Literature DB >> 33396278

Low-Cost IoT-Based Sensor System: A Case Study on Harsh Environmental Monitoring.

Ali Imam Sunny1, Aobo Zhao1, Li Li1, Sambu Kanteh Sakiliba2.   

Abstract

Wireless Sensor Networks (WSNs) are promising technologies for exploiting in harsh environments such as can be found in the nuclear industry. Nuclear storage facilities can be considered harsh environments in that, amongst other variables, they can be dark, congested, and have high gamma radiation levels, which preclude operator access. These conditions represent significant challenges to sensor reliability, data acquisition and communications, power supplies, and longevity. Installed monitoring of parameters such as temperature, pressure, radiation, humidity, and hydrogen content within a nuclear facility may offer significant advantages over current baseline measurement options. This paper explores Commercial Off-The-Shelf (COTS) components to comprise an installed Internet of Things (IoT)-based multipurpose monitoring system for a specific nuclear storage situation measuring hydrogen concentration and temperature. This work addresses two major challenges of developing an installed remote sensing monitor for a typical nuclear storage scenario to detect both hydrogen concentrations and temperature: (1) development of a compact, cost-effective, and robust multisensor system from COTS components, and (2) validation of the sensor system for detecting temperature and hydrogen gas release. The proof of concept system developed in this study not only demonstrates the cost reduction of regular monitoring but also enables intelligent data management through the IoT by using ThingSpeak in a harsh environment.

Entities:  

Keywords:  IoT; condition monitoring; energy harvesting; harsh environment; low-cost sensor; wireless sensor network

Year:  2020        PMID: 33396278     DOI: 10.3390/s21010214

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  9 in total

Review 1.  Toward Integrated Large-Scale Environmental Monitoring Using WSN/UAV/Crowdsensing: A Review of Applications, Signal Processing, and Future Perspectives.

Authors:  Alessio Fascista
Journal:  Sensors (Basel)       Date:  2022-02-25       Impact factor: 3.576

2.  Scientific Developments and New Technological Trajectories in Sensor Research.

Authors:  Mario Coccia; Saeed Roshani; Melika Mosleh
Journal:  Sensors (Basel)       Date:  2021-11-24       Impact factor: 3.576

3.  LSTM-Based Path Prediction for Effective Sensor Filtering in Sensor Registry System.

Authors:  Haotian Chen; Sukhoon Lee; Byung-Won On; Dongwon Jeong
Journal:  Sensors (Basel)       Date:  2021-12-03       Impact factor: 3.576

4.  The Prototype Monitoring System for Pollution Sensing and Online Visualization with the Use of a UAV and a WebRTC-Based Platform.

Authors:  Agnieszka Chodorek; Robert Ryszard Chodorek; Alexander Yastrebov
Journal:  Sensors (Basel)       Date:  2022-02-17       Impact factor: 3.576

Review 5.  A Review of Gas Measurement Set-Ups.

Authors:  Łukasz Fuśnik; Bartłomiej Szafraniak; Anna Paleczek; Dominik Grochala; Artur Rydosz
Journal:  Sensors (Basel)       Date:  2022-03-27       Impact factor: 3.576

6.  Lightweight Self-Detection and Self-Calibration Strategy for MEMS Gas Sensor Arrays.

Authors:  Bing Liu; Yanzhen Zhou; Hongshuo Fu; Ping Fu; Lei Feng
Journal:  Sensors (Basel)       Date:  2022-06-07       Impact factor: 3.847

Review 7.  Wearable Walking Assistant for Freezing of Gait With Environmental IoT Monitoring: A Contribution to the Discussion.

Authors:  Rafael A Bernardes; Filipa Ventura; Hugo Neves; Maria Isabel Fernandes; Pedro Sousa
Journal:  Front Public Health       Date:  2022-06-20

8.  Open and Cost-Effective Digital Ecosystem for Lake Water Quality Monitoring.

Authors:  Daniele Strigaro; Massimiliano Cannata; Fabio Lepori; Camilla Capelli; Andrea Lami; Dario Manca; Silvio Seno
Journal:  Sensors (Basel)       Date:  2022-09-04       Impact factor: 3.847

9.  Monitoring and Predictive Maintenance of Centrifugal Pumps Based on Smart Sensors.

Authors:  Lei Chen; Lijun Wei; Yu Wang; Junshuo Wang; Wenlong Li
Journal:  Sensors (Basel)       Date:  2022-03-09       Impact factor: 3.576

  9 in total

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