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. 2024 May 22;24(11):3317.
doi: 10.3390/s24113317.

A Robust End-to-End IoT System for Supporting Workers in Mining Industries

Marios Vlachos  1 , Lampros Pavlopoulos  1 , Anastasios Georgakopoulos  1 , Georgios Tsimiklis  1 , Angelos Amditis  1
Affiliations

A Robust End-to-End IoT System for Supporting Workers in Mining Industries

Marios Vlachos et al. Sensors (Basel). .

Abstract

The adoption of the Internet of Things (IoT) in the mining industry can dramatically enhance the safety of workers while simultaneously decreasing monitoring costs. By implementing an IoT solution consisting of a number of interconnected smart devices and sensors, mining industries can improve response times during emergencies and also reduce the number of accidents, resulting in an overall improvement of the social image of mines. Thus, in this paper, a robust end-to-end IoT system for supporting workers in harsh environments such as in mining industries is presented. The full IoT solution includes both edge devices worn by the workers in the field and a remote cloud IoT platform, which is responsible for storing and efficiently sharing the gathered data in accordance with regulations, ethics, and GDPR rules. Extended experiments conducted to validate the IoT components both in the laboratory and in the field proved the effectiveness of the proposed solution in monitoring the real-time status of workers in mines.

Keywords: Internet of Things; data warehouse; edge processing; localization; mining industry; real-time monitoring; sensor networks; smart devices; wearables; worker safety.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure A1
Figure A1
Schematic of the smart garment hub (1/2).
Figure A2
Figure A2
Schematic of the smart garment hub (2/2).
Figure A3
Figure A3
Schematic of the smart garment sensors board.
Figure A4
Figure A4
Schematic of the ultra-wideband board.
Figure A5
Figure A5
Schematic of the smart garment hub switch and battery charger.
Figure A6
Figure A6
Wristband’s PCB schematic.
Figure A7
Figure A7
Schematic of the smart earplugs (1/3).
Figure A8
Figure A8
Schematic of the smart earplugs (2/3).
Figure A9
Figure A9
Schematic of the smart earplugs (3/3).
Figure A10
Figure A10
Schematic of the smart earplugs’ daughterboard.
Figure 1
Figure 1
High-level smart garment architecture.
Figure 2
Figure 2
Architecture of the smart garment hub.
Figure 3
Figure 3
High-level architecture of the smart garment hub.
Figure 4
Figure 4
Wristband’s architecture.
Figure 5
Figure 5
Architecture of the smart earplugs.
Figure 6
Figure 6
PCB 3D layouts: (a) Microcontroller unit, (b) Ultra-wideband module, (c) Sensor module, (d) Battery charger and switch.
Figure 7
Figure 7
Wristband’s PCB design: (a) Top side, (b) Bottom side.
Figure 8
Figure 8
Wristband’s PCB after assembly: (a) Top side, (b) Bottom side.
Figure 9
Figure 9
3D representation of the smart earplugs’ hardware.
Figure 10
Figure 10
Side view with the hidden activation switch illustrated (on the left of the charging port).
Figure 11
Figure 11
Top side of the enclosure, with the charging port (USB Type-C connector) illustrated.
Figure 12
Figure 12
Bottom side of the enclosure with the belt clip illustrated.
Figure 13
Figure 13
Mechanical drawing of the wristband’s casing.
Figure 14
Figure 14
Final version of the wristband.
Figure 15
Figure 15
3M Peltor Optime I protective earmuffs.
Figure 16
Figure 16
IIoT platform architecture.
Figure 17
Figure 17
Illustration of data flow.
Figure 18
Figure 18
Marini-Marmi testing campaign.
Figure 19
Figure 19
Marini-Marmi testing setup.
Figure 20
Figure 20
CO measurements (smart garment measurements, Norlab stationary sensor measurements, and calibrated measurements).
Figure 21
Figure 21
NO2 measurements (smart garment measurements, Norlab stationary sensor measurements, and calibrated measurements).
Figure 22
Figure 22
NH3 measurements (smart garment measurements, Norlab stationary sensor measurements, and calibrated measurements).
Figure 23
Figure 23
Outdoor channel impulse response.
Figure 24
Figure 24
Received signal strength versus distance for various transceiver configurations.
Figure 25
Figure 25
Received signal strength for indoor line-of-sight localization.
Figure 26
Figure 26
Distance measurements’ mean error and standard deviation values.
Figure 27
Figure 27
Distance measurements for non-line of sight conditions at a 15-m true distance.
Figure 28
Figure 28
Kemi mine—anchor installation and localization map.
Figure 29
Figure 29
Titania mine—anchor grid according to the localization application.
Figure 30
Figure 30
Smart garment noise level measurements.
Figure 31
Figure 31
Heart rate—wristband versus Empatica E4.
Figure 32
Figure 32
EDA—wristband versus Empatica E4.
Figure 33
Figure 33
Skin temperature—wristband versus Empatica E4.
Figure 34
Figure 34
SpO2—wristband versus commercial finger-based oximeter.
Figure 35
Figure 35
Dashboard visualizing biometric data acquired from the wristband.
See this image and copyright information in PMC

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