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An IoT Measurement System Based on LoRaWAN for Additive Manufacturing.

Tommaso Fedullo1,2, Alberto Morato3, Giovanni Peserico4,5

  • 1Department of Engineering "Enzo Ferrari", University of Modena and Reggio Emilia, Via P. Vivarelli 10, 41125 Modena, Italy.

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|July 28, 2022
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Summary

This study evaluates LoRaWAN sensors embedded in 3D-printed parts for Industrial Internet of Things applications. The research assesses energy consumption and long-range capabilities for these inaccessible, embedded smart sensors.

Keywords:
Industrial IoTIoT measurement systemsLoRabattery lifetimesmart monitoringsmart sensors

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Area of Science:

  • Industrial Internet of Things (IIoT)
  • Wireless Sensor Networks
  • Additive Manufacturing

Background:

  • The Industrial Internet of Things (IIoT) leverages smart sensors and low-power wide-area networks (LPWANs) for innovative measurement systems.
  • LoRaWAN (Long Range WAN) is a prominent LPWAN technology, optimized for low energy consumption, long-range coverage, and cost-effective deployment.
  • Additive manufacturing, a key IIoT component, requires advanced measurement capabilities for in-process monitoring and environmental assessment.

Purpose of the Study:

  • To investigate the effectiveness of LoRa-based smart sensors embedded within artifacts during additive manufacturing.
  • To evaluate the performance of these sensors post-deployment, focusing on energy consumption and long-range operation.
  • To assess the suitability of LoRaWAN technology for monitoring embedded sensors in inaccessible IIoT applications.

Main Methods:

  • Experimental evaluation of two LoRa end-nodes: Microchip RN2483 LoRa Mote and Tinovi PM-IO-5-SM LoRaWAN IO Module.
  • Embedding sensors within artifacts during the early stages of the production phase.
  • Assessing sensor behavior and performance in their final deployed location.

Main Results:

  • Analysis of energy consumption patterns for embedded LoRa sensors.
  • Evaluation of the long-range communication capabilities of the LoRaWAN network in the target application.
  • Assessment of the overall effectiveness and suitability of the LoRa-based sensor network design.

Conclusions:

  • LoRa-based sensor networks show promise for IIoT applications, particularly when embedded in manufactured artifacts.
  • Energy optimization and reliable long-range connectivity are critical for the success of inaccessible embedded sensor systems.
  • The study provides insights into battery life prediction and connectivity range for practical LoRaWAN deployments in additive manufacturing.