Autors: Lishev S., Spasov, G. V., Petrova, G. I.
Title: LoRaWAN IoT System for Measuring Air Parameters in a Traffic Monitoring Station †
Keywords: environmental parameters monitoring, intelligent transport systems, IoT system, LoRa and LoRaWAN

Abstract: Traffic measurement systems are an essential part of intelligent transportation systems (ITS). These are specialized transport infrastructures where traffic data is collected and analyzed in order to optimize the use of road systems, improve transport safety, and implement future transport plans. The rapid development of transportation systems, urbanization, and industrialization have led to a global problem of air pollution. This has raised the topical issue of measuring and monitoring environmental parameters at traffic monitoring stations in ITS. In this paper, we present a wireless environmental monitoring system, which is a subsystem of a traffic monitoring station. Along with measuring traffic parameters, the station also collects useful meteorological information. A novel hybrid, dual-band IoT system based on LoRa and LoRaWAN for environmental parameters monitoring is presented. The hardware realization of a developed hybrid LoRaWAN end device, together with the sensors used for the measurement of air parameters, is described. Initial results from real test monitoring of environmental parameters on the road in urban environments are presented as a proof of concept. The presented wireless environmental monitoring system can also be used for indoor or outdoor air pollution monitoring, serving as a useful complement to intelligent transport systems.

References

  1. Todorov A. Gicheva P. Stoykova V. Karapetkov S. Uzunov H. Dechkova S. Zlatev Z. Environmental Monitoring in Bus Transportation Using a Developed Measurement System Urban Sci. 2023 7 90 10.3390/urbansci7030090
  2. Waheb A.J. Thanasrii S. Andre E.O. Mohd I.S. Wenyan W. Oliveira M.A. LoRaWAN-Based IoT System Implementation for Long-Range Outdoor Air Quality Monitoring Internet Things 2022 19 100540
  3. Feinberg S.N. Williams R. Hagler G. Low J. Smith L. Brown R. Garver D. Davis M. Morton M. Schaefer J. et al. Examining spatiotemporal variability of urban particulate matter and application of high-time resolution data from a network of low-cost air pollution sensors Atmos. Environ. 2019 213 579 584 10.1016/j.atmosenv.2019.06.026 34121907
  4. Taştan M. Gökozan H. Real-Time Monitoring of Indoor Air Quality with Internet of Things-Based E-Nose Appl. Sci. 2019 9 3435 10.3390/app9163435
  5. Cotrim J. Kleinschmidt J. An analytical model for multihop LoRaWAN networks Internet Things 2023 22 100807 10.1016/j.iot.2023.100807
  6. Garrido-Hidalgo C. Roda-Sanchez L. Ramírez F. Fernández-Caballero A. Olivares T. Efficient online resource allocation in large-scale LoRaWAN networks: A multi-agent approach Comput. Netw. 2023 221 109525 10.1016/j.comnet.2022.109525
  7. Popa D. Udrea F. Towards Integrated Mid-Infrared Gas Sensors Sensors 2019 19 2076 10.3390/s19092076 31060244
  8. Andrews D.L. Rayleigh Scattering and Raman Effect Theory Academic Press Cambridge, MA, USA 2017 924 930 9780128032244

Issue

Engineering Proceedings, vol. 100, 2025, Albania, https://doi.org/10.3390/engproc2025100017

Вид: статия в списание, публикация в реферирано издание, индексирана в Scopus