NB-IoT Sensor Network for Obtaining the Input Data for Hydrological Simulation Model

DOI 10.7160/aol.2021.130105
No 1/2021, March
pp. 59-69

Java, O., Sigajevs, A., Binde, J. and Kepka, M. (2021) “NB-IoT Sensor Network for Obtaining the Input Data for Hydrological Simulation Model", AGRIS on-line Papers in Economics and Informatics, Vol. 13, No. 1, pp. 59-69. ISSN 1804-1930. DOI 10.7160/aol.2021.130105.


The article describes the choice of appropriate network technology that provides sufficient coverage to allow the sensor network to be placed even in the remote and difficult to reach locations and the data to reach the cloud server. Further it describes the components of the sensor network, the operating principle, architecture and the processing of the data obtained to convert them into the input data used in the hydrological simulation model. The NB-IoT sensor network proposed by the authors would not only collect the data needed to operate hydrological simulation models, but, for example, could provide the data needed to forecast weather conditions, particularly if the architecture of this sensor network, because of its low cost, would be widely applied around the globe, joining a unified global sensor network.


Sensor network, internet of things, IoT, sensor data processing, NB-IoT.


  1. 0G Baltics (2020) "Company and Technology". [Online]. Available: https://sigfox.lt// [Accessed: 10 Nov 2020].
  2. Awandallah, S., Moure, D. and Torres-González, P. (2019) "An Internet of Things (IoT) Application on Volcano Monitoring", Sensors, Vol. 19, No. 21, pp. 1-29. ISSN 1424-8220. DOI 10.3390/s19214651.
  3. Behrendt, J. and Zimmermann, K. (2008) "Qualitätskontrolle historischer Klimadaten", Klimastatusbericht 2008, pp. 119-125. E-ISSN 1616-5063. ISSN 1437-7691. ISBN 978-3-88148-441-1.
  4. Chaudhari, B. S., Zennaro, M. and Borkar, S. (2020) "LPWAN Technologies: Emerging Application Characteristics, Requirements, and Design Considerations", Future Internet, Vol. 12, No. 46, pp. 1-25. ISSN 1999-5903. DOI 10.3390/fi12030046.
  5. Custers, J. and Graafstal, H. (2005) "Characterization of the water flow in a pool-ridge microtope in a bog", A case study of Männikjärve bog, Estonia. Wageningen University.
  6. Deutsche Telekom AG (2019) "Mobile IoT guide. How NB-IoT and LTE-M are helping the IoT take off", Bonn. [Online]. Available: https://www.gsma.com/iot/resources/mobile-iot-guide-how-nb-iot-and-lte-m-are-helping-the-iot-take-off/[Accessed: 5 Nov 2020].
  7. DFROBOT (2020) "Wind Speed Sensor Voltage Type 0-5V SKU SEN0170". [Online]. Available: https://wiki.dfrobot.com/Wind_Speed_Sensor_Voltage_Type_0-5V__SKU_SEN0170 [Accessed: 14 Dec 2020].
  8. Dictionary.com, LLC. (2020) "Relative humidity". [Online]. Available: https://www.dictionary.com/browse/relative-humidity [Accessed: 12 Nov 2020].
  9. ECMWF (2020) "Near surface meteorological variables from 1979 to 2018 derived from bias-corrected reanalysis". [Online]. Available: https://cds.climate.copernicus.eu/cdsapp#!/dataset/derived-near-surface-meteorological-variables?tab=overview [Accessed: 4 August 2020].
  10. Furukawa Electric Co., LTD. (2011) "Optical Fiber Rain Gauge Commercialized, Japan Meteorological Agency Verification Obtained, and Sales Launched". [Online]. Available: https://www.furukawa.co.jp/english/what/2011/comm_111207.htm [Accessed: 4 Aug 2020].
  11. Gharehpetian, G. B. and Mohammad Mousavi Agah, S. (2017) "Distributed Generation Systems. Design, Operation and Grid Integration", Elsevier Inc., 588 p. ISBN 9780128042083, E-ISBN 9780128042632.
  12. GSMA (2018) "NB-IoT and LTE-M in the context of 5G. Mobile IoT in the 5G future", London. [Online]. Available: https://www.gsma.com/iot/resources/mobile-iot-5g-future/ [Accessed: 10 Aug 2020].
  13. Guardian News and Media Limited (2020) "Decline in aircraft flights clips weather forecasts` wings". [Online]. Available: https://www.theguardian.com/news/2020/apr/09/decline-aircraft-flights-clips-weather-forecasters-wings-coronavirus [Accessed: 4 Aug 2020].
  14. Ha, J.-H., Im, Y.-H., Kim, H.-H., Sim, N.-J. and Yoon, Y. (2018) "Error Correction of Meteorological Data Obtained with Mini-AWSs Based on Machine Learning", Advances in Meteorology, pp. 1-8. E-ISSN 1687-9317, ISSN 1687-9309. DOI 10.1155/2018/7210137.
  15. Hoyos, C. D., Ceballos, L. I., Pérez-Carrasquilla, J. S., Sepulveda, J., López-Zapata, S. M., Zuluaga, M. D., Velásquez, N., Herrera-Mejía, L., Hernández, O., Guzmán-Echavarría, G. and Zapata, M. (2019) "Meteorological conditions leading to the 2015 Salgar flash flood: Lessons for vulnerable regions in tropical complex terrain", Natural Hazards and Earth System Sciences, Vol. 19, No. 11, pp. 2635-2665. ISSN 16849981. DOI 10.5194/nhess-19-2635-2019.
  16. Hua, W., Zhou, L., Nicholson, S. E., Chen, H. and Qin, M. (2019) "Assessing reanalysis data for understanding rainfall climatology and variability over Central Equatorial Africa", Climate Dynamics, Vol. 53, No. 1-2, pp. 651-669. E-ISSN 1432-0894, ISSN 0930-7575. DOI 10.1007/s00382-018-04604-0.
  17. Idbella, M., Iadaresta, M., Gagliarde, G., Mennella, A., Mazzoleni, S. and Bonanomi, G. (2020) "AgriLogger: A New Wireless Sensor for Monitoring Agrometeorological Data in Areas Lacking Communication Networks", Sensors, Vol. 20, pp. 1-13. E-ISSN 1424-8220. DOI 10.3390/s20061589.
  18. Iqbal, M., Abdullah, A. and Shabnam, F. (2020) "An Application Based Comparative Study of LPWAN Technologies for IoT Environment", 2020 IEEE Region 10 Symposium, pp. 1857-1860. DOI 10.1109/TENSYMP50017.2020.9230597.
  19. i-SCOOP (2020) "Cumulocity IoT recognized as IoT platform leader, launches new release". [Online]. Available: https://www.i-scoop.eu/cumulocity-iot/ [Accessed: 4 Aug 2020].
  20. Ismail, N. L., Kassim, M., Ismail, M. and Mohamad, R. (2018) "A review of low power wide area technology in licensed and unlicensed spectrum for IoT use cases", Bulletin of Electrical Engineering and Informatics, Vol. 7, No. 2, pp. 183-190. E-ISSN 2302-9285, ISSN 2089-3191. DOI 10.11591/eei.v7i2.1174.
  21. Jacobsen, D. and Dangles, O. (2017) "Ecology of High Altitude Waters", Oxford: Oxford University Press. ISBN-13: 9780198736868. DOI 10.1093/oso/9780198736868.001.0001.
  22. Java, O. (2018) "Restoration of a Degraded Bog Hydrological Regime Using System Dynamics Modeling", pp. 1105-1113, Prague: CBU International Conference on Innovations in Science and Education. DOI 10.12955/cbup.v6.1301.
  23. kursors.lv (2017) "Lattelecom Rīgā izbūvējis lietu interneta tīklu. Ielādēts no Tehnoloģiju ziņas, apskati un attieksme". [Online]. Available: https://kursors.lv/2017/07/01/lattelecom-riga-izbuvejis-lietu-interneta-tiklu/ [Accessed: 16 Oct 2020]. (in Latvian
  24. Latvijas Mobilais Telefons (2020) "NB-IoT". [Online]. Available: https://bizness.lmt.lv/lv/nb-apraksts [Accessed: 16 Oct 2020].
  25. Liu, W., Zhang, C., Liu, P., Yan, M., Wnag, B., Zhang, J. and Higgs, R. (2018) "Application of Temperature Prediction Based on Neural Network in Intrusion Detection of IoT", Security and Communication Networks, Vol. 2018, pp. 1-10. E-ISSN 1939-0122, ISSN 1939-0114. DOI 10.1155/2018/1635081.
  26. Lufft (2020) "Technical Data. OTT Parsivel2 - Laser Weather Sensor". [Online]. Available: https://www.lufft.com/products/precipitation-sensors-287/ott-parsivel2-laser-weather-sensor-2399/productAction/outputAsPdf/ [Accessed: 23 Oct 2020].
  27. Mashal, A. F. and Fernald, A. G. (2020) "Identifying Capabilities and Potentials of System Dynamics in Hydrology and Water Resources as a Promising Modeling Approach for Water Management", Water, Vol. 12, No. 1342, pp. 1-23. ISSN 2073-4441. DOI 10.3390/w12051432.
  28. Mekki, K., Bajic, E., Chaxel, F. and Meyer, F. (2017) "A comparative study of LPWAN technologies for large-scale IoTdeployment", ICT Express, Vol. 5, No. 1, pp. 1-7. ISSN 2405-9595. DOI 10.1016/j.icte.2017.12.005.
  29. Met Office College (2020) "How we measure wind". [Online]. Available: https://www.metoffice.gov.uk/weather/guides/observations/how-we-measure-wind [Accessed: 23 Oct 2020].
  30. Mwakwate, C. B., Malik, H., Alam, M. M., Moullec, Y. L., Parad, S. and Mumtaz, S. (2019) "Narrowband Internet of Things (NB-IoT): From Physical (PHY) and Media Access Control (MAC) Layers Perspectives", Sensors, pp. 1-34. ISSN 1424-8220. DOI 10.3390/s19112613.
  31. National Weather Service (2020) "Wind Speed". [Online]. Available: Search: https://forecast.weather.gov/glossary.php?word=WIND%20SPEED [Accessed: 23 Oct 2020].
  32. Ndehedehe, C. E. (2019) "The water resources of tropical West Africa: problems, progress, and prospects", Acta Geophysica, Vol. 67, No. 2, pp. 621-649. ISSN 18957455. DOI 10.1007/s11600-019-00260-y.
  33. O'Keffe, J., Marcinkowski, P., Utratna, M., Pinewski, M., Kardel, I., Kundzewicz, Z. W. and Okruszko, T. (2019) "Modelling Climate Change’s Impact on the Hydrology of Natura 2000 Wetland Habitats in the Vistula and Odra River Basins in Poland", Water, Vol. 11, No. 10, pp. 1-24. ISSN 2073-4441. DOI 10.3390/w11102191.
  34. Onal, A. C., Sezer, O. B., Ozbayoglu, M. and Dogdu, E. (2017) "Weather Data Analysis and Sensor Fault Detection Using an Extended IoT Framework with Semantics, Big Data and Machine Learning", 2017 IEEE International Conference on Big Data, pp. 1-10. Boston. DOI 10.1109/BigData.2017.8258150.
  35. Pellarin, T., Román-Cascón, C., Baron, C., Bindlish, R., Brocca, L., Camberlin, P.,, Fernández-Prieto, D., H. Kerr, Y. H., Massari, Ch., Panthou, G., Perrimond, B., Philippon, N. and Quantin, G. (2020) "The precipitation inferred from soil moisture (PrISM) near real-time rainfall product: Evaluation and comparison", Remote Sensing, Vol. 12, No. 3, pp. 1-18. ISSN 2072-4292. DOI 10.3390/rs12030481.
  36. Schlyter, P. (2017) "How bright are natural light sources?". [Online]. Available: http://stjarnhimlen.se/comp/radfaq.html#10 [Accessed: 25 Oct 2020].
  37. Seeed Technology Co., Ltd. (2020) "Groove - Temperature & Humidity Sensor (SHT31)". [Online]. Available: https://www.seeedstudio.com/Grove-Temperature-Humidity-Sensor-SHT31.html [Accessed: 28 Oct 2020].
  38. Sigfox (2020) "Coverage". [Online]. Available: https://www.sigfox.com/en/coverage [Accessed: 26 Oct 2020].
  39. Software AG (2020) "Cumulocity IoT capabilities". [Online]. Available: https://www.softwareag.cloud/site/capability/cumulocity-iot.html#/ [Accessed: 25 Oct 2020].
  40. Staes, J., Rubarenzya, M. H., Meire, P. and Willems , P. (2009) "Modelling hydrological effects of wetland restoration: a differentiated view", Water Science & Technology, pp. 433-441. ISSN 0273-1223. DOI 10.2166/wst.2009.884.
  41. Takami, G., Tokuoka, M., Goto, H. and Nozaka, Y. (2016) "Machine Learning Applied to Sensor Data Analysis", Yokogawa Technical Report English Edition, Vol. 59, No. 1, pp. 27-30. ISSN 0911-8977.
  42. Tektronix (2015) "11 Power Consumption Measuremet Techniques". [Online]. Available: https://www.tek.com/document/how-guide/11-power-consumption-measurement-techniques [Accessed: 3 Aug 2020].
  43. tet (2020) "Pirmais lietu interneta tīkls Latvijā". [Online]. Available: https://iot.tet.lv/lv [Accessed: 14 Sept 2020]. (in Latvian).
  44. Texas Instruments Inc. (2020) "NB-IoT Power Topologies for Smart Meter Wireless Modules Using Primary Cells Reference Design". Dallas. [Online]. Available: https://www.ti.com/lit/pdf/tidueo0b [Accessed: 14 Sept 2020]. (in Latvian).
  45. Valsts Vides ģeoloģijas un meteoroloģijas centrs (2020) "Novērojumu stacijas". [Online]. Available: https://www.meteo.lv/meteorologijas-staciju-karte/?nid=460 [Accessed: 15 Oct 2020]. (in Latvian).
  46. Vodafone Group (2017) "Narrowband IoT: pushing the boundaries of IoT". [Online]. Available: https://www.vodafone.com/business/news-and-insights/white-paper/narrowband-iot-pushing-the-boundaries-of-iot [Accessed: 3 Aug. 2020].
  47. Xie, X., Wu, D., Liu, S. and Li, R. (2017) "IoT Data Analytics Using Deep Learning", Computer Science, Networking and Internet Architecture, pp. 1-11. arXiv:1708.03854.
  48. Yahia, E. M. (2019) "Postharvest Technology of Perishable Horticultural Commodities", Elsevier, E-ISBN 9780128132777, ISBN 9780128132760.
  49. Yamamoto, K., Togami, T., Yamuchi, N. and Ninomiya, S. (2017) "Machine Learning-Based Calibration of Low-Cost Air Temperature Sensors Using Environmental Dat", Sensors, pp. 1-16. ISSN 1424-8220. DOI 10.3390/s17061290.
  50. Yang, M., He, W., Zhang, Z., Xu, Y., Yang, H., Chen, Y. and Xu, X. (2019) "An efficient storage and service method for multi-source merging meteorological big data in cloud environment", EURASIP Journal on Wireless Communications and Networking, Vol. 241, pp. 1-12. ISSN 1687-1499. DOI 10.1186/s13638-019-1576-0.

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