Wireless underground sensor networks (WUSNs) enable large-scale agricultural monitoring for improving farming efficiency and reducing pollution. A WUSN system based on the long range wide area network (LoRaWAN) standard is proposed. A novel LoRaWAN-based simulator is developed to model wireless signal attenuation and path loss in an underground environment by incorporating the Peplinski and modified Friis models. The simulator incorporates the full network stack of the LoRa physical and MAC layers. Simulation results show LoRaWAN-based WUSNs (with a node burial depth of 50 cm) can maintain network connectivity with a range of over several kilometres. The simulation results also show the regional duty cycle restriction significantly reduces network scalability due to acknowledgements from end-devices. For agricultural applications where such frequent acknowledgements are not required, the results show a LoRaWAN WUSN is scalable. A field experiment to evaluate the accuracy of the theoretical path loss model was conducted and results were found to agree with the simulations.
This is a preview of subscription content, access via your institution.
Buy single article
Instant access to the full article PDF.
Price excludes VAT (USA)
Tax calculation will be finalised during checkout.
Akyildiz IF, Stuntebeck EP (2006) Wireless underground sensor networks: research challenges. Ad Hoc Netw 4(6):669–686. https://doi.org/10.1016/j.adhoc.2006.04.003
Alsheikh MA, Lin S, Niyato D, Tan H (2014) Machine learning in wireless sensor networks: algorithms, strategies, and applications in IEEE. Commun Surv Tutor 16(4):1996–2018. https://doi.org/10.1109/COMST.2014.2320099
Augustin A, Yi J, Clausen T, Townsley W (2016) A study of LoRa: long range and low power networks for the internet of things. Sensors 16(9):1466. https://doi.org/10.3390/s16091466
Bogena H, Huisman J, Meier H, Rosenbaum U, Weuthen A (2009) Hybrid wireless underground sensor networks: quantification of signal attenuation in soil. Vadose Zone J 8:755–761. https://doi.org/10.2136/vzj2008.0138
Bor MC, Roedig U, Voigt T, Alonso JM (2016) Do LoRa low-power wide-area networks scale?. In: Proceedings of the 19th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM’16) 59–67.
Cardell-Oliver R, Kranz M, Smettem K, Mayer K (2005) A reactive soil moisture sensor network: design and field evaluation. Int J Distrib Sens Netw 1(2):149–162. https://doi.org/10.1080/15501320590966422
Choi M, Jacobs JM (2007) Soil moisture variability of root zone profiles within SMEX02 remote sensing footprints. Adv Water Resour 30(4):883–896. https://doi.org/10.1016/j.advwatres.2006.07.007
Decagon Devices Inc. (2016) 5TE Water Content, EC and Temperature Sensor. https://manuals.decagon.com/Retired%20and%20Discontinued/Manuals/13509_5TE_Web.pdf. Accessed 29 November 2019.
Dobson M, Ulaby F, Hallikainen M, El-rayes M (1985) Microwave Dielectric Behavior of Wet Soil-Part II: Dielectric Mixing Models. IEEE Trans Geosci Remote Sens GE-23(1):35–46. https://doi.org/10.1109/TGRS.1985.289498
Domingo MC (2012) Magnetic induction for underwater wireless communication networks. IEEE Trans Antennas Propag 60(6):2929–2939. https://doi.org/10.1109/TAP.2012.2194670
Dong X, Vuran MC, Irmak S (2013) Autonomous precision agriculture through integration of wireless underground sensor networks with center pivot irrigation systems. Ad Hoc Netw 11(7):1975–1987. https://doi.org/10.1016/j.adhoc.2012.06.012
Gulbahar B, Akan OB (2012) A communication theoretical modeling and analysis of underwater magneto-inductive wireless channels. IEEE Trans Wirel Commun 11(9):3326–3334. https://doi.org/10.1109/TWC.2012.070912.111943
Kisseleff S, Akyildiz IF, Gerstacker WH (2018) Survey on advances in magnetic induction based wireless underground sensor networks. IEEE Internet Things J 5(6):4843–4856. https://doi.org/10.1109/JIOT.2018.2870289
Kumar DP, Amgoth T, Annavarapu CSR (2019) Machine learning algorithms for wireless sensor networks: a survey. Inform Fus 49:1–25. https://doi.org/10.1016/j.inffus.2018.09.013
Li L, Vuran MC, Akyildiz IF (2007) Characteristics of underground channel for wireless underground sensor networks. In: Proceedings of the 6th annual mediterranean Ad Hoc networking workshop, pp 92–99
LoRa Alliance® (2017) LoRaWAN® Specification v1.1. https://lora-alliance.org/resource-hub/lorawantm-specification-v11. Accessed 29 November 2019.
LoRa Alliance® (2019) About LoRaWAN®. https://lora-alliance.org/about-lorawan. Accessed 29 November 2019.
Mekki K, Bajic E, Chaxel F, Meyer F (2018) A comparative study of LPWAN technologies for large-scale IoT deployment. ICT Express 5(1):1–7. https://doi.org/10.1016/j.icte.2017.12.005
Musăloiu ER., Terzis A, Szlavecz K, Szalay A, Cogan J, Gray J (2006) LifeUnder your feet: a wireless soil ecology sensor network. In: Proceedings of the 3rd workshop on embedded networked sensors, pp 51–55
Peplinski NR, Ulaby FT, Dobson MC (1995) Dielectric properties of soils in the 0.3–1.3-GHz range. IEEE Trans Geosci Remote Sens 33(3):803–807. https://doi.org/10.1109/36.387598
Petajajarvi J, Mikhaylov K, Roivainen A, Hanninen T, Pettissalo M (2015) On the coverage of LPWANs: range evaluation and channel attenuation model for LoRa technology. In: Proceedings of the 14th International Conference on ITS Telecommunications (ITST), pp 55–59. https://doi.org/10.1109/ITST.2015.7377400
Pop A-I, Raza U, Kulkarni P, Sooriyabandara M (2017) Does bidirectional traffic do more harm than good in LoRaWAN based LPWAN networks?. CoRR, abs/1704.0. https://arxiv.org/abs/1704.04174. Accessed 29 November 2019.
Rappaport T (2001) Wireless communications: principles and practice, 2nd edn. Prentice Hall PTR, Upper Saddle River
Raza U, Kulkarni P, Sooriyabandara M (2017) Low power wide area networks: an overview. IEEE Commun Surv Tutor 19(2):855–873. https://doi.org/10.1109/COMST.2017.2652320
Robinson DA, Jones SB, Wraith JM, Or D, Friedman SP (2003) A review of advances in dielectric and electrical conductivity measurement in soils using time domain reflectometry. Vadose Zone J 2(4):444. https://doi.org/10.2113/2.4.444
Sadeghioon AM, Chapman DN, Metje N, Anthony CJ (2017) A new approach to estimating the path loss in underground wireless sensor networks. J Sens Act Netw 6(3):18. https://doi.org/10.3390/jsan6030018
Salam A, Vuran MC (2016) Impacts of soil type and moisture on the capacity of multi-carrier modulation in internet of underground things. In: Proceedings of the 25th international conference on computer communications and networks (ICCCN), pp 1–9. https://doi.org/10.1109/ICCCN.2016.7568532
Semtech (2016) Sx1276/77/78/79 Datasheet. https://www.semtech.com/products/wireless-rf/lora-transceivers/sx1276#download-resources. Accessed 29 November 2019.
Shaw JA (2013) Radiometry and the Friis transmission equation. Am J Phys 81(1):33–37. https://doi.org/10.1119/1.4755780
Silva AR, Vuran MC (2009) Empirical evaluation of wireless underground-to-underground communication in wireless underground sensor networks. In: Krishnamachari B, Suri S, Heinzelman W, Mitra U (eds) Distributed computing in sensor systems. DCOSS 2009. Lecture notes in computer science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02085-8_175516
Silva AR, Vuran MC (2010) (CPS)ˆ2: Integration of center pivot systems with wireless underground sensor networks for autonomous precision agriculture. In: Proceedings of the 1st ACM/IEEE international conference on cyber-physical systems–ICCPS’10. ACM Press, New York, USA, pp 79–88. https://doi.org/10.1145/1795194.1795206
Spencer BF, Ruiz-Sandoval ME, Kurata N (2004) Smart sensing technology: opportunities and challenges. Struct Control Health Monit 11(4):349–368. https://doi.org/10.1002/stc.48
Sun Z, Akyildiz IF (2010) Magnetic induction communications for wireless underground sensor networks. IEEE Trans Antennas Propag 58(7):2426–2435. https://doi.org/10.1109/TAP.2010.2048858
Team SimPy (2019) Overview of SimPy 3.0.11 documentation-discrete event simulation for Python. https://simpy.readthedocs.io/en/latest/. Accessed 29 November 2019.
Ulaby FT, Moore RK, Fung AK (1986) Microwave remote sensing. Artech House, Dedham, MA
van Dam RL, Borchers B, Hendrickx JMH (2005) Methods for prediction of soil dielectric properties: a review. In: Proceedings of SPIE 5794, detection and remediation technologies for mines and minelike targets X, vol 5794. International Society for Optics and Photonics, pp 188–197. https://doi.org/10.1117/12.602868
Vuran MC, Silva AR (2010) Communication through soil in wireless underground sensor networks—theory and practice. In: Ferrari G (ed) Sensor networks. Signals and communication technology. Springer, Berlin Heidelberg
Vuran MC, Akyildiz IF (2010) Channel model and analysis forwireless underground sensor networks in soil medium. Phys Commun 3(4):245–254. https://doi.org/10.1016/j.phycom.2010.07.001
Wang YPE, Lin X, Adhikary A, Grövlen A, Sui Y, Blankenship Y, Bergman J, Razaghi HS (2016) A primer on 3GPP narrowband internet of things (NB-IoT). https://arxiv.org/abs/1606.04171. Accessed 29 November 2019.
Whiting D, Wilson C, Card (2003) Estimating soil texture. 14:1–7. https://www.caryinstitute.org/sites/default/files/public/downloads/lesson-plans/estimating_soil_texture.pdf. Accessed 29 November 2019
Zemmour H, Baudoin G, Diet A (2017) Soil Effects on the underground-to-aboveground communication link in ultrawideband wireless underground sensor networks. IEEE Antennas Wirel Propag Lett 16:218–221. https://doi.org/10.1109/LAWP.2016.2570298
Zhang X, Andreyev A, Zumpf C, Negri MC, Guha S, Ghosh M (2017) Thoreau: a subterranean wireless sensing network for agriculture and the environment. In: Proceedings of the 2017 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), pp 78–84. https://doi.org/10.1109/INFCOMW.2017.8116356
Wu S, Wang KIK, Ivoghlian A, Salcic Z, Austin A, Zhou X (2019) LWS: a LoRaWAN wireless underground sensor network simulator for agriculture applications. In: Proceedings of the 19th IEEE conference on ubiquitous intelligence & computing UIC'2019. https://doi.org/10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00123.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations
About this article
Cite this article
Wu, S., Austin, A.C.M., Ivoghlian, A. et al. Long range wide area network for agricultural wireless underground sensor networks. J Ambient Intell Human Comput 14, 4903–4919 (2023). https://doi.org/10.1007/s12652-020-02137-1