Skip to main content
SpringerLink
Log in

Applicability of Wireless Sensor Networks in Precision Agriculture: A Review

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

Presently, wireless sensor network (WSN) plays important role in engineering, science, agriculture and many other field like surveillance, military applications, smart cars etc. Precision agriculture (PA) is one of the field in which WSN is widely adopted. The aim of the adoption of WSNs in PA is to measure the different environmental parameters such as humidity, temperature, soil moisture, PH value of soil etc., for enhancing the quantity and quality of crops. Further, the WSNs are also helped to reduce the consumptions of the natural resources used in farming. Hence, the aim of this review is to identify the various WSNs technologies adopted for precision agriculture and impact of these technologies to achieve smart agriculture. This review also focuses on the different environmental parameters like irrigation, monitoring, soil properties, temperature for achieving precision agriculture. Further, a detailed study is also carried out on different crops which are covered using WSNs technologies. This review also highlights on the different communication technologies and sensors available for PA. To analyze the impact of the WSNs in agriculture field, several research questions are designed and through this review, we are tried to find the solutions of these research questions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Abbreviations

APTEEN:

Adaptive periodic threshold-sensitive energy efficient sensor network protocol

AMSR-E:

Advanced microwave scanning radiometer for the earth observing system

ASCAT:

Advanced scatterometer

BOP:

Beacon only period

CMOS:

Complementary metal–oxide–semiconductor

CSMA:

Carrier-sense multiple access

DCTA:

Dynamic converge cast tree algorithm

DEEC:

Distributed energy efficient clustering

DGNSS:

Differential global navigation satellite system

DSSS:

Direct-sequence spread spectrum

ECA:

Electrical conductivity

ECHERP:

Equalized cluster head election routing protocol

EEHC:

Energy efficient hierarchical clustering

EMI:

Electromagnetic induction

FHSS:

Frequency-hopping spread spectrum

GFSK:

Gaussian frequency shift keying

GIS:

Geographical information system

GPRS:

General packet radio service

GPS:

Global positioning system

IC:

Integrated circuit

IEEE:

Institute of Electrical and Electronics Engineers

IOT:

Internet of thing

IRT:

Interactive response technology

LAA:

Last address assignment

LLC:

Logical link control layer

MAC:

Media access control address

MC:

Moisture content

MIR:

Mid-infrared

MLR:

Multiple regression analysis

NIR:

Near-infrared spectroscopy

NS2:

Network simulator 2

OASNDFA:

Optimized algorithm of sensor node deployment for intelligent agricultural monitoring

OC:

Organic carbon

OFDM:

Orthogonal frequency-division multiplexing

OGC:

Open Geospatial Consortium

OS:

Operating system

PA:

Precision agriculture

PCR:

Principal component regression

pH:

Potential of hydrogen

PIR Sensor:

Passive infrared sensor

PLSR:

Partial least squares regression

PRI:

Polarization ratio index

PRR:

Packet reception ratio

RBHR:

Region-based hybrid routing protocol

RF:

Radio frequency

RIFD:

Radio frequency identification

RIMCS:

Remote irrigation monitoring and control system

RQ:

Research question

RSSI:

Received signal strength indicator)

SBC:

Single board computer

SCI:

Science citation index

SMSS:

Soil moisture sensor system

SNDCP:

Sub network dependent convergence protocol

SoC:

System on chip

SQL:

Structured Query Language

SWE:

Sensor Web Enablement

TC:

Canopy temperature

TDR:

Time-domain reflectometer

TDT:

Time domain transmissometry

TN:

Total nitrogen

UAV:

Unmanned-aircraft vehicle

URI:

Uniform Resource Identifier

USB:

Universal Serial Bus

vis–NIR:

Visible near infrared

VRI:

Variable rate irrigation

Wi-Fi:

Wireless fidelity

WiMAX:

Worldwide Interoperability for microwave access

WISC:

Wireless in-field sensing and control

WSAN:

Wireless sensor and actuator network

WSN:

Wireless sensor network

WUSNs:

Wireless underground sensor networks

References

  1. Yick, J., Mukherjee, B., & Ghosal, D. (2008). Wireless sensor network survey. Computer Networks, 52(12), 2292–2330.

    Article  Google Scholar 

  2. Baronti, P., Pillai, P., Chook, V. W., Chessa, S., Gotta, A., & Hu, Y. F. (2007). Wireless sensor networks: A survey on the state of the art and the and the 802.15.4 ZigBee standards. Computer Communications, 30(7), 1655–1695.

    Article  Google Scholar 

  3. Kutter, T., Tiemann, S., Siebert, R., & Fountas, S. (2011). The role of communication and co-operation in the adoption of precision farming. Precision Agriculture, 12(1), 2–17.

    Article  Google Scholar 

  4. Polo, J., Hornero, G., Duijneveld, C., García, A., & Casas, O. (2015). Design of a low-cost wireless sensor network with UAV mobile node for agricultural applications. Computers and Electronics in Agriculture, 119, 19–32.

    Article  Google Scholar 

  5. Abbasi, A. Z., Islam, N., & Shaikh, Z. A. (2014). A review of wireless sensors and networks’ applications in agriculture. Computer Standards & Interfaces, 36(2), 263–270.

    Article  Google Scholar 

  6. Garcia-Sanchez, A. J., Garcia-Sanchez, F., & Garcia-Haro, J. (2011). Wireless sensor network deployment for integrating video-surveillance and data-monitoring in precision agriculture over distributed crops. Computers and Electronics in Agriculture, 75(2), 288–303.

    Article  Google Scholar 

  7. Zhang, R., Ren, Z., Sun, J., Tang, W., Ning, D., & Qian, Y. (2017). Method for monitoring the cotton plant vigor based on the WSN technology. Computers and Electronics in Agriculture, 133, 68–79.

    Article  Google Scholar 

  8. Sai, Z., Fan, Y., Yuliang, T., Lei, X., & Yifong, Z. (2016). Optimized algorithm of sensor node deployment for intelligent agricultural monitoring. Computers and Electronics in Agriculture, 127, 76–86.

    Article  Google Scholar 

  9. Jiang, J. A., Wang, C. H., Liao, M. S., Zheng, X. Y., Liu, J. H., Chuang, C. L., et al. (2016). A wireless sensor network-based monitoring system with dynamic convergecast tree algorithm for precision cultivation management in orchid greenhouses. Precision Agriculture, 17(6), 766–785.

    Article  Google Scholar 

  10. Kim, Y. D., Yang, Y. M., Kang, W. S., & Kim, D. K. (2014). On the design of beacon based wireless sensor network for agricultural emergency monitoring systems. Computer Standards & Interfaces, 36(2), 288–299.

    Article  Google Scholar 

  11. Bapat, V., Kale, P., Shinde, V., Deshpande, N., & Shaligram, A. (2017). WSN application for crop protection to divert animal intrusions in the agricultural land. Computers and Electronics in Agriculture, 133, 88–96.

    Article  Google Scholar 

  12. Portz, G., Molin, J. P., & Jasper, J. (2012). Active crop sensor to detect variability of nitrogen supply and biomass on sugarcane fields. Precision Agriculture, 13(1), 33–44.

    Article  Google Scholar 

  13. Reiser, D., Paraforos, D. S., Khan, M. T., Griepentrog, H. W., & Vázquez-Arellano, M. (2017). Autonomous field navigation, data acquisition and node location in wireless sensor networks. Precision Agriculture, 18(3), 279–292.

    Article  Google Scholar 

  14. Smiljkovikj, K., & Gavrilovska, L. (2014). SmartWine: Intelligent end-to-end cloud-based monitoring system. Wireless Personal Communications, 78(3), 1777–1788.

    Article  Google Scholar 

  15. Díaz, S. E., Pérez, J. C., Mateos, A. C., Marinescu, M. C., & Guerra, B. B. (2011). A novel methodology for the monitoring of the agricultural production process based on wireless sensor networks. Computers and Electronics in Agriculture, 76(2), 252–265.

    Article  Google Scholar 

  16. Zhu, B., Han, W., Wang, Y., Wang, N., Chen, Y., & Guo, C. (2014). Development and evaluation of a wireless sensor network monitoring system in various agricultural environments. Journal of Microwave Power and Electromagnetic Energy, 48(3), 170–183.

    Article  Google Scholar 

  17. Srbinovska, M., Gavrovski, C., Dimcev, V., Krkoleva, A., & Borozan, V. (2015). Environmental parameters monitoring in precision agriculture using wireless sensor networks. Journal of Cleaner Production, 88, 297–307.

    Article  Google Scholar 

  18. Yu, X., Wu, P., Han, W., & Zhang, Z. (2013). A survey on wireless sensor network infrastructure for agriculture. Computer Standards & Interfaces, 35(1), 59–64.

    Article  Google Scholar 

  19. Abouzar, P., Michelson, D. G., & Hamdi, M. (2016). RSSI-based distributed self-localization for wireless sensor networks used in precision agriculture. IEEE Transactions on Wireless Communications, 15(10), 6638–6650.

    Article  Google Scholar 

  20. El-Kader, S. M. A., & El-Basioni, B. M. M. (2013). Precision farming solution in Egypt using the wireless sensor network technology. Egyptian Informatics Journal, 14(3), 221–233.

    Article  Google Scholar 

  21. Georgieva, T., Paskova, N., Gaazi, B., Todorov, G., & Daskalov, P. (2016). Design of wireless sensor network for monitoring of soil quality parameters. Agriculture and Agricultural Science Procedia, 10, 431–437.

    Article  Google Scholar 

  22. Kaiwartya, O., Abdullah, A. H., Cao, Y., Raw, R. S., Kumar, S., Lobiyal, D. K., et al. (2016). T-MQM: Testbed-based multi-metric quality measurement of sensor deployment for precision agriculture—A case study. IEEE Sensors Journal, 16(23), 8649–8664.

    Google Scholar 

  23. Tan Lam, P., Le Quang, T., Le Nguyen, N., & Dat Nguyen, S. (2018). Wireless sensing modules for rural monitoring and precision agriculture applications. Journal of Information and Telecommunication, 2(1), 107–123.

    Article  Google Scholar 

  24. An, W., Ci, S., Luo, H., Wu, D., Adamchuk, V., Sharif, H., et al. (2015). Effective sensor deployment based on field information coverage in precision agriculture. Wireless Communications and Mobile Computing, 15(12), 1606–1620.

    Article  Google Scholar 

  25. Lee, W. S., & Ehsani, R. (2015). Sensing systems for precision agriculture in Florida. Computers and Electronics in Agriculture, 112, 2–9.

    Article  Google Scholar 

  26. Valente, J., Sanz, D., Barrientos, A., Cerro, J. D., Ribeiro, Á., & Rossi, C. (2011). An air-ground wireless sensor network for crop monitoring. Sensors, 11(6), 6088–6108.

    Article  Google Scholar 

  27. Zhang, Z., Wu, P., Han, W., & Yu, X. (2017). Remote monitoring system for agricultural information based on wireless sensor network. Journal of the Chinese Institute of Engineers, 40(1), 75–81.

    Article  Google Scholar 

  28. Li, X. H., Cheng, X., Yan, K., & Gong, P. (2010). A monitoring system for vegetable greenhouses based on a wireless sensor network. Sensors, 10(10), 8963–8980.

    Article  Google Scholar 

  29. Park, D. H., & Park, J. W. (2011). Wireless sensor network-based greenhouse environment monitoring and automatic control system for dew condensation prevention. Sensors, 11(4), 3640–3651.

    Article  Google Scholar 

  30. Mesas-Carrascosa, F. J., Santano, D. V., Meroño, J. E., de la Orden, M. S., & García-Ferrer, A. (2015). Open source hardware to monitor environmental parameters in precision agriculture. Biosystems Engineering, 137, 73–83.

    Article  Google Scholar 

  31. Gutiérrez, J., Villa-Medina, J. F., Nieto-Garibay, A., & Porta-Gándara, M. Á. (2014). Automated irrigation system using a wireless sensor network and GPRS module. IEEE Transactions on Instrumentation and Measurement, 63(1), 166–176.

    Article  Google Scholar 

  32. Levy, D., Coleman, W. K., & Veilleux, R. E. (2013). Adaptation of potato to water shortage: irrigation management and enhancement of tolerance to drought and salinity. American Journal of Potato Research, 90(2), 186–206.

    Article  Google Scholar 

  33. Hedley, C. B., Roudier, P., Yule, I. J., Ekanayake, J., & Bradbury, S. (2013). Soil water status and water table depth modelling using electromagnetic surveys for precision irrigation scheduling. Geoderma, 199, 22–29.

    Article  Google Scholar 

  34. Navarro-Hellín, H., Torres-Sánchez, R., Soto-Valles, F., Albaladejo-Pérez, C., López-Riquelme, J. A., & Domingo-Miguel, R. (2015). A wireless sensors architecture for efficient irrigation water management. Agricultural Water Management, 151, 64–74.

    Article  Google Scholar 

  35. Nolz, R., Kammerer, G., & Cepuder, P. (2013). Calibrating soil water potential sensors integrated into a wireless monitoring network. Agricultural Water Management, 116, 12–20.

    Article  Google Scholar 

  36. Viani, F., Bertolli, M., Salucci, M., & Polo, A. (2017). Low-cost wireless monitoring and decision support for water saving in agriculture. IEEE Sensors Journal, 17(13), 4299–4309.

    Article  Google Scholar 

  37. Kim, Y., Evans, R. G., & Iversen, W. M. (2008). Remote sensing and control of an irrigation system using a distributed wireless sensor network. IEEE Transactions on Instrumentation and Measurement, 57(7), 1379–1387.

    Article  Google Scholar 

  38. Zhao, W., Li, J., Yang, R., & Li, Y. (2018). Determining placement criteria of moisture sensors through temporal stability analysis of soil water contents for a variable rate irrigation system. Precision Agriculture, 19(4), 648–665.

    Article  Google Scholar 

  39. Chávez, J. L., Pierce, F. J., Elliott, T. V., Evans, R. G., Kim, Y., & Iversen, W. M. (2010). A remote irrigation monitoring and control system (RIMCS) for continuous move systems. Part B: Field testing and results. Precision Agriculture, 11(1), 11–26.

    Article  Google Scholar 

  40. Maurya, S., & Jain, V. K. (2016). Fuzzy based energy efficient sensor network protocol for precision agriculture. Computers and Electronics in Agriculture, 130, 20–37.

    Article  Google Scholar 

  41. Sawant, S., Durbha, S. S., & Jagarlapudi, A. (2017). Interoperable agro-meteorological observation and analysis platform for precision agriculture: A case study in citrus crop water requirement estimation. Computers and Electronics in Agriculture, 138, 175–187.

    Article  Google Scholar 

  42. Kim, Y., & Evans, R. G. (2009). Software design for wireless sensor-based site-specific irrigation. Computers and Electronics in Agriculture, 66(2), 159–165.

    Article  Google Scholar 

  43. Coates, R. W., Delwiche, M. J., Broad, A., & Holler, M. (2013). Wireless sensor network with irrigation valve control. Computers and Electronics in Agriculture, 96, 13–22.

    Article  Google Scholar 

  44. Nikolidakis, S. A., Kandris, D., Vergados, D. D., & Douligeris, C. (2015). Energy efficient automated control of irrigation in agriculture by using wireless sensor networks. Computers and Electronics in Agriculture, 113, 154–163.

    Article  MATH  Google Scholar 

  45. Nagarajan, G., & Minu, R. I. (2018). Wireless soil monitoring sensor for sprinkler irrigation automation system. Wireless Personal Communications, 98(2), 1835–1851.

    Article  Google Scholar 

  46. Goumopoulos, C., O’Flynn, B., & Kameas, A. (2014). Automated zone-specific irrigation with wireless sensor/actuator network and adaptable decision support. Computers and Electronics in Agriculture, 105, 20–33.

    Article  Google Scholar 

  47. Kim, Y., Schmid, T., Charbiwala, Z. M., Friedman, J., & Srivastava, M. B. (2008). NAWMS: Nonintrusive autonomous water monitoring system. In Proceedings of the 6th ACM conference on embedded network sensor systems (pp. 309–322). ACM.

  48. Masseroni, D., Facchi, A., Depoli, E. V., Renga, F. M., & Gandolfi, C. (2016). Irrig-OH: An open-hardware device for soil water potential monitoring and irrigation management. Irrigation and Drainage, 65(5), 750–761.

    Article  Google Scholar 

  49. Wong, B. P., & Kerkez, B. (2016). Real-time environmental sensor data: An application to water quality using web services. Environmental Modelling and Software, 84, 505–517.

    Article  Google Scholar 

  50. Lozoya, C., Mendoza, C., Aguilar, A., Román, A., & Castelló, R. (2016). Sensor-based model driven control strategy for precision irrigation. Journal of Sensors, 2016, 9784071. https://doi.org/10.1155/2016/9784071.

    Article  Google Scholar 

  51. Rossel, R. A. V., & Bouma, J. (2016). Soil sensing: A new paradigm for agriculture. Agricultural Systems, 148, 71–74.

    Article  Google Scholar 

  52. Bernardi, A. D. C., Bettiol, G. M., Ferreira, R. D. P., Santos, K. E. L., Rabello, L. M., & Inamasu, R. Y. (2016). Spatial variability of soil properties and yield of a grazed alfalfa pasture in Brazil. Precision Agriculture, 17(6), 737–752.

    Article  Google Scholar 

  53. Kuang, B., & Mouazen, A. M. (2013). Effect of spiking strategy and ratio on calibration of on-line visible and near infrared soil sensor for measurement in European farms. Soil and Tillage Research, 128, 125–136.

    Article  Google Scholar 

  54. Pedrera-Parrilla, A., Van De Vijver, E., Van Meirvenne, M., Espejo-Pérez, A. J., Giráldez, J. V., & Vanderlinden, K. (2016). Apparent electrical conductivity measurements in an olive orchard under wet and dry soil conditions: significance for clay and soil water content mapping. Precision Agriculture, 17(5), 531–545.

    Article  Google Scholar 

  55. Fu, W., Tunney, H., & Zhang, C. (2010). Spatial variation of soil nutrients in a dairy farm and its implications for site-specific fertilizer application. Soil and Tillage Research, 106(2), 185–193.

    Article  Google Scholar 

  56. Bogena, H. R., Huisman, J. A., Oberdörster, C., & Vereecken, H. (2007). Evaluation of a low-cost soil water content sensor for wireless network applications. Journal of Hydrology, 344(1–2), 32–42.

    Article  Google Scholar 

  57. Knadel, M., Thomsen, A., Schelde, K., & Greve, M. H. (2015). Soil organic carbon and particle sizes mapping using vis–NIR, EC and temperature mobile sensor platform. Computers and Electronics in Agriculture, 114, 134–144.

    Article  Google Scholar 

  58. Li, Z., Wang, N., Franzen, A., Taher, P., Godsey, C., Zhang, H., et al. (2014). Practical deployment of an in-field soil property wireless sensor network. Computer Standards & Interfaces, 36(2), 278–287.

    Article  Google Scholar 

  59. Ritsema, C. J., Kuipers, H., Kleiboer, L., Van Den Elsen, E., Oostindie, K., Wesseling, J. G., et al. (2009). A new wireless underground network system for continuous monitoring of soil water contents. Water resources research, 45(4), 1–9.

    Article  Google Scholar 

  60. Majone, B., Viani, F., Filippi, E., Bellin, A., Massa, A., Toller, G., et al. (2013). Wireless sensor network deployment for monitoring soil moisture dynamics at the field scale. Procedia Environmental Sciences, 19, 426–435.

    Article  Google Scholar 

  61. Kizito, F., Campbell, C. S., Campbell, G. S., Cobos, D. R., Teare, B. L., Carter, B., et al. (2008). Frequency, electrical conductivity and temperature analysis of a low-cost capacitance soil moisture sensor. Journal of Hydrology, 352(3–4), 367–378.

    Article  Google Scholar 

  62. Cardenas-Lailhacar, B., & Dukes, M. D. (2010). Precision of soil moisture sensor irrigation controllers under field conditions. Agricultural Water Management, 97(5), 666–672.

    Article  Google Scholar 

  63. Brocca, L., Hasenauer, S., Lacava, T., Melone, F., Moramarco, T., Wagner, W., et al. (2011). Soil moisture estimation through ASCAT and AMSR-E sensors: An intercomparison and validation study across Europe. Remote Sensing of Environment, 115(12), 3390–3408.

    Article  Google Scholar 

  64. Ge, Y., Thomasson, J. A., & Sui, R. (2011). Remote sensing of soil properties in precision agriculture: A review. Frontiers of Earth Science, 5(3), 229–238.

    Google Scholar 

  65. Vuran, M. C., & Akyildiz, I. F. (2010). Channel model and analysis for wireless underground sensor networks in soil medium. Physical Communication, 3(4), 245–254.

    Article  Google Scholar 

  66. Badia-Melis, R., Garcia-Hierro, J., Ruiz-Garcia, L., Jiménez-Ariza, T., Villalba, J. I. R., & Barreiro, P. (2014). Assessing the dynamic behavior of WSN motes and RFID semi-passive tags for temperature monitoring. Computers and Electronics in Agriculture, 103, 11–16.

    Article  Google Scholar 

  67. Green, O., Nadimi, E. S., Blanes-Vidal, V., Jørgensen, R. N., Storm, I. M. D., & Sørensen, C. G. (2009). Monitoring and modeling temperature variations inside silage stacks using novel wireless sensor networks. Computers and Electronics in Agriculture, 69(2), 149–157.

    Article  Google Scholar 

  68. Jahnavi, V. S., & Ahamed, S. F. (2015). Smart wireless sensor network for automated greenhouse. IETE Journal of Research, 61(2), 180–185.

    Article  Google Scholar 

  69. Jackson, T., Mansfield, K., Saafi, M., Colman, T., & Romine, P. (2008). Measuring soil temperature and moisture using wireless MEMS sensors. Measurement, 41(4), 381–390.

    Article  Google Scholar 

  70. Martínez, J., Egea, G., Agüera, J., & Pérez-Ruiz, M. (2017). A cost-effective canopy temperature measurement system for precision agriculture: a case study on sugar beet. Precision Agriculture, 18(1), 95–110.

    Article  Google Scholar 

  71. Pierce, F. J., & Elliott, T. V. (2008). Regional and on-farm wireless sensor networks for agricultural systems in Eastern Washington. Computers and Electronics in Agriculture, 61(1), 32–43.

    Article  Google Scholar 

  72. Mahan, J. R., Conaty, W., Neilsen, J., Payton, P., & Cox, S. B. (2010). Field performance in agricultural settings of a wireless temperature monitoring system based on a low-cost infrared sensor. Computers and Electronics in Agriculture, 71(2), 176–181.

    Article  Google Scholar 

  73. Mendez, G. R., & Mukhopadhyay, S. C. (2013). A Wi-Fi based smart wireless sensor network for an agricultural environment. In Wireless sensor networks and ecological monitoring (pp. 247–268). Springer, Berlin.

  74. Zhang, J., Li, W., Han, N., & Kan, J. (2008). Forest fire detection system based on a ZigBee wireless sensor network. Frontiers of Forestry in China, 3(3), 369–374.

    Article  Google Scholar 

  75. Versichele, M., Neutens, T., Delafontaine, M., & Van de Weghe, N. (2012). The use of Bluetooth for analysing spatiotemporal dynamics of human movement at mass events: A case study of the Ghent Festivities. Applied Geography, 32(2), 208–220.

    Article  Google Scholar 

  76. Leroy, D., Detal, G., Cathalo, J., Manulis, M., Koeune, F., & Bonaventure, O. (2011). SWISH: Secure WiFi sharing. Computer Networks, 55(7), 1614–1630.

    Article  Google Scholar 

  77. Gu, Q. H., Lu, C. W., Li, F. B., & Wan, C. Y. (2008). Monitoring dispatch information system of trucks and shovels in an open pit based on GIS/GPS/GPRS. Journal of China University of Mining and Technology, 18(2), 288–292.

    Article  Google Scholar 

  78. Gungor, V. C., & Lambert, F. C. (2006). A survey on communication networks for electric system automation. Computer Networks, 50(7), 877–897.

    Article  Google Scholar 

  79. http://www.stevenswater.com/.

  80. http://au.ictinternational.com/.

  81. https://www.meade.com/.

  82. https://www.sensirion.com/en/.

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Jaypee University of Information Technology, Waknaghat, Solan, Himachal Pradesh, India

    Divyansh Thakur, Yugal Kumar, Arvind Kumar & Pradeep Kumar Singh

Authors
  1. Divyansh Thakur
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yugal Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Arvind Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Pradeep Kumar Singh
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yugal Kumar.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Thakur, D., Kumar, Y., Kumar, A. et al. Applicability of Wireless Sensor Networks in Precision Agriculture: A Review. Wireless Pers Commun 107, 471–512 (2019). https://doi.org/10.1007/s11277-019-06285-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-019-06285-2

Keywords

Search

Navigation