A Review of the Applications of the Internet of Things (IoT) for Agricultural Automation

Abstract

Purpose

The Internet of Things (IoT) is a network of devices for communicating machine to machine (M2M) based on wired and wireless Internet. IoT in agriculture is a revolutionary technology that can be applied to agricultural production year-round. The aim of this study is to summarize cases of IoT being applied to agricultural automation in the agricultural sector and to discuss the limitations and prospects for expanding the application of IoT technology in Korea.

Methods

The application of IoT in agriculture was classified and analyzed based on previous data, and the sensors and communication technologies used were compared. Based on the analysis results, the limitations of and prospects for IoT in agriculture were discussed.

Results

IoT was widely used in agriculture, such as management systems, monitoring systems, control systems, and unmanned machinery. In addition, the various wireless communication technologies used in agriculture, such as Wi-Fi, long-range wide area network (LoRaWAN), mobile communication (e.g., 2G, 3G, and 4G), ZigBee, and Bluetooth, were also used in IoT-based agriculture.

Conclusion

With the development of various communication technologies, such as 5G, it is expected that faster and broader IoT technologies will be applied to various agricultural processes in the future. IoT-based agriculture equipped with a communication system suitable for each agricultural environment can contribute to agricultural automation by increasing crop quality and production and reducing labor.

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Abbreviations

DGPS:

Differential global positioning system

GPRS:

General packet radio service

GPS:

Global positioning system

GSM:

Global system for mobile communications

IoT:

Internet of things

LoRa:

Long range

LoRaWAN:

Long-range wide area network

M2M:

Machine to machine

NFC:

Near-field communication

RFID:

Radio frequency identification

WSN:

Wireless sensor network

References

  1. Aafreen, R., Neyaz, S. Y., Shamim, R., & Beg, M. S. (2019). An IoT based system for telemetry and control of greenhouse environment. In: 2019 International Conference on Electrical, Electronics and Computer Engineering (UPCON), pp. 1–6, Aligarh, India: IEEE.

  2. Abd El-kader, S. M., & El-Basioni, B. M. M. (2013). Precision farming solution in Egypt using the wireless sensor network technology. Egyptian Informatics Journal, 14(3), 221–233. https://doi.org/10.1016/j.eij.2013.06.004.

    Article  Google Scholar 

  3. Adame, T., Bel, A., Bellalta, B., Barcelo, J., & Oliver, M. (2014). IEEE 802.11 ah: the WiFi approach for M2M communications. IEEE Wireless Communications, 21(6), 144–152. https://doi.org/10.1109/MWC.2014.7000982.

    Article  Google Scholar 

  4. Akkaş, M. A., & Sokullu, R. (2017). An IoT-based greenhouse monitoring system with Micaz motes. Procedia Computer Science, 113, 603–608. https://doi.org/10.1016/j.procs.2017.08.300.

    Article  Google Scholar 

  5. Ananthi, N., Divya, J., Divya, M., & Janani, V. (2017). IoT based smart soil monitoring system for agricultural production. In: 2017 IEEE Technological Innovations in ICT for Agriculture and Rural Development (TIAR), pp. 209–214, Chennai, India: IEEE.

  6. Anastasi, G., Conti, M., Di Francesco, M., & Passarella, A. (2009). Energy conservation in wireless sensor networks: a survey. Ad Hoc Networks, 7(3), 537–568. https://doi.org/10.1016/j.adhoc.2008.06.003.

    Article  Google Scholar 

  7. Ande, P., & Rojatkar, D. (2017). A survey: application of IoT. International Research Journal of Engineering and Technology, 4(10), 347–350.

    Google Scholar 

  8. Antony, A. P., Leith, K., Jolley, C., Lu, J., & Sweeney, D. J. (2020). A review of practice and implementation of the Internet of Things (IoT) for smallholder agriculture. Sustainability, 12(9), 3750. https://doi.org/10.3390/su12093750.

    Article  Google Scholar 

  9. Aqeel-ur-Rehman, A., 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. https://doi.org/10.1016/j.csi.2011.03.004.

    Article  Google Scholar 

  10. AshifuddinMondal, M., & Rehena, Z. (2018). IoT based intelligent agriculture field monitoring system. In: 2018 8th International Conference on Cloud Computing, Data Science & Engineering (Confluence), pp. 625–629, Noida, India: IEEE.

  11. Astill, J., Dara, R. A., Fraser, E. D., Roberts, B., & Sharif, S. (2020). Smart poultry management: smart sensors, big data, and the Internet of Things. Computers and Electronics in Agriculture, 170, 105291. https://doi.org/10.1016/j.compag.2020.105291.

    Article  Google Scholar 

  12. Baseca, C. C., Sendra, S., Lloret, J., & Tomas, J. (2019). A smart decision system for digital farming. Agronomy, 9(5), 216. https://doi.org/10.3390/agronomy9050216.

    Article  Google Scholar 

  13. BigAg. (2018). Autonomous tractors- the future of farming? http://www.bigag.com/topics/equipment/autonomous-tractors-future-farming/. Accessed 18 January 2018.

  14. Borgia, E. (2014). The internet of things vision: key features, applications and open issues. Computer Communications, 54, 1–31. https://doi.org/10.1016/j.comcom.2014.09.008.

    Article  Google Scholar 

  15. Boursianis, A. D., Papadopoulou, M. S., Diamantoulakis, P., Liopa-Tsakalidi, A., Barouchas, P., Salahas, G., et al. (2020). Internet of Things (IoT) and agricultural unmanned aerial vehicles (UAVs) in smart farming: a comprehensive review. Internet of Things, 100187. https://doi.org/10.1016/j.iot.2020.100187.

  16. Bu, F., & Wang, X. (2019). A smart agriculture IoT system based on deep reinforcement learning. Future Generation Computer Systems, 99, 500–507. https://doi.org/10.1016/j.future.2019.04.041.

    Article  Google Scholar 

  17. Chaudhary, R., Pandey, J. R., Pandey, P., & Chaudhary, P. (2015). Case study of Internet of Things in area of agriculture, ‘AGCO's fuse technology's’ ‘connected farm services’. In: 2015 International Conference on Green Computing and Internet of Things (ICGCIoT), pp. 148–153, Noida, India: IEEE.

  18. Chowdhury, B. S., & Raghukiran, N. (2017). Autonomous sprinkler system with Internet of Things. International Journal of Applied Engineering Research, 12(16), 5430–5432.

    Google Scholar 

  19. Dagar, R., Som, S., & Khatri, S. K. (2018). Smart farming – IoT in agriculture. In: 2018 International Conference on Inventive Research in Computing Applications (ICIRCA), pp. 1052–1056, Coimbatore, India: IEEE.

  20. Dallimore, K. (2017). Precision livestock farming. https://www.canadianpoultrymag.com/health/precision-livestock-farming-30052. Accessed 23 January 2017.

  21. Debauche, O., El Moulat, M., Mahmoudi, S., Boukraa, S., Manneback, P., & Lebeau, F. (2018). Web monitoring of bee health for researchers and beekeepers based on the internet of things. Procedia Computer Science, 130, 991–998. https://doi.org/10.1016/j.procs.2018.04.103.

    Article  Google Scholar 

  22. Dhall, R., & Agrawal, H. (2018). An improved energy efficient duty cycling algorithm for IoT based precision agriculture. Procedia Computer Science, 141, 135–142. https://doi.org/10.1016/j.procs.2018.10.159.

    Article  Google Scholar 

  23. Dholu, M., & Ghodinde, K. A. (2018). Internet of Things (IoT) for precision agriculture application. In: 2018 2nd International Conference on Trends in Electronics and Informatics (ICOEI), pp. 339–342, Thirunelveli, India: IEEE.

  24. Diène, B., Rodrigues, J. J., Diallo, O., Ndoye, E. H. M., & Korotaev, V. V. (2020). Data management techniques for Internet of Things. Mechanical Systems and Signal Processing, 138, 106564. https://doi.org/10.1016/j.ymssp.2019.106564.

    Article  Google Scholar 

  25. Edwards-Murphy, F., Magno, M., Whelan, P. M., O’Halloran, J., & Popovici, E. M. (2016). B+ WSN: smart beehive with preliminary decision tree analysis for agriculture and honey bee health monitoring. Computers and Electronics in Agriculture, 124, 211–219. https://doi.org/10.1016/j.compag.2016.04.008.

    Article  Google Scholar 

  26. FAO. (2017). The future of food and agriculture–trends and challenges. Food and Agriculture Organization of the United Nations. http://www.fao.org/3/a-i6583e.pdf. Accessed 22 February 2017.

  27. Farooq, M. S., Riaz, S., Abid, A., Abid, K., & Naeem, M. A. (2019). A survey on the role of IoT in agriculture for the implementation of smart farming. IEEE Access, 7, 156237–156271. https://doi.org/10.1109/access.2019.2949703.

    Article  Google Scholar 

  28. Fernández-Garcia, R., & Gil, I. (2017). An alternative wearable tracking system based on a low-power wide-area network. Sensors, 17(3), 592. https://doi.org/10.3390/s17030592.

    Article  Google Scholar 

  29. Foughali, K., Fathallah, K., & Frihida, A. (2018). Using cloud IOT for disease prevention in precision agriculture. Procedia Computer Science, 130, 575–582. https://doi.org/10.1016/j.procs.2018.04.106.

    Article  Google Scholar 

  30. Frenzel, L. (2012). The fundamentals of short-range wireless technology. https://www.electronicdesign.com/technologies/communications/article/21798230/the-fundamentals-of-shortrange-wireless-technology. Accessed 11 October 2012.

  31. Gao, D., Sun, Q., Hu, B., & Zhang, S. (2020). A framework for agricultural pest and disease monitoring based on internet-of-things and unmanned aerial vehicles. Sensors, 20(5), 1487. https://doi.org/10.3390/s20051487.

    Article  Google Scholar 

  32. Gavaskar, S., & Sumithra, A. (2017). Design and development of pest monitoring system for implementing precision agriculture using IOT. International Journal of Science Technology & Engineering, 3(9), 46–48.

    Google Scholar 

  33. Geng, X., Zhang, Q., Wei, Q., Zhang, T., Cai, Y., Liang, Y., & Sun, X. (2019). A mobile greenhouse environment monitoring system based on the internet of things. IEEE Access, 7, 135832–135844. https://doi.org/10.1109/access.2019.2941521.

    Article  Google Scholar 

  34. Giri, A., Dutta, S., & Neogy, S. (2016). Enabling agricultural automation to optimize utilization of water, fertilizer and insecticides by implementing Internet of Things (IoT). In: 2016 International Conference on Information Technology (InCITe)-The Next Generation IT Summit on the Theme-Internet of Things: Connect your Worlds, pp. 125–131, Noida, India: IEEE.

  35. Glaroudis, D., Iossifides, A., & Chatzimisios, P. (2020). Survey, comparison and research challenges of IoT application protocols for smart farming. Computer Networks, 168, 107037. https://doi.org/10.1016/j.comnet.2019.107037.

    Article  Google Scholar 

  36. Goap, A., Sharma, D., Shukla, A., & Krishna, C. R. (2018). An IoT based smart irrigation management system using machine learning and open source technologies. Computers and Electronics in Agriculture, 155, 41–49. https://doi.org/10.1016/j.compag.2018.09.040.

    Article  Google Scholar 

  37. Gubbi, J., Buyya, R., Marusic, S., & Palaniswami, M. (2013). Internet of Things (IoT): a vision, architectural elements, and future directions. Future Generation Computer Systems, 29(7), 1645–1660. https://doi.org/10.1016/j.future.2013.01.010.

    Article  Google Scholar 

  38. Guerra, M. (2017). 3 ways the IoT revolutionizes farming. https://www.electronicdesign.com/technologies/analog/article/21805428/3-ways-the-iot-revolutionizes-farming. Accessed 14 August 2017.

  39. 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. https://doi.org/10.1109/tim.2013.2276487.

    Article  Google Scholar 

  40. Hadipour, M., Derakhshandeh, J. F., & Shiran, M. A. (2020). An experimental setup of multi-intelligent control system (MICS) of water management using the Internet of Things (IoT). ISA Transactions, 96, 309–326. https://doi.org/10.1016/j.isatra.2019.06.026.

    Article  Google Scholar 

  41. Halachmi, I., & Guarino, M. (2016). Precision livestock farming: a ‘per animal’ approach using advanced monitoring technologies. Animal, 10(9), 1482–1483. https://doi.org/10.1017/S1751731116001142.

    Article  Google Scholar 

  42. Heble, S., Kumar, A., Prasad, K. V. V. D., Samirana, S., Rajalakshmi, P., & Desai, U. B. (2018). A low power IoT network for smart agriculture. In: 2018 IEEE 4th World Forum on Internet of Things (WF-IoT), pp. 609–614, Singapore: IEEE.

  43. Hong, G. Z., & Hsieh, C. L. (2016). Application of integrated control strategy and bluetooth for irrigating romaine lettuce in greenhouse. IFAC-PapersOnLine, 49(16), 381–386. https://doi.org/10.1016/j.ifacol.2016.10.070.

    Article  Google Scholar 

  44. Huang, A. (2016). Transforming the agricultural industry. https://www.ibm.com/blogs/internet-of-things/agricultural-industry/. Accessed 9 August 2016.

  45. Işık, M. F., Haboğlu, M. R., & Işık, E. (2017). A monitoring and control system integrated with smart phones for the efficient use of underground water resources in agricultural product growing. Hittite Journal of Science and Engineering, 4(2), 99–103. https://doi.org/10.17350/hjse19030000055.

    Article  Google Scholar 

  46. Islam, M. S., & Dey, G. K. (2019). Precision agriculture: renewable energy based smart crop field monitoring and management system using WSN via IoT. In: 2019 International Conference on Sustainable Technologies for Industry 4.0 (STI), pp. 1–6, Dhaka, Bangladesh: IEEE.

  47. Jawad, H. M., Nordin, R., Gharghan, S. K., Jawad, A. M., & Ismail, M. (2017). Energy-efficient wireless sensor networks for precision agriculture: a review. Sensors, 17(8), 1781. https://doi.org/10.3390/s17081781.

    Article  Google Scholar 

  48. Jayaraman, P. P., Yavari, A., Georgakopoulos, D., Morshed, A., & Zaslavsky, A. (2016). Internet of things platform for smart farming: experiences and lessons learnt. Sensors, 16(11), 1884. https://doi.org/10.3390/s16111884.

    Article  Google Scholar 

  49. Jin, X. B., Yu, X. H., Wang, X. Y., Bai, Y. T., Su, T. L., & Kong, J. L. (2020). Deep learning predictor for sustainable precision agriculture based on Internet of Things system. Sustainability, 12(4), 1433. https://doi.org/10.3390/su12041433.

    Article  Google Scholar 

  50. Kalaivani, T., Allirani, A., & Priya, P. (2011). A survey on Zigbee based wireless sensor networks in agriculture. In: 3rd International Conference on Trendz in Information Sciences & Computing (TISC2011), pp. 85–89, Chennai, India: IEEE.

  51. Kang, H., & Chen, C. (2020). Fast implementation of real-time fruit detection in apple orchards using deep learning. Computers and Electronics in Agriculture, 168, 105108. https://doi.org/10.1016/j.compag.2019.105108.

    Article  Google Scholar 

  52. Karim, F., & Karim, F. (2017). Monitoring system using web of things in precision agriculture. Procedia Computer Science, 110, 402–409. https://doi.org/10.1016/j.procs.2017.06.083.

    Article  Google Scholar 

  53. Khatri, N., Sharma, A., Khatri, K. K., & Sharma, G. D. (2018). An IoT-based innovative real-time pH monitoring and control of municipal wastewater for agriculture and gardening. In A. K. Somani, S. Srivastava, A. Mundra, & S. Rawat (Eds.), Proceedings of first international conference on smart system, innovations and computing (pp. 353–362). Singapore: Springer Singapore.

    Google Scholar 

  54. Khattab, A., Habib, S. E., Ismail, H., Zayan, S., Fahmy, Y., & Khairy, M. M. (2019). An IoT-based cognitive monitoring system for early plant disease forecast. Computers and Electronics in Agriculture, 166, 105028. https://doi.org/10.1016/j.compag.2019.105028.

    Article  Google Scholar 

  55. Köksal, Ö., & Tekinerdogan, B. (2019). Architecture design approach for IoT-based farm management information systems. Precision Agriculture, 20(5), 926–958. https://doi.org/10.1007/s11119-018-09624-8.

    Article  Google Scholar 

  56. Kumar, V., Ramasamy, R., & VasimBabu, M. (2017). Implementation of IoT in smart irrigation system using Arduino processor. International Journal of Civil Engineering and Technology, 8(10), 1304–1314.

    Google Scholar 

  57. Lavanya, G., Rani, C., & Ganeshkumar, P. (2018). An automated low cost IoT based Fertilizer Intimation System for smart agriculture. In An automated low cost IoT based fertilizer intimation system for smart agriculture. Sustainable Computing: Informatics and Systems. https://doi.org/10.1016/j.suscom.2019.01.002.

    Google Scholar 

  58. Lee, M., Hwang, J., & Yoe, H. (2013). Agricultural production system based on IoT. In: 2013 IEEE 16th International Conference on Computational Science and Engineering, pp. 833–837, Sydney, Australia: IEEE.

  59. Li, H., Wang, H., Yin, W., Li, Y., Qian, Y., & Hu, F. (2015). Development of a remote monitoring system for henhouse environment based on IoT technology. Future Internet, 7(3), 329–341.

    Article  Google Scholar 

  60. Li, C., Tang, Y., Wang, M., & Zhao, X. (2018). Agricultural machinery information collection and operation based on data platform. In: 2018 IEEE International Conference of Safety Produce Informatization (IICSPI), pp. 472–475, Chongqing, China: IEEE.

  61. Liao, M. S., Chuang, C. L., Lin, T. S., Chen, C. P., Zheng, X. Y., Chen, P. T., Liao, K. C., & Jiang, J. A. (2012). Development of an autonomous early warning system for Bactrocera dorsalis (Hendel) outbreaks in remote fruit orchards. Computers and Electronics in Agriculture, 88, 1–12. https://doi.org/10.1016/j.compag.2012.06.008.

    Article  Google Scholar 

  62. Liao, M. S., Chen, S. F., Chou, C. Y., Chen, H. Y., Yeh, S. H., Chang, Y. C., & Jiang, J. A. (2017). On precisely relating the growth of Phalaenopsis leaves to greenhouse environmental factors by using an IoT-based monitoring system. Computers and Electronics in Agriculture, 136, 125–139. https://doi.org/10.1016/j.compag.2017.03.003.

    Article  Google Scholar 

  63. Lipiński, A. J., Markowski, P., Lipiński, S., & Pyra, P. (2016). Precision of tractor operations with soil cultivation implements using manual and automatic steering modes. Biosystems Engineering, 145, 22–28. https://doi.org/10.1016/j.biosystemseng.2016.02.008.

    Article  Google Scholar 

  64. Maheswari, R., Azath, H., Sharmila, P., & Gnanamalar, S. S. R. (2019). Smart village: Solar based smart agriculture with IoT enabled for climatic change and fertilization of soil. In: 2019 IEEE 5th International Conference on Mechatronics System and Robots (ICMSR), pp. 102–105, Singapore: IEEE.

  65. Marković, D., Koprivica, R., Pešović, U., & Randić, S. (2015). Application of IoT in monitoring and controlling agricultural production. Acta Agriculturae Serbica, 20(40), 145–153.

    Article  Google Scholar 

  66. Martinez, J. (2014). Smart viticulture project in Spain uses sensor devices to harvest healthier, more abundant grapes for coveted Albariño wines. http://www.libelium.com/sensors-mag-smart-viticulture-project-in-spain-uses-sensor-devices-to-harvest-healthier-more-abundant-grapes-for-coveted-albarino-wines/. Accessed 24 February 2014.

  67. Memon, M. H., Kumar, W., Memon, A., Chowdhry, B. S., Aamir, M., & Kumar, P. (2016). Internet of Things (IoT) enabled smart animal farm. In: 2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom), pp. 2067–2072, New Delhi: IEEE.

  68. Meola, A. (2020). Smart farming in 2020: How IoT sensors are creating a more efficient precision agriculture industry. https://www.businessinsider.com/smart-farming-iot-agriculture. Accessed 24 January 2020.

  69. Mohanraj, I., Ashokumar, K., & Naren, J. (2016). Field monitoring and automation using IOT in agriculture domain. Procedia Computer Science, 93, 931–939. https://doi.org/10.1016/j.procs.2016.07.275.

    Article  Google Scholar 

  70. Moon, A., Kim, J., Zhang, J., & Son, S. W. (2018). Evaluating fidelity of lossy compression on spatiotemporal data from an IoT enabled smart farm. Computers and Electronics in Agriculture, 154, 304–313. https://doi.org/10.1016/j.compag.2018.08.045.

    Article  Google Scholar 

  71. Mordor Intelligence. (2019). Internet of things (IoT) market-growth, trends, forecasts (2020–2025). https://www.mordorintelligence.com/industry-reports/internet-of-things-moving-towards-a-smarter-tomorrow-market-industry. Accessed 11 November 2020.

  72. Muangprathub, J., Boonnam, N., Kajornkasirat, S., Lekbangpong, N., Wanichsombat, A., & Nillaor, P. (2019). IoT and agriculture data analysis for smart farm. Computers and Electronics in Agriculture, 156, 467–474. https://doi.org/10.1016/j.compag.2018.12.011.

    Article  Google Scholar 

  73. Muhammad, A., Haider, B., & Ahmad, Z. (2016). IoT enabled analysis of irrigation rosters in the Indus basin irrigation system. Procedia Engineering, 154, 229–235. https://doi.org/10.1016/j.proeng.2016.07.457.

    Article  Google Scholar 

  74. Mukherjee, A., Misra, S., Sukrutha, A., & Raghuwanshi, N. S. (2020). Distributed aerial processing for IoT-based edge UAV swarms in smart farming. Computer Networks, 167, 107038. https://doi.org/10.1016/j.comnet.2019.107038.

    Article  Google Scholar 

  75. Na, A., Isaac, W., Varshney, S., & Khan, E. (2016). An IoT based system for remote monitoring of soil characteristics. In: 2016 International Conference on Information Technology (InCITe)-The Next Generation IT Summit on the Theme-Internet of Things: Connect Your Worlds, pp. 316–320, Noida, India: IEEE.

  76. Nadimi, E. S., Jørgensen, R. N., Blanes-Vidal, V., & Christensen, S. (2012). Monitoring and classifying animal behavior using ZigBee-based mobile ad hoc wireless sensor networks and artificial neural networks. Computers and Electronics in Agriculture, 82, 44–54. https://doi.org/10.1016/j.compag.2011.12.008.

    Article  Google Scholar 

  77. Narendran, S., Pradeep, P., & Ramesh, M. V. (2017). An Internet of Things (IoT) based sustainable water management. In: 2017 IEEE Global Humanitarian Technology Conference (GHTC), pp. 1–6, San Jose, CA: IEEE.

  78. Navulur, S., & Prasad, M. G. (2017). Agricultural management through wireless sensors and internet of things. International Journal of Electrical and Computer Engineering, 7(6), 3492–3499. https://doi.org/10.11591/ijece.v7i6.pp3492-3499.

    Article  Google Scholar 

  79. Nawandar, N. K., & Satpute, V. R. (2019). IoT based low cost and intelligent module for smart irrigation system. Computers and Electronics in Agriculture, 162, 979–990. https://doi.org/10.1016/j.compag.2019.05.027.

    Article  Google Scholar 

  80. Ojha, T., Misra, S., & Raghuwanshi, N. S. (2015). Wireless sensor networks for agriculture: the state-of-the-art in practice and future challenges. Computers and Electronics in Agriculture, 118, 66–84. https://doi.org/10.1016/j.compag.2015.08.011.

    Article  Google Scholar 

  81. Pal, P., Gupta, R., Tiwari, S., & Sharma, A. (2017). IoT based air pollution monitoring system using Arduino. International Research Journal of Engineering and Technology, 4(10), 1137–1140.

    Google Scholar 

  82. Pan, L., Xu, M., Xi, L., & Hao, Y. (2016). Research of livestock farming IoT system based on RESTful web services. In: 2016 5th International Conference on Computer Science and Network Technology (ICCSNT), pp. 113–116, Changchun, China: IEEE.

  83. Paraforos, D. S., Vassiliadis, V., Kortenbruck, D., Stamkopoulos, K., Ziogas, V., Sapounas, A. A., & Griepentrog, H. W. (2016). A farm management information system using future internet technologies. IFAC-PapersOnLine, 49(16), 324–329. https://doi.org/10.1016/j.ifacol.2016.10.060.

    Article  Google Scholar 

  84. Park, S. H., Park, T., Park, H. D., Jung, D. H., & Kim, J. Y. (2019). Development of wireless sensor node and controller complying with communication Interface standard for smart farming. Journal of Biosystems Engineering, 44, 41–45. https://doi.org/10.1007/s42853-019-00001-5.

    Article  Google Scholar 

  85. Patil, K. A., & Kale, N. R. (2016). A model for smart agriculture using IoT. In: 2016 International Conference on Global Trends in Signal Processing, Information Computing and Communication (ICGTSPICC), pp. 543–545, Jalgaon, India: IEEE.

  86. Perera, C., Liu, C. H., Jayawardena, S., & Chen, M. (2014). A survey on internet of things from industrial market perspective. IEEE Access, 2, 1660–1679. https://doi.org/10.1109/access.2015.2389854.

    Article  Google Scholar 

  87. Ravindra, S. (2018). IoT applications in agriculture. https://www.agritechtomorrow.com/article/2018/01/iot-applications-in-agriculture/10457. Accessed 18 January 2018.

  88. Ray, P. P. (2016). A survey of IoT cloud platforms. Future Computing and Informatics Journal, 1(1–2), 35–46. https://doi.org/10.1016/j.fcij.2017.02.001.

    Article  Google Scholar 

  89. Ray, B. (2017). An in-depth look at IoT in agriculture & smart farming solutions. https://www.link-labs.com/blog/iot-agriculture. Accessed 30 November 2017.

  90. Reid, J., Moorehead, S., Foessel, A., & Sanchez, J. (2016). Autonomous driving in agriculture leading to autonomous worksite solutions. SAE technical paper 2016-01-8006. https://www.sae.org/publications/technical-papers/content/2016-01-8006/. Accessed 27 September 2016.

  91. Sadowski, S., & Spachos, P. (2020). Wireless technologies for smart agricultural monitoring using internet of things devices with energy harvesting capabilities. Computers and Electronics in Agriculture, 172, 105338. https://doi.org/10.1016/j.compag.2020.105338.

    Article  Google Scholar 

  92. Saha, A. K., Saha, J., Ray, R., Sircar, S., Dutta, S., Chattopadhyay, S. P., et al. (2018). IOT-based drone for improvement of crop quality in agricultural field. In: 2018 IEEE 8th Annual Computing and Communication Workshop and Conference (CCWC), pp. 612–615, Las Vegas, NV: IEEE.

  93. Saraf, S. B., & Gawali, D. H. (2017). IoT based smart irrigation monitoring and controlling system. In: 2017 2nd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT), pp. 815–819, Bangalore, India: IEEE.

  94. Shi, X., An, X., Zhao, Q., Liu, H., Xia, L., Sun, X., & Guo, Y. (2019). State-of-the-art internet of things in protected agriculture. Sensors, 19(8), 1833. https://doi.org/10.3390/s19081833.

    Article  Google Scholar 

  95. Singh, R. K., Aernouts, M., De Meyer, M., Weyn, M., & Berkvens, R. (2020). Leveraging LoRaWAN technology for precision agriculture in greenhouses. Sensors, 20(7), 1827. https://doi.org/10.3390/s20071827.

    Article  Google Scholar 

  96. Smith, D., Lyle, S., Berry, A., Manning, N., Zaki, M., & Neely, A. (2015). Internet of animal health things (IoAHT) opportunities and challenges. Cambridge: University of Cambridge. https://doi.org/10.13140/RG.2.1.1113.8409.

    Google Scholar 

  97. Suárez, J. I., Arroyo, P., Lozano, J., Herrero, J. L., & Padilla, M. (2018). Bluetooth gas sensing module combined with smartphones for air quality monitoring. Chemosphere, 205, 618–626. https://doi.org/10.1016/j.chemosphere.2018.04.154.

    Article  Google Scholar 

  98. Talavera, J. M., Tobón, L. E., Gómez, J. A., Culman, M. A., Aranda, J. M., Parra, D. T., Quiroz, L. A., Hoyos, A., & Garreta, L. E. (2017). Review of IoT applications in agro-industrial and environmental fields. Computers and Electronics in Agriculture, 142, 283–297. https://doi.org/10.1016/j.compag.2017.09.015.

    Article  Google Scholar 

  99. Tzounis, A., Katsoulas, N., Bartzanas, T., & Kittas, C. (2017). Internet of Things in agriculture, recent advances and future challenges. Biosystems Engineering, 164, 31–48. https://doi.org/10.1016/j.biosystemseng.2017.09.007.

    Article  Google Scholar 

  100. Vaquerizo-Hdez, D., Muñoz, P., & Barrero, D. F. (2017). A low power consumption algorithm for efficient energy consumption in zigbee motes. Sensors, 17(10), 2179. https://doi.org/10.3390/s17102179.

    Article  Google Scholar 

  101. Vasisht, D., Kapetanovic, Z., Won, J., Jin, X., Chandra, R., Sinha, S., et al. (2017). Farmbeats: an IoT platform for data-driven agriculture. In: 14th USENIX Symposium on Networked Systems Design and Implementation, pp. 515–529, Boston, MA: USENIX.

  102. Veloo, K., Kojima, H., Takata, S., Nakamura, M., & Nakajo, H. (2019). Interactive cultivation system for the future IoT-based agriculture. In: 2019 Seventh International Symposium on Computing and Networking Workshops (CANDARW), pp. 298–304, Nagasaki, Japan: IEEE.

  103. Verdouw, C., Sundmaeker, H., Tekinerdogan, B., Conzon, D., & Montanaro, T. (2019). Architecture framework of IoT-based food and farm systems: a multiple case study. Computers and Electronics in Agriculture, 165, 104939. https://doi.org/10.1016/j.compag.2019.104939.

    Article  Google Scholar 

  104. Wang, J., Chen, M., Zhou, J., & Li, P. (2019). Data communication mechanism for greenhouse environment monitoring and control: an agent-based IoT system. Information Processing in Agriculture., 7, 444–455. https://doi.org/10.1016/j.inpa.2019.11.002.

    Article  Google Scholar 

  105. Wang, E., Attard, S., Linton, A., McGlinchey, M., Xiang, W., Philippa, B., & Everingham, Y. (2020). Development of a closed-loop irrigation system for sugarcane farms using the Internet of Things. Computers and Electronics in Agriculture, 172, 105376. https://doi.org/10.1016/j.compag.2020.105376.

    Article  Google Scholar 

  106. Warpe, T. S., & Pippal, S. R. (2016). A study of fertilizer distribution system for agriculture using wireless sensor network. International Journal of Computer Applications, 147(2), 43–46.

    Article  Google Scholar 

  107. Wolfert, S., Ge, L., Verdouw, C., & Bogaardt, M. J. (2017). Big data in smart farming–a review. Agricultural Systems, 153, 69–80. https://doi.org/10.1016/j.agsy.2017.01.023.

    Article  Google Scholar 

  108. Xiaojun, C., Xianpeng, L., & Peng, X. (2015). IOT-based air pollution monitoring and forecasting system. In: 2015 International Conference on Computer and Computational Sciences (ICCCS), pp. 257–260, Noida, India: IEEE.

  109. Xu, G., Shen, W., & Wang, X. (2014). Applications of wireless sensor networks in marine environment monitoring: a survey. Sensors, 14(9), 16932–16954. https://doi.org/10.3390/s140916932.

    Article  Google Scholar 

  110. Yan-e, D. (2011). Design of intelligent agriculture management information system based on IoT. In: 2011 Fourth International Conference on Intelligent Computation Technology and Automation, pp. 1045–1049, Guangdong, China: IEEE.

  111. Ye, J., Chen, B., Liu, Q., & Fang, Y. (2013). A precision agriculture management system based on Internet of Things and WebGIS. In: 2013 21st International Conference on Geoinformatics, pp. 1–5, Kaifend, China: IEEE.

  112. Zeinab, K. A. M., & Elmustafa, S. A. A. (2017). Internet of Things applications, challenges and related future technologies. World Scientific News, 2(67), 126–148.

    Google Scholar 

  113. Zhang, R., Hao, F., & Sun, X. (2017). The design of agricultural machinery service management system based on Internet of Things. Procedia Computer Science, 107(1), 53–57. https://doi.org/10.1016/j.procs.2017.03.055.

    Article  Google Scholar 

  114. Zhang, S., Wang, Y., Zhu, Z., Li, Z., Du, Y., & Mao, E. (2018). Tractor path tracking control based on binocular vision. Information Processing in Agriculture, 5(4), 422–432. https://doi.org/10.1016/j.inpa.2018.07.003.

    Article  Google Scholar 

  115. Zhao, Y., Liu, L., Xie, C., Wang, R., Wang, F., Bu, Y., & Zhang, S. (2020). An effective automatic system deployed in agricultural Internet of Things using multi-context fusion network towards crop disease recognition in the wild. Applied Soft Computing, 89, 106128. https://doi.org/10.1016/j.asoc.2020.106128.

    Article  Google Scholar 

  116. Zhou, L., Song, L., Xie, C., & Zhang, J. (2012). Applications of Internet of Things in the facility agriculture. In D. Li & Y. Chen (Eds.), Computer and computing Technologies in Agriculture VI (pp. 297–303). Heidelberg: Springer Berlin Heidelberg.

    Google Scholar 

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Funding

This work was supported by the Korea Institute of Planning and Evaluation for Technology in Food, Agriculture, Forestry (IPET) through Agriculture, Food and Rural Affairs Research Center Support Program, funded by Ministry of Agriculture, Food and Rural Affairs (MAFRA) (714002-07). It was also supported by the Korea Institute of Planning and Evaluation for Technology in Food, Agriculture, Forestry (IPET) through Advanced Production Technology Development Program, funded by Ministry of Agriculture, Food and Rural Affairs (MAFRA) (318072-03).

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Correspondence to Won-Suk Lee.

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Kim, WS., Lee, WS. & Kim, YJ. A Review of the Applications of the Internet of Things (IoT) for Agricultural Automation. J. Biosyst. Eng. 45, 385–400 (2020). https://doi.org/10.1007/s42853-020-00078-3

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Keywords

  • Agricultural automation
  • Internet of thing
  • IoT applications
  • Wireless sensor network