Integrating IoT Sensors and Smart Automation into Traditional Sustainable Agriculture Practices
Keywords:
Indian knowledge system, Internet of things, LoRa, Natural farming, Precision irrigation, Smart agriculture, Sustainable Farming, Wireless sensor networksAbstract
Indian farming draws on generations of experience in maintaining soil, conserving water, choosing crop combinations, and managing pests through ecological methods. Much of this knowledge is shared within farming communities and applied through observation and judgement rather than continuous measurement. Low-cost Internet of Things (IoT) devices now make it possible to collect field data, send it over low-power networks, process it locally, and operate selected equipment automatically. This paper examines ways these capabilities can support traditional sustainable agriculture. It discusses practices including Zero Budget Natural Farming (ZBNF), mulching, mixed cropping, and rainwater harvesting, along with relevant sensors, communication options, analytics, and actuators. The proposed approach keeps farmers and their agronomic knowledge at the centre: IoT supplies measurements and timely feedback, while decisions remain open to farmer review. The paper also considers barriers such as equipment cost, calibration, maintenance, rural connectivity, energy supply, interoperability, digital literacy, and data ownership. Published quantitative evidence for IoT-assisted traditional farming remains limited, so potential benefits need to be tested through field studies rather than assumed.
References
A. Walter, R. Finger, R. Huber, and N. Buchmann, “Opinion: Smart Farming Is Key to Developing Sustainable Agriculture,” Proceedings of the National Academy of Sciences, vol. 114, no. 24, pp. 6148–6150, Jun. 2017.
A. and N. S., “Dying wisdom: rise, fall and potential of India’s traditional water harvesting systems.” Center for Science and Environment, Jan. 1997.
A. Khadse, P. M. Rosset, H. Morales, and B. G. Ferguson, “Taking Agroecology to Scale: The Zero Budget Natural Farming Peasant Movement in Karnataka, India,” The Journal of Peasant Studies, vol. 45, no. 1, pp. 192–219, Feb. 2017.
S. Wolfert, L. Ge, C. Verdouw, and M.-J. Bogaardt, “Big Data in Smart Farming – A Review,” Agricultural Systems, vol. 153, no. 1, pp. 69–80, May 2017.
O. Elijah, T. A. Rahman, I. Orikumhi, C. Y. Leow, and M. H. D. N. Hindia, “An Overview of Internet of Things (IoT) and Data Analytics in Agriculture: Benefits and Challenges,” IEEE Internet of Things Journal, vol. 5, no. 5, pp. 3758–3773, Oct. 2018.
M. Ayaz, M. Ammad-uddin, Z. Sharif, A. Mansour, and H. M. Aggoune, “Internet-of-Things (IoT) Based Smart Agriculture: Towards Making the Fields Talk,” IEEE Access, vol. 7, no. 1, pp. 1–1, 2019.
M. S. Farooq, S. Riaz, A. Abid, K. Abid, and M. A. Naeem, “A Survey on the Role of IoT in Agriculture for the Implementation of Smart Farming,” IEEE Access, vol. 7, no. 2169–3536, pp. 156237–156271, 2019.
A. Khanna and S. Kaur, “Evolution of Internet of Things (IoT) and Its Significant Impact in the Field of Precision Agriculture,” Computers and Electronics in Agriculture, vol. 157,
pp. 218–231, Feb. 2019.
A. Augustin, J. Yi, T. Clausen, and W. Townsley, “A Study of LoRa: Long Range & Low Power Networks for the Internet of Things,” Sensors, vol. 16, no. 9, p. 1466, Sep. 2016.
T. Ayoub Shaikh, T. Rasool, and F. Rasheed Lone, “Towards Leveraging the Role of Machine Learning and Artificial Intelligence in Precision Agriculture and Smart Farming,” Computers and Electronics in Agriculture, vol. 198, p. 107119, Jul. 2022.
S. P. Mohanty, D. P. Hughes, and M. Salathé, “Using Deep Learning for Image-Based Plant Disease Detection,” Frontiers in Plant Science, vol. 7, Sep. 2016.
A. Kamilaris and F. X. Prenafeta-Boldú, “Deep Learning in Agriculture: A Survey,” Computers and Electronics in Agriculture, vol. 147, pp. 70–90, Apr. 2018.
J. Muangprathub, N. Boonnam, S. Kajornkasirat, N. Lekbangpong, A. Wanichsombat, and P. Nillaor, “IoT and Agriculture Data Analysis for Smart Farm,” Computers and Electronics in Agriculture, vol. 156, pp. 467–474, Jan. 2019.
A. Villa-Henriksen, L. A. Pesonen, G. Ole, and S. C. A. Grøn, “Internet of Things in Arable Farming: Implementation, Applications, Challenges and Potential,” Biosystems Engineering, vol. 191, pp. 60–84, Mar. 2020.
FAO, “The State of Food and Agriculture 2022: Leveraging Automation to Transform Agrifood Systems,” FAO, 2022.
