Open Access Open Access  Restricted Access Subscription or Fee Access

IoT based Solution for Soil Management and Crop Suggestion

Rutvik Dalal, Harshvadan Mihir

Abstract


Agriculture is India’s most important and fundamental occupation, as it balances everyone’s nutritional needs while also providing essential raw materials for various businesses. Traditional farming techniques have proven to be quite inefficient to some extent. Innovative farming techniques such as use of IoT (Internet of Things) are gradually ameliorating crop yields, making them more profitable and reducing agricultural waste. The IoT concept aims to create a complex information system by combining sensor data collection, efficient data trans- mission via networking, machine learning, artificial intelligence, big data, and clouds. This paper highlights the work carried out in the field of agriculture and smart sensing with the help of IoT. Various sensors like NPK, pH, temperature and humidity sensors were interfaced together to create a system which can provide real time sensed values to the user. Along with that, a machine learning based crop suggestion module has been designed which is capable of providing a relevant crop suggestion according the given conditions.

Full Text:

PDF

References


World Population Projected to Reach 9.8 Billion in 2050 and 11.2 Billion in 2100. [online] Available at: https://www.un.org/development/desa/en/news/population/world- population- prospects2017.html [Accessed 18 April 2019].

How is the Global Population Distributed Across the World? Accessed: Apr. 13, 2019. [Online]. Available: https://ourworldindata.org/world- population-growth

D. Tripathi, R. Mishra, K. K. Maurya, R. B. Singh, and D.W. Wilson, “Estimates for world population and global food availability for global health,” The Role of Functional Food Security in Global Health. 2019, pp. 3 24.

M. Elder and S. Hayashi, “A regional perspective on biofuels in Asia,” in Biofuels and Sustainability (Science for Sustainable Societies). Springer, 2018.

M. Ayaz, M. Ammad-Uddin, Z. Sharif, A. Mansour and E. -H. M. Aggoune, ”Internet-of-Things (IoT)-Based Smart Agriculture: Toward Making the Fields Talk,” in IEEE Access, vol. 7, pp. 129551-129583, 2019, doi: 10.1109/ACCESS.2019.2932609.

S. R. Prathibha, A. Hongal and M. P. Jyothi, ”IOT Based Monitoring System in Smart Agriculture,” 2017 International Conference on Recent Advances in Electronics and Communication Technology (ICRAECT), 2017, pp. 81-84, doi: 10.1109/ICRAECT.2017.52.

M. K. Saini and R. K. Saini, ”Agriculture monitoring and prediction using Internet of Things (IoT),” 2020 Sixth International Conference on Parallel, Distributed and Grid Computing (PDGC), 2020, pp. 53-56, doi: 10.1109/PDGC50313.2020.9315836.

N. Arvindan and D. Kartheeka, “Experimental investigation of remote control via Android smartphone of Arduino-based automated irrigation system using moisture sensor”, 3rd International Conference on Electrical Energy Systems (ICEES), 17-19 Mar. 2016. 9. M. Dholu and K. A. Ghodinde, Internet of Things (IoT) for Preci- sion Agriculture Application, 2018 2nd International Conference on Trends in Electronics and Informatics (ICOEI), 2018, pp. 339-342, doi: 10.1109/ICOEI.2018.8553720. 10. N. Tilley, “NPK values: What do the numbers on fertilizer mean,” Gardening Know How, 26-Feb- 2011. [Online]. Available: https://www.gardeningknowhow.com/garden-how-to/soil- fertilizers/fertilizer-numbers-npk.htm. [Accessed: 10-Mar-2022]. 11. How2electronics.com. [Online]. Available: https://how2electronics.com/measure-soil-nutrient- using-arduino-soil-npk-sensor/. [Accessed: 10-Mar-2022]. 12. “IOT based smart agriculture monitoring system,” Regular, vol. 9, no. 9, pp. 325–328, 2020. 13. Ingle, ”Crop Recommendation Dataset”, vol. 1, Kaggle, 2020. [Dataset]. Available: https://www.kaggle.com/atharvaingle/crop- recommendation-dataset. [Accessed: 10-Mar-2022].




DOI: https://doi.org/10.37628/jrfd.v7i2.1653

Refbacks

  • There are currently no refbacks.