Authors :
Dr. Chetan Marol; Supriya Khanapur; Jyoti Rathod; Salauddin Mulla; Rakshita Bajantri
Volume/Issue :
Volume 10 - 2025, Issue 1 - January
Google Scholar :
https://tinyurl.com/yt4hm85d
Scribd :
https://tinyurl.com/bdfh4ezx
DOI :
https://doi.org/10.5281/zenodo.14831456
Abstract :
New ideas to lessen human labour in agriculture have been made possible by technological advancements,
especially in the areas of IoT, AI, and machine learning. Inefficient irrigation techniques are frequently the result of
farming in areas with unpredictable rainfall and high temperatures, which presents difficulties for the sustained
production of crops. Using IoT-based sensors, including soil moisture sensors, DHT11 sensors, and a NodeMCU
microcontroller, this study aims to develop an autonomous and reasonably priced irrigation system. The system uses a
fuzzy logic model to optimise water use based on weather forecasts, temperature, humidity, and soil moisture data.
Incorporating solar energy also minimises carbon footprints, guarantees sustainability, and lessens reliance on traditional
energy sources. The suggested system tackles the twin goals of effective water management and ecological.
Keywords :
ESP8226, Humidity Sensor, DHT11 Sensor, Moisture Sensor.
References :
- https://www.worldbank.org/en/topic/water in agriculture.
- Akhrs, G, “Smart Materials and Smart systems for the Future", Canadian Military Journal, 08/2000.
- Gubbi, J., Buyya, R., Marusic, S., Palaniswami, M., 2013. Internet of things (IoT): a vision, architectural elements, and future directions. Futur. Gener. Comput. Syst. 29,1645–1660
- Janani M and Jebakumar R. A Study on Smart Irrigation Using Machine Learning. Cell Cellular Lif Sci J 2019, 4(2): 000141.
- LiakosKG,BusatoP,MoshouD,PearsonS,BochtisD(2 018)Machine Learning in Agriculture: A Review. Sensors (Basel) 18(8): 2674
- Viani F, Bertolli MG, Salucci M, Polo A (2017)Low-Cost Wireless Monitoring and Decision Support for Water Saving in Agriculture. IEEE Sensors Journal. .
- Radadiya BL, T hakkar RG, T humar VM, Chaudhari BD (2016) Cloud computing and agriculture, International Journal of Agriculture Sciences 8(22): 1429-1431
- Gupta A, Krishna V, Gupta S, Aggarwal J (2016) Android based Solar Powered Automatic Irrigation System. Indian Journal of Science and Technology
- Gupta, A.; Krishna, V.; Gupta, S.; Aggarwal, J. Android based solar powered automatic irrigation system. Indian J. Sci. Technol. 2016,9. 1– 5.
New ideas to lessen human labour in agriculture have been made possible by technological advancements,
especially in the areas of IoT, AI, and machine learning. Inefficient irrigation techniques are frequently the result of
farming in areas with unpredictable rainfall and high temperatures, which presents difficulties for the sustained
production of crops. Using IoT-based sensors, including soil moisture sensors, DHT11 sensors, and a NodeMCU
microcontroller, this study aims to develop an autonomous and reasonably priced irrigation system. The system uses a
fuzzy logic model to optimise water use based on weather forecasts, temperature, humidity, and soil moisture data.
Incorporating solar energy also minimises carbon footprints, guarantees sustainability, and lessens reliance on traditional
energy sources. The suggested system tackles the twin goals of effective water management and ecological.
Keywords :
ESP8226, Humidity Sensor, DHT11 Sensor, Moisture Sensor.
