Published December 4, 2025 | Version v1

Sowing the Seeds of Precision: Innovations in Wireless Sensor Networks for Agricultural Environmental Monitoring

Description

Wireless Sensor Networks (WSNs) are used in precision agriculture to provide real-time environmental parameter monitoring that is essential to crop productivity. This study looks at the most current advancements in WSN technology and its application in monitoring vital factors including temperature, humidity, soil moisture, and light intensity in agricultural contexts, with an emphasis on the agricultural region of Bardhaman District, West Bengal, India. For sustainable and long-term sensor network functioning in this area, the study looks into several sensor placement procedures, creative data aggregation strategies, and energy-efficient protocols. To improve data accuracy and decision-making abilities, contemporary analytics techniques like machine learning and data fusion are also used. The results highlight how well WSNs work in Bardhaman District to maximise agricultural sustainability and productivity. The study discusses issues with WSN deployment, like network connectivity and power management, and suggests solutions specific to the region's agricultural environment. The goal of future study is to improve the precision agricultural utility of WSNs even more, with an emphasis on boosting resilience and productivity in farming operations in Bardhaman District.

Files

14324ijans01.pdf

Files (658.7 kB)

Name Size Download all
md5:b68abc6f9a5cdf6afd7f09998196fcb6
658.7 kB Preview Download

Additional details

Related works

Dates

Copyrighted
2024

References

  • [1] Dey, Chanchal & Mistri, Tapas. (2020). Changing Trends of Market Prices of Rice in Burdwan and Memari Markets of Purba Bardhaman District, West Bengal, India. [2] Jawad, Haider Mahmood, Rosdiadee Nordin, Sadik Kamel Gharghan, Aqeel Mahmood Jawad, and Mahamod Ismail. 2017. "Energy-Efficient Wireless Sensor Networks for Precision Agriculture: A Review" Sensors 17, no. 8: 1781. https://doi.org/10.3390/s17081781 [3] Soussi A, Zero E, Sacile R, Trinchero D, Fossa M. Smart Sensors and Smart Data for Precision Agriculture: A Review. Sensors (Basel). 2024 Apr 21;24(8):2647. doi: 10.3390/s24082647. PMID: 38676264; PMCID: PMC11053448. [4] Alahmad, Tarek, Miklós Neményi, and Anikó Nyéki. 2023. "Applying IoT Sensors and Big Data to Improve Precision Crop Production: A Review" Agronomy 13, no. 10: 2603. https://doi.org/10.3390/agronomy13102603 [5] García L, Parra L, Jimenez JM, Parra M, Lloret J, Mauri PV, Lorenz P. Deployment Strategies of Soil Monitoring WSN for Precision Agriculture Irrigation Scheduling in Rural Areas. Sensors (Basel). 2021 Mar 1;21(5):1693. doi: 10.3390/s21051693. PMID: 33804524; PMCID: PMC7957636. [6] Ravesa Akhter, Shabir Ahmad Sofi, Precision agriculture using IoT data analytics and machine learning, Journal of King Saud University - Computer and Information Sciences, Volume 34, Issue 8, Part B, 2022, Pages 5602-5618, ISSN 1319-1578, https://doi.org/10.1016/j.jksuci.2021.05.013. (https://www.sciencedirect.com/science/article/pii/S1319157821001282) [7] Blaszczyszyn, B. & Radunovic, B.. (2008). Using Transmit-Only Sensors to Reduce Deployment Cost of Wireless Sensor Networks. 1202 - 1210. 10.1109/INFOCOM.2008.176. [8] Liu Z, Zhang J, Liu Y, Feng F, Liu Y. Data aggregation algorithm for wireless sensor networks with different initial energy of nodes. PeerJ Comput Sci. 2024 Mar 15;10:e1932. doi: 10.7717/peerjcs.1932. PMID: 38660199; PMCID: PMC11041949.