Authors : D. Z. Zakut; O. B. Goodtalk; A. N. Lawal; S. A. Yusuf; I. Isa

Volume/Issue : Volume 11 - 2026, Issue 8 - August

---

Google Scholar : https://tinyurl.com/43psm5b7

DOI : https://doi.org/10.38124/ijisrt/26aug1576

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

---

Abstract : Precision agriculture provides an effective approach for improving agricultural productivity through spatially and temporally informed monitoring of soil, environmental, and crop conditions. However, many precision agriculture technologies remain relatively expensive and technically complex for small- and medium-scale farmers, particularly in developing countries. This paper presents a low-cost GNSS-based precision agricultural monitoring system integrating an ESP32, agricultural sensors, IoT communication, and real-time web visualization. The system acquires soil moisture, temperature, relative humidity, and GNSS data and transmits location-tagged measurements to a web server for remote monitoring.

Keywords : Precision Agriculture, GNSS, GPS, Internet of Things, ESP32, Smart Farming, Soil Monitoring, Real-Time Visualization, Low-Cost Agricultural Monitoring.

References :

1. A. Soussi, E. Zero, R. Sacile, D. Trinchero, and M. Fossa, “Smart sensors and smart data for precision agriculture: A review,” Sensors, vol. 24, no. 8, Art. no. 2647, 2024, doi: 10.3390/s24082647.
2. S. Dhanasekar, “A comprehensive review on current issues and advancements of Internet of Things in precision agriculture,” Computer Science Review, 2024, Art. no. 100694, doi: 10.1016/j.cosrev.2024.100694.
3. M. K. K. et al., “Global Navigation Satellite Systems as state-of-the-art solutions in precision agriculture: A review of studies indexed in the Web of Science,” Agriculture, vol. 13, no. 7, Art. no. 1417, 2023, doi: 10.3390/agriculture13071417.
4. N. V. Nguyen and W. Cho, “Performance evaluation of a typical low-cost multi-frequency multi-GNSS device for positioning and navigation in agriculture—Part 2: Dynamic testing,” AgriEngineering, vol. 5, no. 1, pp. 127–140, 2023, doi: 10.3390/agriengineering5010008.
5. N. V. Nguyen and W. Cho, “Performance evaluation of a typical low-cost multi-frequency multi-GNSS device for positioning and navigation in agriculture—Part 1: Static testing,” Smart Agricultural Technology, vol. 1, Art. no. 100004, 2021, doi: 10.1016/j.atech.2021.100004.
6. A. Oliveira-Jr., C. Resende, A. Pereira, P. Madureira, J. Gonçalves, R. Moutinho, and F. Soares, “IoT sensing platform as a driver for digital farming in rural Africa,” Sensors, vol. 20, no. 12, Art. no. 3511, 2020, doi: 10.3390/s20123511.
7. H. Shahab, M. Iqbal, A. Sohaib, F. U. Khan, and M. Waqas, “IoT-based agriculture management techniques for sustainable farming: A comprehensive review,” Computers and Electronics in Agriculture, vol. 220, Art. no. 108851, 2024, doi: 10.1016/j.compag.2024.108851.
8. S. Dhanasekar, “A comprehensive review on current issues and advancements of Internet of Things in precision agriculture,” Computer Science Review, vol. 52, Art. no. 100694, 2024, doi: 10.1016/j.cosrev.2024.100694.
9. S. V. Gaikwad, A. D. Vibhute, K. V. Kale, and S. C. Mehrotra, “An innovative IoT based system for precision farming,” Computers and Electronics in Agriculture, vol. 187, Art. no. 106291, 2021, doi: 10.1016/j.compag.2021.106291.
10. H. Zhang, L. He, F. Di Gioia, D. Choi, A. Elia, and P. Heinemann, “LoRaWAN based internet of things (IoT) system for precision irrigation in plasticulture fresh-market tomato,” Smart Agricultural Technology, vol. 2, Art. no. 100053, 2022, doi: 10.1016/j.atech.2022.100053.
11. G. S. Carvalho, F. O. Silva, and M. V. O. Pacheco, “Performance analysis of relative GPS positioning for low-cost receiver-equipped agricultural rovers,” Sensors, vol. 23, no. 21, Art. no. 8835, 2023, doi: 10.3390/s23218835.
12. E. F. Rivera Guzmán, E. D. Mañay Chochos, M. D. Chiliquinga Malliquinga, P. F. Baldeón Egas, and R. M. Toasa Guachi, “LoRa network-based system for monitoring the agricultural sector in Andean areas: Case study Ecuador,” Sensors, vol. 22, no. 18, Art. no. 6743, 2022, doi: 10.3390/s22186743.
13. N. Bristow, S. Rengaraj, D. R. Chadwick, J. Kettle, and D. L. Jones, “Development of a LoRaWAN IoT node with ion-selective electrode soil nitrate sensors for precision agriculture,” Sensors, vol. 22, no. 23, Art. no. 9100, 2022, doi: 10.3390/s22239100.
14. M. J. K. et al., “Design and implementation of ESP32-based IoT devices,” Sensors, vol. 23, no. 15, Art. no. 6739, 2023, doi: 10.3390/s23156739.
15. N. Wielgocka, T. Hadas, A. Kaczmarek, and G. Marut, “Feasibility of using low-cost dual-frequency GNSS receivers for land surveying,” Sensors, vol. 21, no. 6, Art. no. 1956, 2021, doi: 10.3390/s21061956.
16. D. Janos and P. Kuras, “Evaluation of low-cost GNSS receiver under demanding conditions in RTK network mode,” Sensors, vol. 21, no. 16, Art. no. 5552, 2021, doi: 10.3390/s21165552.
17. E. Reitbauer and C. Schmied, “Bridging GNSS outages with IMU and odometry: A case study for agricultural vehicles,” Sensors, vol. 21, no. 13, Art. no. 4467, 2021, doi: 10.3390/s21134467.
18. V. Hamza, B. Stopar, O. Sterle, and P. Pavlovčič-Prešeren, “Observations and positioning quality of low-cost GNSS receivers: A review,” GPS Solutions, vol. 28, Art. no. 149, 2024, doi: 10.1007/s10291-024-01686-8.