Smart Agriculture Monitoring System Using IoT

This paper presents an Internet of Things (IoT)-based smart agriculture monitoring prototype built around an ESP32 microcontroller. The system integrates soil-moisture sensing, ambient temperature and relative-humidity measurement, and irrigation-water monitoring through total dissolved solids (TDS) and turbidity sensors. A relay interface controls a water pump, and an OLED provides local status information. Selected values and pump state are shared through Firebase Realtime Database for a web dashboard, while a Telegram bot supports status requests and remote mode and pump commands. The supplied firmware implements threshold-based automatic control with soil-moisture hysteresis and multi-sample confirmation. This manuscript documents the implemented architecture and interface evidence. It does not claim calibrated sensor accuracy, water savings, crop-yield improvement, or field-scale reliability; these require controlled validation

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Publication Details

Journal
International Journal for Research in Applied Science and Engineering Technology
Published
2026-11-11
DOI
https://doi.org/10.22214/ijraset.2026.85614
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
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article

Smart Agriculture Monitoring System Using IoT

Varun Kumar, Vinayak C Yalaburgi, Dr. Banumathi K. L., Honnushree R et al.
International Journal for Research in Applied Science and Engineering Technology
Smart Agriculture and AI
article

Smart Agriculture Monitoring System Using IoT

Varun Kumar, Vinayak C Yalaburgi, Dr. Banumathi K. L., Honnushree R, Shahid S Khan
article en

Abstract

This paper presents an Internet of Things (IoT)-based smart agriculture monitoring prototype built around an ESP32 microcontroller. The system integrates soil-moisture sensing, ambient temperature and relative-humidity measurement, and irrigation-water monitoring through total dissolved solids (TDS) and turbidity sensors. A relay interface controls a water pump, and an OLED provides local status information. Selected values and pump state are shared through Firebase Realtime Database for a web dashboard, while a Telegram bot supports status requests and remote mode and pump commands. The supplied firmware implements threshold-based automatic control with soil-moisture hysteresis and multi-sample confirmation. This manuscript documents the implemented architecture and interface evidence. It does not claim calibrated sensor accuracy, water savings, crop-yield improvement, or field-scale reliability; these require controlled validation

International Journal for Research in Applied Science and Engineering TechnologyVol. 14(11)
Bapuji Institute of Engineering and Technology (IN)
Smart Agriculture and AI
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