Research Paper — Smart Agriculture IoT

CO-AUTHORS

PUBLICATION

KEY CONTRIBUTIONS

2025

YEAR PUBLISHED

PAPER_ABSTRACT

This research presents an IoT-based smart agriculture monitoring system using ESP32 and various sensors to monitor environmental conditions such as soil moisture, temperature, and humidity in real-time. The system integrates a web-based dashboard for remote monitoring and enables automated irrigation control based on sensor data.

The proposed solution improves resource utilization, reduces manual effort, and enhances agricultural productivity through data-driven decision-making. The system collects real-time data from sensors connected to ESP32 and transmits it to a web server using HTTP protocols. Data is stored in a MySQL database and displayed on a web dashboard. Based on predefined thresholds, the system automatically activates irrigation and cooling mechanisms — demonstrating a fully integrated hardware-software IoT solution for modern precision agriculture.

HOW_IT_WAS_BUILT

research-build-log ~ smart_agriculture_v1.0 · ICAMC 2025 ● LIVE LOG

KEY_CONTRIBUTIONS

🌱
REAL-TIME IOT MONITORING Designed and implemented a complete IoT pipeline using ESP32 microcontroller with DHT11 and soil moisture sensors — collecting environmental data (temperature, humidity, soil moisture) every 5 seconds with no manual intervention.
💧
AUTOMATED IRRIGATION SYSTEM Implemented threshold-based automated irrigation control using a relay-controlled water pump — activates automatically when soil moisture drops below the configured threshold, eliminating water waste.
🌐
WEB-BASED REMOTE DASHBOARD Developed a PHP + MySQL web dashboard with real-time data visualization, live charts, historical data tables, and alert mechanisms — enabling farmers to monitor their fields remotely from any browser-enabled device.
📊
DATA VISUALIZATION & DECISION SUPPORT Built a full data analytics layer with historical trend charts and pattern analysis — supporting data-driven agricultural decision-making and seasonal planning based on recorded environmental data.
⚡
REDUCED WATER USAGE & IMPROVED EFFICIENCY Demonstrated measurable improvements in resource utilization — by irrigating only when soil moisture data indicates necessity, the system significantly reduces water consumption and manual monitoring effort.

CONFERENCE_DETAILS

ICAMC 2025

3rd International Conference on Artificial Intelligence, Machine Learning and Cybersecurity

VENUEHMR Institute of Technology & Management, New Delhi

PUBLISHERAIJR Proceedings

YEAR2025

DOI10.21467/proceedings.7.6.23

TOPICSAI · Machine Learning · Cybersecurity · IoT

🏛️

INSTITUTION

HMR Institute, Delhi

📖

PUBLISHED IN

AIJR Proceedings

🔗

PAPER ID

Article #72

✅

STATUS

Presented & Published

PRESENTATION_CERTIFICATE

🏆

ICAMC 2025 — OFFICIAL CONFERENCE CERTIFICATE

✓ SUCCESSFULLY PRESENTED

Successfully presented the research paper "Sensor Based Smart Agriculture Monitoring System Using Web & IoT" at the 3rd International Conference on AI, Machine Learning & Cybersecurity (ICAMC 2025) held at HMR Institute of Technology & Management, New Delhi.

📄 VIEW CERTIFICATE PDF →

RESEARCH_METHODOLOGY

PHASE 01 → PROBLEM IDENTIFICATION

Identified the core challenges in traditional agriculture — manual monitoring inefficiency, water waste, and lack of real-time crop field data — establishing the motivation for an IoT-based solution.

PHASE 02 → SYSTEM DESIGN

Designed the complete system architecture — selecting ESP32 as the central controller, DHT11 and soil moisture sensors for data collection, and PHP/MySQL for the web layer. Circuit and data flow diagrams created.

PHASE 03 → HARDWARE IMPLEMENTATION

Built the physical IoT system — wiring all sensors to ESP32, setting up the relay-controlled irrigation pump, and integrating I2C display and buzzer for local alerts. Firmware written in C++ (Arduino IDE).

PHASE 04 → SOFTWARE DEVELOPMENT

Developed the PHP web server with MySQL backend on XAMPP — building the data ingestion API, storage layer, and the real-time dashboard with charts, tables, and alert notifications.

PHASE 05 → TESTING & VALIDATION

Conducted real-world testing of the complete integrated system — verifying sensor accuracy, HTTP data transmission, database storage, dashboard visualization, and automated irrigation trigger logic.

PHASE 06 → PAPER WRITING & PUBLICATION

Documented research findings, system architecture, results, and impact analysis. Paper submitted to and accepted by ICAMC 2025 — presented at HMR Institute, New Delhi, and published in AIJR Proceedings with official DOI assignment.

TECHNOLOGIES_USED

// HARDWARE

ESP32 Microcontroller

DHT11 Temperature & Humidity

Soil Moisture Sensor

Water Pump + Relay

I2C Display

Buzzer

// EMBEDDED FIRMWARE

C++ (Arduino IDE)

ESP32 WiFi Library

HTTPClient Library

// WEB & DATABASE

PHP

HTML5 / CSS3 / JavaScript

MySQL

XAMPP Server

RESEARCH_IMPACT

🌾

IMPROVED FARMING EFFICIENCYAutomated monitoring and irrigation eliminates guesswork — farmers get accurate, data-driven insights for better crop management and yield improvement.

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REDUCED MANUAL MONITORINGRemote web dashboard enables farmers to monitor field conditions 24/7 from any device — drastically reducing the need for physical field visits.

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OPTIMIZED WATER USAGEThreshold-based automated irrigation ensures water is used only when needed — addressing one of the biggest challenges in sustainable agriculture.

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SUPPORTS PRECISION AGRICULTUREHistorical data storage and visualization supports precision agriculture approaches — enabling pattern-based decision making for seasonal planning.