An IoT-Based Smart Plant Monitoring and Irrigation System with Real-Time Environmental Sensing, Automated Alerts, and Cloud Analytics
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arXiv
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| Format: | Preprint |
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2026
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| author | Hasib, Abdul Akib, A. S. M. Ahsanul Sarkar |
| author_facet | Hasib, Abdul Akib, A. S. M. Ahsanul Sarkar |
| contents | The increasing global demand for sustainable agriculture necessitates intelligent monitoring systems that optimize resource utilization and plant health management. Traditional farming methods rely on manual observation and periodic watering, often leading to water wastage, inconsistent plant growth, and delayed response to environmental changes. This paper presents a comprehensive IoT-based smart plant monitoring system that integrates multiple environmental sensors with automated irrigation and cloud analytics. The proposed system utilizes an ESP32 microcontroller to collect real-time data from DHT22 (temperature/humidity), HC-SR04 (water level), and soil moisture sensors, with visual feedback through an OLED display and auditory alerts via a buzzer. All sensor data is wirelessly transmitted to the ThingSpeak cloud platform for remote monitoring, historical analysis, and automated alert generation. Experimental results demonstrate the system's effectiveness in maintaining optimal soil moisture levels (with 92\% accuracy), providing real-time environmental monitoring, and reducing water consumption by approximately 40\% compared to conventional irrigation methods. The integrated web dashboard offers comprehensive visualization of plant health parameters, making it suitable for both small-scale gardening and commercial agriculture applications. With a total implementation cost of \$45.20, this system provides an affordable, scalable solution for precision agriculture and smart farming. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_15830 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | An IoT-Based Smart Plant Monitoring and Irrigation System with Real-Time Environmental Sensing, Automated Alerts, and Cloud Analytics Hasib, Abdul Akib, A. S. M. Ahsanul Sarkar Computer Vision and Pattern Recognition The increasing global demand for sustainable agriculture necessitates intelligent monitoring systems that optimize resource utilization and plant health management. Traditional farming methods rely on manual observation and periodic watering, often leading to water wastage, inconsistent plant growth, and delayed response to environmental changes. This paper presents a comprehensive IoT-based smart plant monitoring system that integrates multiple environmental sensors with automated irrigation and cloud analytics. The proposed system utilizes an ESP32 microcontroller to collect real-time data from DHT22 (temperature/humidity), HC-SR04 (water level), and soil moisture sensors, with visual feedback through an OLED display and auditory alerts via a buzzer. All sensor data is wirelessly transmitted to the ThingSpeak cloud platform for remote monitoring, historical analysis, and automated alert generation. Experimental results demonstrate the system's effectiveness in maintaining optimal soil moisture levels (with 92\% accuracy), providing real-time environmental monitoring, and reducing water consumption by approximately 40\% compared to conventional irrigation methods. The integrated web dashboard offers comprehensive visualization of plant health parameters, making it suitable for both small-scale gardening and commercial agriculture applications. With a total implementation cost of \$45.20, this system provides an affordable, scalable solution for precision agriculture and smart farming. |
| title | An IoT-Based Smart Plant Monitoring and Irrigation System with Real-Time Environmental Sensing, Automated Alerts, and Cloud Analytics |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2601.15830 |