AI Based Solar Powered Plant Health Monitoring
Plant & Crop Monitoring,Crop Health Assessment,Disease Detection,Leaf Image Analysis,Stress Detection in Plants,Growth Monitoring
The proposed project presents an AI-based solar-powered plant health monitoring system that leverages the Internet of
Things (IoT) and machine learning (ML) for real-time, intelligent agricultural support. The system utilizes an ESP32-CAM module
to capture periodic images of plants, enabling visual monitoring. An ESP8266 microcontroller is integrated with various
environmental sensors including a soil moisture sensor, DHT11 temperature and humidity sensor, and a light intensity sensor to
gather essential data about the plant's growing conditions. A solar panel powers the entire setup, ensuring sustainability and enabling
deployment in remote, off-grid agricultural areas. The collected sensor data, along with processed images, is transmitted via Wi-Fi
to a cloud server or web dashboard for remote access and analysis. A trained machine learning model processes the images to detect
early signs of plant stress or disease, offering timely alerts to farmers or researchers. This intelligent system promotes efficient
water usage, improved crop yield, and early disease intervention, reducing dependency on manual inspection. By integrating
renewable energy, wireless communication, this solution provides an eco-friendly, cost-effective, and scalable approach to modern
precision farming.
"AI Based Solar Powered Plant Health Monitoring ", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.11, Issue 1, page no.b549-b553, January-2026, Available :https://ijsdr.org/papers/IJSDR2512167.pdf
Volume 11
Issue 1,
January-2026
Pages : b549-b553
Paper Reg. ID: IJSDR_306628
Published Paper Id: IJSDR2512167
Downloads: 000323
Research Area: Science and Technology
Country: Chikkaballapur , Karnataka , India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
