SMART PLANT MONITOR (SOIL MOISTURE, LIGHT AND TEMPERATURE)

Abstract

The rapid development of Internet of Things (IoT) technologies has transformed conventional agricultural practices by enabling continuous environmental monitoring, automated data collection, and intelligent decision-making. Plant growth and productivity are strongly influenced by critical environmental parameters such as soil moisture, light intensity, and ambient temperature. Traditional plant monitoring methods largely depend on manual observation and periodic inspection, which may result in delayed identification of unfavorable growing conditions, inefficient water utilization, and reduced plant health. This research presents a Smart Plant Monitor designed to continuously measure soil moisture, light intensity, and temperature using interconnected sensors and a microcontroller-based monitoring platform. The proposed system integrates a soil moisture sensor for evaluating water availability in the root zone, a light sensor for monitoring illumination conditions, and a temperature sensor for detecting environmental temperature variations. Sensor measurements are periodically acquired, processed, compared with predefined threshold values, and presented through a real-time monitoring interface. The proposed architecture supports automated alerts when soil becomes excessively dry, when light intensity falls outside the desired range, or when temperature conditions become unsuitable for healthy plant growth. An IoT-enabled communication layer further facilitates remote access to sensor information through cloud dashboards, web interfaces, or mobile applications. The system reduces dependence on manual inspection and supports timely irrigation and environmental management decisions. Experimental evaluation is conducted using sensor response accuracy, monitoring reliability, alert response time, and resource efficiency. The observed results demonstrate that the integrated smart monitoring approach provides improved responsiveness and continuous awareness compared with conventional manual plantcare methods. The proposed framework is low-cost, scalable, energy-efficient, and suitable for home gardens, nurseries, greenhouses, indoor plants, and precision agriculture applications. By integrating realtime sensing, IoT communication, threshold-based decision logic, and intelligent alerts, the Smart Plant Monitor contributes toward sustainable water management, healthier plant growth, and data-driven agriculture.