Abstract

The incorporation of Internet of Things-IoT technology in agriculture has ushered in a transformative era, shifting from qualitative, experience-based practices to quantitative, datadriven methodologies in recent years. This paper delves into the world of IoT in agriculture, with a particular emphasis on Indoor Plant Monitoring Systems. This study investigated the practical implications of an IoT framework designed for indoor plant monitoring, to bridge the gap by focusing on improving data collection and visualization capabilities. A prototype-based approach was used, which included DHT11 sensors for temperature and humidity monitoring, a soilmoisture sensor, and a watering actuation subsystem. Succulent plants were chosen as resilient samples to test the IoT system's ability to capture and respond to critical parameters because of their capacity to endure changes in environmental conditions and flourish in arid environments. The DHT11 sensor results demonstrated the interconnected dynamics of temperature and humidity, providing the important insights into climate control strategies for optimal plant growth. The data from the soil moisture sensors, combined with manual interventions, demonstrated the IPMS's adaptability in maintaining favorable soil conditions. A point-biserial correlation analysis, in particular, revealed a strong negative correlation (−0.89) between moisture levels and water pump status, confirming the system's efficacy in automated watering. The IPMS demonstrated its effectiveness in leveraging real-time data for informed decison-making, paving the way for future enhancements and comprehensive plant health assessments.

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