Integrated Environment Analysis System for Plant Growth Monitoring using IoT

Modern agriculture is enhanced by the aid of automation technologies through the use of IoT devices, having the capability to grow crops in real-time irrespective of the location. This paper proposes the construction and analysis of an integrated Environmental Analysis System (EAS) model based on the Internet of Things (IoT) that is a low-cost and efficient solution for modern environmental monitoring. The IoT subsystem comprises of temperature and humidity sensors, soil moisture and light intensity sensors, air quality sensors, and a Raspberry Pi 4. With this system, the gathered data will be sent to the cloud-based IoT server for data analysis and remote supervision so as to increase the level of automation and control. The experiments done prove that the proposed model exceeded in sensor coverage, real-time processing, automation, and data insight compared to the existing methods. The system includes a novel method for automated soil moisture monitoring with features for accurate real-time processing, where resource waste through irrigation is substantially reduced. Additionally, automated regulation of the environmental factors significantly improves the overall health and growth of the plants. Incorporating these new findings makes it easier to conclude that the system is efficient and sustainable in meeting the demands and constraints faced in modern agriculture, greenhouses, and vertical farms.