Automated Smart Garden Monitoring Using Microcontroller and Sensor Devices With Backup Solar Energy

Vol. 5, No. 1

Abstract

This research introduces an Automated Smart Garden Monitoring Technology System (ASGMTS) designed to enhance plant growth and health through technology-driven optimization. The system utilizes sensors, data analytics, and machine learning algorithms to monitor real-time environmental conditions, including temperature, humidity, soil moisture, light levels, and plant growth. The study aims to design and develop a smart garden monitoring system applicable to both indoor and outdoor settings, assessing its performance, usability, and user acceptance. The envisioned outcomes include optimized plant growth, reduced resource consumption, and support for sustainable gardening practices.

The background emphasizes challenges in traditional farming and the need for efficient automated monitoring. The proposed solution employs Arduino microcontrollers and sensors, building upon a prototype by Kumar et al. (2021). The research extends this by incorporating CO2 and TVOC sensors for improved gardening insights. The study addresses the lack of research on cost-effective, customizable, and user-friendly smart garden monitoring systems, aiming to bridge this gap.

Evaluation metrics, such as weighted means from user perceptions, validate the system's usefulness, reliability, and design appeal. Findings indicate strong agreement among evaluators regarding the system’s utility, reliability, and design aesthetics. In conclusion, the research underscores the efficiency of Arduino Uno and Arduino Mega as control systems for the smart garden monitoring system. The recommendation suggests the integration of wireless communication for enhanced scalability, customization through preset profiles, incorporation of AI and machine learning for adaptive gardening, and cost optimization for wider accessibility.

This study contributes to the advancement of smart gardening technology, offering insights for future improvements and innovations in automated garden monitoring systems.