Autonomous IoT-Integrated Smart Indoor Herb Farming System with Adaptive Light and Water Regulation

Abstract

The rise of controlled-environment agriculture (CEA) is the result of the dual phenomenon of fast global urbanisation and a shortage of arable land. This survey paper provides a comprehensive review of recent advancements in Internet of Things (IoT) technologies for the automation of indoor herb production through adaptive lighting and irrigation control. It examines a combination of sensors, microcontrollers, and data analytics systems, along with a range of architectural structures and enabling technologies that help facilitate efficient intelligent monitoring. The review summarises the findings of several recent studies to illustrate how IoT-based systems can enhance plant production through real-time data collection of monitored variables such as soil moisture, ambient humidity, and light levels. While significant advancements have already been made, one major limitation is that many existing systems are not yet capable of real-time operation and consequently still depend on human interventions. To bridge this gap, this paper delineates the design of a self-sufficient, IoT-orchestrated model that autonomously modulates photon flux intensity and hydraulic flow based on closed-loop feedback from a sensor network. Enhancing resource efficiency, reducing human intervention, and promoting sustainable indoor herb production are the main goals of this suggested system. The integration of predictive machine learning models and energy-aware control algorithms for next-generation intelligent farming solutions is one of the research directions suggested in the paper's conclusion.