The current research in indoor hydroponics is centered around the creation of sustainable and efficient IoT-based systems. The use of sensing devices allows these systems to continuously collect data in real time about many of the critical variables within a growing environment (temperature, humidity, pH, electrical conductivity, etc.) and to be controlled remotely. In addition to providing remote access to the growing environment, many of these systems are designed using cost effective materials (microcontrollers) and are built using open-source software platforms; this enables them to scale and accommodate smaller environments. With respect to automation, the systems provide for automatic dosing of nutrients, pH control, and climate/environmental control, which will allow growers to minimize their involvement in the growing process while maintaining an optimal growing environment. Additionally, the application of machine learning techniques may provide opportunities for improving the growth potential through optimized control strategies developed from large amounts of data. As the field continues to evolve, it appears that the focus will continue to be on developing low-cost, high-efficiency, and user friendly indoor growing systems capable of supporting self-sustained food production systems particularly in areas where the amount of arable land is limited, or the climate makes outdoor farming impossible.
K et al. (Thu,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: