Improved Internet of Things (IoT) monitoring system for growth optimization of Brassica chinensis

Abstract

The Internet of Things (IoT) has been integrated in various applications such as smart homes and smart cities. IoT in agriculture such as in monitoring indoor climatic conditions can help to improve the plant growth. This paper proposes a new approach in utilizing IoT technology as a remote monitoring system to control the indoor climatic conditions via light emitting diode (LED) parameters which include spectrums, photoperiod and intensity in order to increase yields as well as to reduce the turnaround time. This study showed that growth of Brassica chinensis under different wavelengths of light source has influenced plant growth performance and phytochemicals characteristics. Four different light treatments were experimented using pulse treatment (1 h light and 1 h dark), continuous light (CL), high intensity and artificial light control of 12 h light and 12 h dark. Data such as the leaves count, height, dry weight and chlorophyll a & b of plants were analyzed. The results showed high mean value of plants’ fresh weight (FW) of 410.77 g under pulse treatment compared to other light treatments. The percentage of moisture content (MC) was recorded higher on average under normal light (99.15%), value of leaf area (LA) was recorded higher under artificial sunlight with an average value of 976.84 cm2. Even though the results of LA were better under artificial sunlight, CL with low intensity gave higher stem height (SH) and number of leaves (NOL). In order to capture real-time data and monitor the environmental parameters of the plant experiment, an intelligent embedded system was developed to automate the LED control and manipulation. The results showed that the system is stable and has significant referential in the area of plant factory or indoor farming.