Soilless Indoor Farming: A Systematic Review of Iot-Based Monitoring Systems and Physiochemical Characterization Methods for Lactuca Sativa

With the emphasis of smarter, more efficient crop growing methodologies coupled with advances in sensors, Internet of Things (IoTs) and artificial illumination especially at the urban areas propel the development of indoor farming to another level as never been seen before as per compared to open and large-scale farming. However, there is a relatively big void in term of reference data availability for soilless indoor farming i.e precision farming, level of nutrients, light irradiances, yield improvement and etc. This review paper primarily aims to design and implement IoT system for real-time monitoring of multiple parameters in indoor farming. It involves using related sensors and components to monitor critical parameters in real-time. Edge computing solutions and a cloud-based storage/computing to be applied accordingly as tools to facilitate data monitoring and storage. The study includes the installation of various sensors such as nutrient quality monitoring (NPK sensors, pH, Electrical Conductivity (EC), nutrient temperature), climates monitoring (humidity, indoor room temperature, CO2 gas) and irrigation (flow, level and turbidity). All of these data then shall be transmitted accordingly to relevant processors, monitoring system and then being stored at clouds. The methodology is structured in a way that the system could be scaled-up for larger space and modular setting. Nowadays, IoT system is used widely in farming but trending towards application in indoor farming, for example, soilless lettuce indoor farming. This review paper has illustrated the bio-characteristics of the lettuce: Lactuca Sativa such as morphological or physiological parameters and biochemical parameters like basic chemical composition, chlorophyll, micro/macro minerals and so on which the parameters can be obtained by using modern IoT system. To set up soilless lettuce indoor farming, modern IoT system is utilized and the overall process from data monitoring to data harvesting can be simplified.