Development of Integrated Real Time Iot-Based Monitoring System for Optimal Ipomoea Aquatica Indoor Cultivation

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 study is primarily aims at design and implement IoT system for real-time multi nodes parameters monitoring for indoor farming using related sensors and related components to tap on real time indoor farming critical parameters. Edge computing solutions and a cloud-based storage/computing to be applied accordingly as tools to facilitate data monitoring and storage. This study will involve installation of various sensors aiming at sensing parameters and functionality of nutrient quality monitoring (nutrient 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. This study also aims at collecting real-time data for future yield improvement purposes. Technically, this study will contribute a real-time monitoring system of closed-loop automated nutrient quality management, climates and irrigation for soilless indoor farming on top of useful data/trend for future indoor leafy agricultural studies and improvement particularly in Sarawak, Malaysia.