Difference between revisions of "Team:NCTU Formosa/Model"

     The purpose of our smart farming system is to precisely regulate soil microbiota using bio-stimulators to achieve a desired effect. While microbiology and ecology drive the efficiency of our bio-stimulators, dry-lab analyses and models power the control center of our system. To truly achieve precision regulation, we designed a system of interconnected models, linked together through our IoTtalk platform and strengthened by continuous feedback of data. NGS data provides invaluable details of our bacterial regulation network. Machine learning software in the form of Weka processes these details, granting prediction capabilities made more accurate through self-learning. An electrical conductivity sensor details levels of nitrogen, phosphorus and potassium present in soil and alerts farmers when another application is needed, and a curcumin sensor allows for consistent monitoring of curcumin concentrations without damaging plants. Both sensors transmit figures constantly through IoTtalk, providing steady data for calibration of their respective models through artificial intelligence. Finally, inhibition modelling of newly constructed bio-stimulators in the form of bacteriocins grants even greater precision, while peptide prediction using the Scoring Card Method characterizes even more novel and efficient bio-stimulators. Click below to learn how we turn farming into a science!