Open source agritech for sustainable growth

Over-salination of soil threatens crop yields in many countries. However, traditional farming methods exacerbate issues with over-fertilisation, and there is lack of standardised data for comprehensive studies on this problem. Moreover, the vast majority of farmers face challenges in monitoring environmental conditions and health of their crops.

In this project, we designed an open source IoT farming system to automate processes, provide real-time data, and optimise resource usage for precision farming. By utilising and analysing crop data, the system optimises parameters to enhance crop growth.

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Project Team

Students:

  • Ian William Snodgrass (Chemical Engineering, Class of 2024)
  • Lam Shao Ren, Derek (Chemical Engineering, Class of 2024)
  • Lim Weizhe (Mechanical Engineering, Class of 2024)
  • Namuduri Venkata Raghav (Chemical Engineering, Class of 2024)
  • Wong Jun Lin (Electrical Engineering, Class of 2024)

Supervisors: