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Agriculture 4.0: Automation with Big Data


In this course, students will explore IoT robotics in application to agriculture when creating their own smart plant. They will utilise their computational thinking when programming to find the perfect environment to help plants grow by themselves. Students will nurture their problem-solving skills and growth mindset in a practical immersive learning environment which is essential for their personal development and success. FlipRobot Agriculture 2.0 – Autonomous with Big Data course is offered to students to learn at home through online live delivery with our certified coaches.

Certificate on Completion
Own the robotic hardware kit for continuous learning
Qualify to enter the international OneWorld Robotics Competition
Background on Agriculture 4.0:  Automation with Big Data

Source: EY and Microsoft


Module 1

  • Future in Farming Challenge Briefing

  • Introduction to the Internet of Things (IoT)

  • Introduction to robotics in agriculture

  • Assembly of Smart Plant

Module 2

  • Introduction to Moisture Sensor

  • Coding multiple sensors in Blockly

  • Future in Farming Challenge 1: A Place In The Sun

Module 3

  • Introduction to serial data

  • Computational Thinking in deciphering serial data

  • Coding using real-time information

  • Future in Farming Challenge 2: The right climate

Module 4

  • Future In Farming Final Practical Challenge

  • Future In Farming Final Presentation Challenge 

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Course Outline
  • Construct a solution design of an autonomous vehicle using Internet of Things (IoT)

  • Assemble agricultural robotics and adjust through mechanical engineering of different hardware features

  • Design robotic codes using big data to control robotics movements using multiple coding platforms

  • Apply computational and design thinking into practice

  • Critically evaluate the current agriculture technology to propose a viable design solution to an agricultural automation related problem

  • Acquire knowledge to program and calibrate motors to control the robot in response to real world data

  • Master their skills using FlipCode to control robotics movements to complete industrial agriculture

  • Embody the growth mindset principle into practice

Learning  Outcomes
  • Age-group suitability: Years 7 to 9 

  • Prerequisite requirements: None

  • Class format: Live online teaching via Zoom. Robotic assembly and coding by students at home. Interaction between teacher and students live online

  • System requirements: 

    • Windows 10 version 1809 and above (64 bits)

    • If using ChromeOS, users will require to install the FlipRobot Chrome extension

    • Support macOS but not iOS​

    • An Internet connection and an internet browser

    • Zoom video conference application

    • A computer with a camera, mic, speaker (or headphones)

  • We will require a physical delivery address to send the FlipRobot hardware kit.

Course Details
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