Disciplines/Subjects: Computer Science, Environmental Science, Agriculture, Robotics
Key Themes: Artificial Intelligence, Large Language Models, Model Design, Sustainable Technology
In this innovative final project, students will design and build an AI-controlled tabletop greenhouse that integrates modern technology with sustainable agriculture. The project begins with students brainstorming and sketching potential designs, considering functionality, aesthetics, and structural integrity. Using CAD software, they will create precise digital blueprints of their greenhouse. These designs will then be brought to life using a laser cutter to fabricate the structure’s components. Once cut, students will assemble the pieces, ensuring the greenhouse is sturdy and waterproof, which may involve sealing edges with silicon or other waterproofing materials.
The interior of the greenhouse will be filled with soil and planted with real vegetation. The heart of the project lies in integrating an AI-controlled environment to optimize plant growth. Students will install a series of sensors, including a soil moisture sensor to monitor water content. If the soil becomes too dry, a microcontroller, such as a Micro: bit, will automatically activate a watering system. To ensure plants receive adequate light, LED grow lights will be programmed to turn on and off based on a preset schedule or environmental feedback.
To maintain an optimal temperature, the greenhouse will include fans for cooling and windows that can be opened automatically based on temperature readings. Students will program these systems using the Micro: bit, combining coding with hardware integration. Throughout the project, students will test, refine, and troubleshoot their prototypes to achieve an efficient, self-sustaining system.
This project combines design, engineering, and environmental science while fostering skills in CAD, laser cutting, circuitry, coding, and problem-solving. By the end of the project, students will have a functional tabletop greenhouse and a deeper understanding of how AI and technology can contribute to sustainable agriculture. This hands-on experience will prepare them for real-world applications of STEM disciplines.
Thinking Habits:
Systems Thinking: Understand how sensors, software, and hardware interact to maintain optimal conditions.
Problem-Solving: Debug code, optimize hardware configurations, and enhance AI decision-making processes.
Ethical Thinking: Address accessibility and inclusivity challenges, considering the needs of individuals with autism.
Transferability: Application of AI to real-world problems, Cross-disciplinary connections between technology, agriculture, and inclusivity, Creation of prototypes applicable to larger-scale sustainable practices
Subject Knowledge: Fundamentals of AI and Arduino programming, Sensor data analysis and hardware-software interaction, Sustainable farming principles and environmental monitoring