Industry Brief (30 minutes)

Present the AI in the Field: Agriculture slide deck and introduce the real-world AI application.

How is AI used in Agriculture?

Begin by discussing the challenges farmers face when monitoring crops. Ask students:

• What challenges might a farmer face when trying to monitor a large field of crops?
• Why might it be difficult for a human to inspect every crop individually?
• How could technology help farmers gather information about their crops more efficiently?

Explain that many farms use AI crop monitoring systems to check crops across large fields. These systems help farmers quickly identify crop health such as: healthy, dehydrated, dead.

• Help students distinguish between Input → Processing → Output → Action.

Input - The farmer sets up and programs the AI system by choosing what it should detect and provide crop images or sensor data for analysis.

Processing - The AI system uses cameras and sensors to capture images of crops and analyze visual patterns such as color, shape, or texture to detect crop health.

Output - The AI outputs a classification describing the crop’s condition, such as healthy, dehydrated, or dead.

Action - The program uses that output to trigger a response, such as flagging crops for attention, recording crop health data, or guiding equipment to specific areas of the field.

AI Systems and Human Decision-Making

Explain that AI crop monitoring systems can help farmers quickly identify patterns and understand what is happening across large fields. However, AI systems do not replace human decision-making. Farmers still need to review the information, interpret the results, and decide what actions should be taken.

Ask students:

• What decisions should still be made by the farmer instead of the AI system?
• Why is it important for humans to review and interpret AI outputs?
• What could happen if a farmer relied only on AI predictions without human oversight?

Explain the Challenge (10 minutes)

Show the agriculture mat and crop cards. Introduce the scenario and explain the AI system students will build across the module.

Scenario: A farmer has noticed that some crops are not growing well but is unsure why. Some are healthy, some are dehydrated, and some are dead. The farmer needs a way to quickly monitor crop health across the field. Students will build an AI-powered crop monitoring system using Ari to simulate an agricultural monitoring drone that moves through the field, captures images of crops, and identifies their health. Using this information, the system can help the farmer locate unhealthy crops and decide what actions may be needed.

What Students Will Build Across the Module

Lesson 2 - Sensor Data Collection

Students use Ari’s ToF sensor and Compass App to measure and map crop fields by collecting distance and directional data for each plot.

Lesson 3 - Using AI for Crop Navigation

Students use AI to identify a specific crop condition and use the output to guide Ari to the correct crop location.

Lesson 4 – Building an AI Data Collection System

Students expand their system to identify crop conditions and locations, then record and organize the collected data.

Lesson 5 – Designing an AI Crop Monitoring System

Students build a complete system that scans the entire field, identifies crop conditions, and collects data across all crop locations.

Lesson 6 – AI System Capstone

Students analyze the data collected by their crop monitoring system and evaluate how effectively it identified and monitored crop conditions.

Clarify Success Criteria

A successful AI crop monitoring system will:

1. Detect crop conditions using camera input
2. Output accurate classifications (healthy, dehydrated, dead)
3. Use outputs to guide Ari’s movement and behavior
4. Collect and organize data about the field

Group Exploration (25 minutes)

Have students turn to Module 2, Lesson 1 in their Field Notebooks and begin on the AI System Framework page. They will use this page to record their work throughout the lesson.

Students will research and select two AI systems in agriculture and complete a chart for each.

• Students should use this information to refine their system design and better understand how AI crop monitoring systems work in real environments.

Suggested research questions include:

1. How is artificial intelligence used in agriculture?
2. What tasks do agricultural robots or AI systems perform?
3. What kinds of data do AI systems collect when monitoring crops?
4. How do cameras and sensors help farmers understand crop health?
5. What technologies help farmers detect crop diseases or dehydration?

Designing Your AI System

Give students the Agriculture Mat and Crop Cards. Display the planning questions for students to reference as they work and take notes in their Field Notebooks. Students should discuss:

• What problem is your agricultural AI system designed to help solve?
• How will Ari move throughout the fields?
• What crop conditions or visual patterns will the AI system detect?
• What information or data will the system need to collect?
• How should the system respond to different crop conditions?

Exit Ticket - Explain Your Thinking (10 minutes)

Conclude the lesson by presenting the “Explain Your Thinking” question and having students independently complete a written response in their Field Notebook.

Explain Your Thinking:

In your own words, what is Ari’s role in this system, and what is the farmer’s role? What does this show about the difference between an AI system and the human using it?