AI Agritech Lab Kit

AI Agritech Lab Kit  Grades: 9th+ Number of Students: 2 participants per kit  Number of Lessons: Not specifically stated — lesson plans are included Hours of Content: 15 to 20 contact hours   Highlights: AI + sensor kit applying computer vision and machine learning to real-world agriculture, Data Science,r and environmental-monitoring use cases. Works with Gen AI, Power BI, Python, 13 sensors, and Excel.  The AI Agritech Kit is an AI, IoT, and data-science lab that transforms live sensor data into intelligent farming decisions using Generative AI. Students collect real-world data from 10 agriculture sensors, analyze it with Python and Excel, visualize it with Power BI, then query a Generative AI agent in plain language (including voice-in/voice-out interaction) to get insights, recommendations, and predictions. Built-in AI guardrails are cited for safe, responsible, and age-appropriate learning. Positioned as a project-based, inquiry-driven learning experience.   Curriculum or Lesson Topics: Environmental & Soil Monitoring: Using Soil Moisture, Raindrop, and Temperature/Humidity sensors to simulate irrigation and crop-health monitoring decisions Climate & Air Quality Sensing: Using the Gas Sensor and Light Detector to model greenhouse conditions, air quality, and growing-condition monitoring Smart Irrigation & IoT Automation: Combining multiple sensors (sensor fusion) into an automated decision system — e.g., triggering irrigation logic based on soil and rainfall data Data-Driven Farming Decisions: Using Python and Power BI to analyze collected field data and surface trends relevant to crop and resource management Generative AI for Agricultural Insight: Applying Gen AI to interpret sensor data and generate natural-language recommendations, mirroring real AI-powered agricultural advisory tools Sustainability & Global Impact: Connecting sensor-based projects to UNSDG themes — Zero Hunger, Climate Action, and Sustainable Communities — framing the kit's work around real agricultural and environmental challenges   Standard Alignments: AI4K12 “5 Big Ideas of AI”, ISTE, CSTA, NGSS, Common Core   What’s Included: 1 Data Block (central sensor hub, 7 total ports — 6 GPIO + 1 I2C, USB-C for charging/data transfer) 10 Agriculture Sensors: LDR sensor, Gas sensor, Raindrop sensor, Soil Moisture sensor, Liquid Temperature sensor, Photogate sensor, Ultrasonic sensor, Humidity sensor, & PIR Motion sensor Gen AI tool integration for insights & predictions Lesson plans and facilitator reference guide   Technology Requirements/Specifications: Computer: A Windows OS laptop or desktop is strongly recommended — the DSPRO Software, Device Manager/driver steps (CH340/CP210x USB drivers), and Excel Data Streamer integration are Windows-oriented workflows per the product manual. USB Port: A free USB-A or USB-C port (with adapter if needed) to connect the Data Block via the included USB-C cable Microsoft Power BI: For advanced data visualization and dashboarding (Power BI Desktop or Power BI service access) Python: For data science workflows referenced in the AI Lab brochure (Python | Power BI listed as a feature) — a Python 3.x environment with relevant data science libraries Generative AI Access: Since Gen AI Integration is a listed feature, access to a Generative AI tool/service is required. Internet Access: Needed for Gen AI integration, Power BI cloud features (if using the online version), and initial software/driver downloads Minimum System Specs: A current machine with at least 4-8GB RAM to comfortably run Power BI, and Python simultaneously Programming Platform: AI Agritech Lab software, Python and Power BI   Special Notes and Considerations: Due to production time, this item typically ships 3-4 weeks after receipt of the order.