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Seeed Studio Grove Smart Agriculture Kit for Raspberry Pi 4

$105.00 $123.99


Tags:

Raspberry Pi


Categories:

Raspberry Pi Kits
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  • Description

Features

  • Easy-to-use and low-cost hardware kit: combines an affordable hardware kit with FREE curriculums and activities for students’ hands-on experience in precision agriculture techniques to food production.
  • New tools for STEAM Education learners: students learn about AI, Machine learning, and IoT by building a garden monitoring system.
  • Easily use with Raspberry Pi 4: with atmospheric and environmental sensors to understand their soil's health, analyze data, and make decisions.
  • Real-time data collection: The student-built IoT devices connect to custom Microsoft Excel workbooks that collect real-time data using Excel’s Data Streamer.
  • Building your own Machine Learning models: using Lobe.ai, students apply the technique to predict nutrient deficiencies in their plants and identifying pests in their garden.
  • Introducing Microsoft responsible AI framework: engaging students with some of the social and ethical challenges raised by this new technology.

Applications

Combined with software and curriculum & resources, you can get hands-on experience, learn about artificial intelligence, machine learning, the Internet of Things, data science and then apply the knowledge in growing plants in the real world.

This kit is highly suitable for use in different scenarios, no matter in the classroom, at home, at maker spaces/ fab labs or through distance learning courses:

  • School garden monitoring
  • Home garden monitoring
  • Distance teaching /learning
  • Online courses
  • Hobby and DIY projects

Included

  • 1x Grove Base Hat for Raspberry Pi with a Fan
  • 1x One Wire Temperature Sensor
  • 1x Grove Capacitive Soil Moisture Sensor
  • 1x Grove Sunlight Sensor
  • 1x Grove Temperature & Humidity Sensor
  • 1x Grove Relay
  • 1x Grove Dual Button
  • 1x micro SD Card with Card Reader (32 GB)
  • 1x USB to TTL Serial Cable
  • 1x Screwdriver

Downloads