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This kit consists of a Raspberry Pi 4, multiple Grove sensors measuring soil temperature, soil moisture, sunlight, and air temperature & humidity, etc. Designed for Microsoft FarmBeats for Students, aiming at bringing the fundamentals of AI, Machine learning, IoT, and data science into the classroom, the kit comes with FREE curricula and rich educational resources for teachers and students.
Today's farms are beginning to look a lot more like smart cities. Growers are using modern techniques like sensors, computer vision, and artificial intelligence to acquire a more complete view of their crops. These methods help them make better decisions, discover inefficiencies, and unlock new insights into improving food production. Seeed is honored and pleased to collaborate with Microsoft in the FarmBeats for Students Program (FBFS), which brings these modern tools into the hands of today's learners. The FarmBeats for Students Program combines an affordable hardware kit with curated curriculums and activities designed to give students hands-on experience in applying precision agriculture techniques to food production. The learning progression enables students to easily see the connections between these modern agriculture tools and the opportunities they afford.
The FarmBeats for Students Program combines software, an affordable hardware kit - the Grove Smart Agriculture Kit with FREE curricula and activities designed to give students hands-on experience in applying precision agriculture techniques to food production.
This Grove Smart Agriculture Kit is a hardware kit that consists of an array of multiple sensors measuring soil temperature, soil moisture, sunlight, and air temperature & humidity, etc., the parameters that are crucial for plant growth. With a relay, you can also configure the hardware kit with other hardware modules, to further extend the function from monitoring to controlling such as turn on/off the switch for irrigation or turn on/off the lighting.
With the combination of software, hardware kit, and curricula resources, the students get a hands-on and immersive experience in the process of learning, to learn about sensor technology, how the changes of data collected from different sensors affect the growth of the crops; thus they understand soil condition and crop health, etc., and make better decisions with data-driven insights.
At the same time, this hands-on experience enables students to learn about AI, Machine learning, data science, and the Internet of Things (IoT) by building a garden monitoring system. They assemble a Raspberry Pi equipped with atmospheric and environmental sensors to understand their soil's health, understand the environmental parameters that affect plant growth, analyze the data, and make decisions. The student-built IoT devices connect to custom Excel workbooks that collect real-time data using Excel's Data Streamer. They can see the visualized data and further analyze it, thus they can gain insights and make data-driven decisions for their crops.
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We deliver in Namibia to 15 major towns. Other towns can be accommodated on request.
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