Enterprise AI Analysis
From Soil to Software: Experience from a STEM Workshop on Smart Plant Care and Teachable Machines
This workshop introduces high school students to AI and computing through hands-on activities involving smart plant care. Participants build IoT sensor systems, train image classifiers with Teachable Machine, and explore real-world AI applications, bridging the gap between theoretical concepts and practical implementation.
Executive Impact at a Glance
Key metrics for immediate executive insight.
0%
Student Engagement
0%
AI Literacy Boost
0%
Hands-on Learning
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
IoT & Sensors
Machine Learning
Educational Impact
Exploring the integration of hardware and software for environmental monitoring.
Understanding AI model training and deployment for practical applications.
Analyzing the effectiveness and student feedback of the workshop curriculum.
100%
Accessibility for Novice Learners
Enterprise Process Flow
Data Acquisition (Sensors)
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Visual Programming (MakeCode)
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Data Logging (Google Sheets)
→
AI Model Training (Teachable Machine)
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Real-time Inference
| Feature | Workshop Approach | Traditional Methods |
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| Data Collection |
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| AI Training |
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Case Study: Smart Plant Care Assistant
High school students successfully developed and deployed an IoT-based smart plant care system, utilizing ESP32 microcontrollers and environmental sensors. They programmed conditional logic to provide automated care recommendations based on real-time data.
Company: Toledo EXCEL Program
Outcome: Enhanced understanding of embedded systems, data science, and basic AI logic through tangible results.
95%
Positive Student Feedback
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Phased Implementation Roadmap
A strategic approach to integrating AI into your enterprise.
Phase 1: Sensor System Deployment
Configure ESP32 microcontrollers and integrate environmental sensors for data acquisition.
Phase 2: Visual Programming & Data Logging
Students use MakeCode to program sensor logic and log data to Google Sheets.
Phase 3: AI Model Development
Train image classifiers with Teachable Machine for plant health analysis.
Phase 4: Real-world Application & Refinement
Integrate AI models for smart plant care decisions and iterate based on feedback.
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