Week 01 — Project Management

Fab Academy 2026 · Jenny Rojas · Industrial FabLab UCuenca

1. Thought Process

Overview and Motivation

Orchids have specific cultural needs: airy substrates such as bark and sphagnum, high sensitivity to overwatering (which increases root rot risk), and a strong dependence on stable humidity and temperature cycles for healthy growth and flowering.

The central challenge is to provide water in a way that keeps both the substrate and the plant healthy while minimizing water waste and human intervention.

The proposed solution combines multiple data sources — substrate moisture, ambient humidity, temperature, and camera-based visual monitoring — with an AI decision engine that adapts watering volume and timing.

Evidence basis: Research in precision irrigation and IoT shows that sensor-driven systems using machine learning improve water efficiency and plant outcomes. Orchid horticultural guidelines provide target humidity ranges and substrate recommendations.

2. Project Ideas Exploration

Option A — Threshold-based Moisture Pump

A simple system where a substrate moisture sensor activates a micro-pump when readings fall below a fixed threshold.

Pros: Low cost, easy to build, fast to prototype.

Cons: Not adaptive; risk of overwatering.

Option B — Microclimate Controller

Controls ambient humidity using a nebulizer and fan, while watering remains manual or semi-assisted.

Pros: Good for epiphytic orchids.

Cons: Higher energy use and complexity.

Option C — Sensor Fusion + Edge AI (Selected)

Combines moisture, humidity, temperature, and camera data processed by a lightweight AI model running on an edge device.

Pros: Adaptive decisions, visual diagnostics.

Cons: Higher hardware and software complexity.

Option D — Educational STEAM Kit

Modular kit designed for classrooms where students assemble and program the system.

Pros: Educational, low cost.

Cons: Not fully autonomous.

Option E — Cloud-connected Commercial Pod

Full system with cloud analytics, dashboards, and predictive maintenance.

Pros: Advanced analytics.

Cons: Cloud dependency and higher cost.

3. Defining My Project

Chosen Option: Sensor Fusion + Edge AI

The goal is to build an autonomous orchid pot that automates watering decisions using fused sensor inputs and visual monitoring.

Sensors: Capacitive moisture, temperature & humidity, water level, camera
Actuators: Peristaltic pump, LEDs or buzzer
Compute: ESP32 + Raspberry Pi or Jetson Nano
Connectivity: Wi-Fi (MQTT), local storage
Safety: Low-water lock, emergency stop, watchdog timer

Success criteria: Healthy orchids over a 6-week trial, at least 25% water savings, and system uptime above 95%.

4. Experimentation Plan

Phase 0: CAD design, 3D printing, sensor calibration
Phase 1: Alpha prototype and data collection
Phase 2: ML training and edge inference deployment
Phase 3: Real-world pilot and comparative analysis

5. Conclusion

Sensor fusion combined with edge AI enables a robust autonomous orchid pot that optimizes water usage, reduces root rot risk, and adapts to environmental variation. Digital fabrication ensures reproducibility and educational impact.