How My Android App Learned to Talk to Plants
summary
An IoT greenhouse prototype collects soil moisture, pH, CO₂, light and wind and runs actuators (PWM fan, pump at 20% moisture, linear actuator for vents, servo flaps) using threshold rules; some sensors proved unreliable so pH is kept, EC discarded, NPK re‑calibrated 10×. Edge image analysis stores 480p frames in 32MB PSRAM for green/yellow pixel and edge density tests. Network uses ESP32‑S3 + LoRa between nodes, gateway Wi‑Fi to a Flask API + Docker Compose + Cloudflare Tunnel backend with MySQL and GitHub JSON snapshots, and an Android app built with Jetpack Compose, Retrofit, Moshi, Coil for live dashboards and cached OpenWeather forecasts.
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chapters (15)
- 0:00IoT greenhouse project intro
- 1:05Smart greenhouse motivation
- 2:08Hardware and sensors
- 4:41Actuators and control
- 6:08Microcontrollers and network
- 7:11Node communication and data
- 8:39Automated thresholds
- 9:00Leaf health analysis
- 10:07Android app and website
- 12:34Android MVVM architecture
- 14:01Home screen UI
- 16:07History graphs
- 17:52Weather API
- 19:17Future improvements
- 21:01Summary & Q&A
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