How My Android App Learned to Talk to Plants
summary
An IoT greenhouse that collects sensor data with an ESP32S3 network of nodes and uploads JSON snapshots to a Flask API/MySQL backend routed via Cloudflare Tunnel and mirrored to GitHub, with an Android app using Jetpack Compose, Moshi and Retrofit for live dashboards. Hardware includes SED41 CO₂/temperature/humidity, BH1750 light, capacitive moisture and pH (SEN603), actuators: PWM fans, water pump, linear actuator and servo; thresholds trigger actions (e.g. 30% moisture, 45°C), 10‑minute uploads, and a crude 480p on-device leaf detection prototype; EC/NPK sensors proved unreliable and were downweighted.
AI-written summary · about
chapters (10)
- 0:00IoT greenhouse project intro
- 1:06Hardware components overview
- 3:35Soil sensors calibration
- 5:44Actuators and automation
- 7:30Network config and LoRa
- 9:58On-device plant image processing
- 11:04Android app architecture
- 13:32API integration and data flow
- 16:00Weather integration and improvements
- 17:50Q&A
related talks
22mHow My Android App Learned to Talk to Plants
54mAutomating & Monitoring Seedling Growth in the Cloud Using IoT, Messaging & Micronaut
21mObservability Made Simple: Monitoring Plants with IoT & Grafana
28mBuilding an IoT Monitoring App with InfluxDB
31mBuilding an IoT App with InfluxDB, Python, Flask And Plotly
56mAutomating & Monitoring Seedling Growth in the Cloud Using IoT, Messaging & Micronaut
33mNode-RED and Android in IoT Application Development
37mAndroid Industrial: Real-time data visualization