Objective: Transmit and visualise sensor data on cloud platforms
Group Name: SweetHertz
| Student | Admission No. |
|---|---|
| Njogorio Sharon Nyambura | 164110 |
| Jonyo Janny | 166885 |
| Ogutu Cindy Atieno | 158842 |
| Mukoma Dennis Murage | 139360 |
| Kemoi Kristina Chebet | 168652 |
| Mapelu Neema Naserian | 150176 |
This deliverable extends Architecture (a) from Deliverable 2 - ESP32 + MQ-5 + DHT22 + LCD - by adding cloud connectivity. The ESP32 connects over simulated WiFi (Wokwi-GUEST), reads sensor values every 10 seconds, and publishes them to InfluxDB Cloud (time-series storage) which is then visualised through a Grafana dashboard.
[DHT22] ──┐
├──→ [ESP32] ──WiFi──→ [InfluxDB Cloud] ──→ [Grafana Dashboard]
[MQ-5] ──┘ │
[LCD]
| Component | Role | Connection |
|---|---|---|
| ESP32 DevKit V1 | Microcontroller | - |
| DHT22 | Temperature & humidity sensor | GPIO 15 |
| Potentiometer (MQ-5 simulated) | Gas level (analog) | GPIO 34 |
| LCD 16 × 2 I2C | Local display | GPIO 21 (SDA), GPIO 22 (SCL), addr 0x27 |
Note: Wokwi does not have a native MQ-5 component. A potentiometer is used to simulate the analog output of the gas sensor, which can be swept from 0 V to 3.3 V to represent varying gas concentrations.
Wokwi Project: https://wokwi.com/projects/468734014046870529
The firmware for the simulation is stored in deliverable3/wokwi-web/sketch.ino, with the corresponding circuit definition in deliverable3/wokwi-web/diagram.json and library list in deliverable3/wokwi-web/libraries.txt. The project configuration is provided in deliverable3/platformio.ini.
- Boot sequence - initialises LCD, DHT22, connects to
Wokwi-GUESTWiFi, syncs NTP time, validates InfluxDB connection. - Sensor loop - reads DHT22 (temperature & humidity) and MQ-5 analog value every 2 seconds; displays live readings on the LCD.
- Cloud publish - every 10 seconds, writes the sensor readings to InfluxDB Cloud over HTTPS for time-series storage and later visualisation in Grafana.
The firmware therefore performs local sensing, on-device display, wireless transmission, and cloud logging within a single ESP32-based monitoring node.
The simulation was connected to the greenhouse bucket in InfluxDB Cloud, where all readings from the greenhouse_sensors measurement were stored as time-series data.
The following fields are written to the greenhouse_sensors measurement on every publish cycle:
| Field | Unit | Description |
|---|---|---|
temperature |
°C | DHT22 ambient temperature |
humidity |
% RH | DHT22 relative humidity |
gas_raw |
ADC count (0–4095) | MQ-5 raw 12-bit ADC reading |
gas_voltage |
V | MQ-5 voltage derived from ADC reading |
Grafana was connected to the same InfluxDB bucket and used to create dashboard panels for temperature, humidity, and gas readings over time.
The Grafana dashboard was designed to track the main greenhouse variables over time and to relate them to the environmental ranges identified for daisy growth in Deliverable 1.
| Panel | Visualisation | Purpose |
|---|---|---|
| Temperature Over Time | Line chart | Shows how greenhouse temperature changes over time and whether it remains within the desirable 15 – 24 °C range. |
| Humidity Over Time | Line chart | Tracks relative humidity trends and helps identify whether the environment remains near the target 40 – 60% RH range. |
| Gas Level Over Time | Bar chart/time series | Displays the changing analog MQ-5 reading, indicating variation in simulated gas concentration levels. |
Grafana Dashboard: https://wittyzeppelin2875.grafana.net/goto/s8b8wt?orgId=stacks-1713913
Despite consistent hardware troubles, we attempted the physical implementation as well.
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