Technical deep-dives on VPD, ESP-NOW architecture, reliability engineering and edge automation.
Not humidity percentage — VPD. Learn the right metric to understand what your plants actually feel.
Saying "keep humidity at 60%" in greenhouse cultivation is like guiding a pilot by looking at the window view. The real indicator isn't relative humidity (RH) — it's Vapor Pressure Deficit (VPD).
Air at a given temperature can hold a maximum amount of water vapor before it is "saturated." VPD measures the difference between current vapor content and the saturation point, in kPa. High VPD = air is "thirsty" and pulls vapor aggressively from the plant.
The ALAZ Sensor Node calculates two separate VPD values: one based on air measurements, and one based on leaf surface temperature. A plant's stomata sense the leaf surface temperature, not air humidity. This difference can fundamentally change stress calculations.
Formula used is the Tetens equation: SVP = 0.61078 × exp(17.27 × T / (T + 237.3)) — industry-standard accuracy from -40°C to +50°C.
Enter a target VPD (e.g. 1.0 kPa). The system calculates the ideal RH range based on current temperature. If the RH target falls outside 40–80%, it adjusts the temperature suggestion by ±2°C — one parameter, a complete climate prescription.
Not every connection point needs to be a WiFi router. The engineering rationale behind ALAZ's ESP-NOW choice.
Typical IoT projects connect every sensor to WiFi. That seems reasonable at home; but in a 200-node commercial greenhouse it means 200 separate WiFi sessions — well beyond what routers can handle.
ESP-NOW is a proprietary peer-to-peer protocol by Espressif operating at the 802.11 sublayer. It enables direct data transfer between ESP32 devices without network handshaking, IP stack, or router dependency.
| Protocol | Typical Latency | Router Required |
|---|---|---|
| WiFi (MQTT) | 50–300ms | Yes |
| BLE | 20–100ms | No (short range) |
| ESP-NOW (ALAZ) | 5–15ms | No |
Sensor nodes transmit data directly to the Gateway via ESP-NOW. The Gateway relays this over WiFi to the Core via WebSocket. Sensors never touch the WiFi network — dramatically reducing power consumption and RF congestion.
Up to 200m in open air. For enclosed metal greenhouses, a repeater topology is planned. One Gateway manages 24 nodes; one Core manages 8 Gateways — totaling 192 nodes under one roof.
Not claims — proof. Real benchmark results from ALAZ production certification tests.
When automation is involved, the word "reliable" can be an empty marketing promise. We turned it into numbers.
100 relay commands / 2 second burst, 1000 iterations, 30 minutes continuous.
A /diag request was sent every minute for 48 hours — 2,880 total requests.
In greenhouses, RF noise (metal roofs, irrigation equipment, LED drivers) can disrupt communication. When the ALAZ Relay Node loses an ACK packet:
On ESP32 microcontrollers, "heap exhausted → abort()" is common. ALAZ prevents this with a 4-tier degradation system: suspend WS broadcast, slow poll rate, slow SD writes, and as a last resort: flush SD then perform a controlled reboot. Never an unexpected crash.
No monthly subscription. No server downtime. Works through internet outages. The advantages of edge-first architecture.
Large cloud IoT platforms give great demos. In real-world scenarios, the questions that arise are: "Whose greenhouse heater turned off during server maintenance?" For us, the answer is clear: critical automation must not depend on the cloud.
All decision logic, data processing, and control runs on local hardware (the ESP32 ecosystem). Even if the internet connection drops: relay commands work, sensor data is collected, SD logging continues, automation rules stay active.
For remote centralized monitoring (viewing multiple facilities from a single dashboard), a cloud layer can be useful. ALAZ provides API endpoints for this use case — but it's an optional layer, not required for the system to operate.
"Your control center should be in your building — not in someone else's data center."