From sensory judgment to data-driven decision, modern fermentation monitoring is undergoing a technological revolution.

Parameter logic and alarm threshold setting in practice are the core defense for ensuring fermentation quality.

Expert experience beyond textbooks: the three pitfalls of sensor drift, control hysteresis, and data silos.

Technical architecture and sensor deployment diagram of modern fermentation room temperature and humidity monitoring system

±0.1°C

Sensor display accuracy

±2°C / ±5°C

Warning / Action temperature threshold

30 min

Humidity exceedance delay filter time

5 min

Valid alarm duration judgment time

38°C → 36°C

Cooling on/off hysteresis

85% RH

Ambient humidity action threshold (middle plateau)

±2%

Sensor replacement deviation threshold

3 层 / 多点

Spatial gradient deployment (upper/middle/lower)

Baijiu Daqu Fermentation

Temperature curve shows 'slow rise, middle plateau, slow decline' characteristics; material temperature is the core monitoring indicator, and preventing 'burning' is critical.

Bakery Product Proofing

Extremely sensitive to humidity; balance between surface crusting and droplet formation; delay filtering recommended to avoid false alarms from door opening interference.

Modern Fermentation Room Temperature and Humidity Real-Time Monitoring Technical System and Parameter Alarm Thresholds

At three in the morning in the fermentation room, aside from the faint sound of equipment operation, there is that unique stillness filled with the scent of fermentation. In many people's impression, fermentation is a process full of "artistic sense" — veteran masters judge by smelling, looking, and touching based on experience. But in my ten years of industry experience, I have increasingly realized: Without data support, all "experience" is extremely fragile in the face of modern industrial production.

I once experienced an extremely painful lesson. It was late autumn 2021 at a large-scale baijiu production base in the south. Due to the seasonal transition, external humidity fluctuated greatly. We had deployed a basic temperature and humidity monitoring system at that time, but because we were too greedy for cheapness in sensor selection and used non-industrial consumer-grade probes, after three consecutive days of rainy weather, the environmental humidity became too high, causing severe electrochemical drift in the sensors. The system consistently showed humidity around 75%, which looked perfect, but in reality, the actual humidity inside the fermentation pits had soared to over 92%.

When we discovered abnormal "water stains" and unusual moldy odors on the surface of the koji starter blocks the next morning, that batch of valuable koji blocks was completely ruined. This accident taught me: A fermentation monitoring system must not only "see" data, but also "see accurately," and must be capable of surviving in extreme environments while continuously outputting accurate information.

I. From "Sensory Art" to "Digital Twin": The Technical Architecture of Modern Monitoring

Modern fermentation room monitoring has evolved from the era of single instrument panels to the closed-loop IoT (Internet of Things) era of "sensing-transmission-decision-execution." A system that can truly withstand production pressure must have a rigorous four-layer architecture.

1. Perception Layer: Reject "Cheap Accuracy"

In the perception layer, many enterprises easily make a mistake: believing that any sensor with a display accuracy of ±0.1°C is a good sensor. This is completely a misconception. In environments like fermentation rooms with high humidity and possibly corrosive gases (such as CO₂, NH₃), Stability is far more important than Accuracy.

The industrial-grade solution I recommend must meet the following three hard requirements:

Anti-condensation design: The sensor probe must have a hydrophobic coating to prevent water droplets from forming a bridge on the probe when humidity approaches saturation, causing instant reading jumps.

Multi-point spatial gradient deployment: A fermentation room is not a uniform box. In large koji rooms or proofing rooms, there is an obvious "heat island effect." I usually require vertical deployment at upper, middle, and lower heights within the room, and set monitoring points near doors and windows, near vents, and at the center of the room. If you only use one point, you see the temperature of "one point," not the state of "the entire space."

Decoupling of material temperature and environmental temperature: This is easily overlooked by many beginners. Environmental temperature and humidity monitor the "air," while the core of fermentation is the "material temperature" (such as the interior of koji blocks or dough center). A complete system must simultaneously connect environmental probes and insertion-type material temperature probes, because the temperature difference (ΔT) between the two is often a key indicator for judging the fermentation stage.

2. Transmission Layer: Stability Is the Lifeline

In the selection of transmission protocols, I always adhere to one principle: Critical control logic uses wired, auxiliary monitoring uses wireless.

Wired (RS485/Modbus): For core PLC control loops, the Modbus RTU protocol must be used. It is extremely stable with strong anti-interference capability — even in complex electromagnetic environments (such as when large fans start), data will not be lost.

Wireless (LoRa/NB-IoT): For hard-to-wire corners or temporarily added monitoring points, LoRa is my first choice. Its penetrating power is extremely strong, performing far better than WiFi or Zigbee in reinforced concrete factory buildings.

3. Decision and Execution Layer: The Value of Edge Computing

Many people are superstitious about "cloud monitoring," believing that only processing all data in the cloud counts as intelligence. But in actual production, this is very dangerous. Once there is network fluctuation, your alarms will be delayed.

I advocate "Edge-side decision-making, cloud-side analysis." All alarm threshold judgments and PID temperature control logic must run on the local PLC or edge gateway. The role of the cloud should be to record historical trends and perform long-cycle process optimization analysis, not to be responsible for immediate safety control.

II. Parameter Logic and Alarm Threshold Setting in Practical Scenarios

Parameter setting is not decided by intuition; it must be based on process curves. I will give my recommended settings through two typical scenarios.

1. Baijiu Daqu Fermentation: Capturing the Pulse of the "Middle Plateau"

Baijiu fermentation is a dynamic biological process, and its temperature curve presents the typical characteristics of "slow rise, middle plateau, slow decline."

Fermentation Stage	Core Objective	Recommended Ambient Temp	Recommended Ambient Humidity	Key Monitoring Indicator
Slow Rise Stage	Surface growth, mold development	25–35°C	80–90% RH	Observe microbial colonization
Middle Plateau Stage	Microbial metabolic peak	35–45°C	70–80% RH	Material temperature is the core, prevent "burning"
Slow Decline Stage	Cooling, drying	20–30°C	50–65% RH	Prevent excessive heat or moisture absorption in later stage

My recommended alarm thresholds (using the middle plateau stage as an example):

Early Warning: When the material temperature deviates from the target value by ±2°C, the system should trigger a silent warning (e.g., APP push notification) to remind operators to check ventilation or moisture.

Action Threshold: When the material temperature deviates by ±5°C, or the ambient humidity exceeds 85% for 30 consecutive minutes, an audible and visual alarm must be triggered, along with automatic activation of the exhaust system.

Experience: During the middle plateau stage, never look only at the ambient temperature. If the ambient temperature is low but the material temperature is abnormally high, it indicates excessively active internal fermentation. Immediate cooling intervention is required, otherwise acidity may become uncontrolled.

2. Bakery Product Proofing: The "Balance Beam" of Humidity and Temperature

The proofing room in the baking industry is extremely sensitive to humidity. If the humidity is too low, the dough surface will crust, preventing volume expansion; if too high, water droplets will form on the surface, affecting color and structure.

Stage	Temperature Setting	Humidity Setting	Recommended Alarm Threshold (Warning / Action)
Primary Fermentation	26–28°C	75–85% RH	Temp ±1.5°C / Humidity ±5% RH
Final Proofing	35–38°C	80–90% RH	Temp ±2°C / Humidity ±7% RH

Pitfall Guide**: In the final proofing stage, the most common cause of alarms is "door opening interference." When an operator opens the proofing room door for loading or unloading, temperature and humidity drop instantly. If your system is set too sensitively, it will frequently trigger false "cry wolf" alarms. **I recommend adding "delay filtering" to the alarm logic: only when the value deviation exceeds the set threshold and persists for more than 5 minutes should it be judged as a valid alarm.

III. Expert-Level Pitfall Guide: Things Textbooks Don't Tell You

When actually deploying monitoring systems, you will encounter many "non-technical" issues.

Sensor "Drift" and "Dead Zone": In high-humidity environments, sensors are prone to failure. I recommend establishing a "periodic calibration mechanism." Use a standard calibrator to compare core monitoring points every quarter. If a deviation exceeding 2% is found, replace it directly — do not attempt software compensation.

"Hysteresis" Setting in Control Logic: Many junior engineers, when writing control programs, set "cooling on at 38°C, off at 37.9°C." This causes the equipment to start and stop frequently at the critical point, wasting energy and severely shortening compressor or heater lifespan. A hysteresis must be set, for example: start cooling at 38°C, stop only when it drops to 36°C.

Data Silo Problem: Many factories' monitoring systems are closed — data can only be viewed, not exported. This is fatal when facing HACCP or ISO quality traceability audits. Be sure to choose a system that supports open protocols (such as MQTT or API) so your monitoring data can seamlessly connect to the enterprise's ERP or MES systems.

IV. Conclusion

Modern fermentation room temperature and humidity monitoring is transforming from an "auxiliary tool" to a "core productive force." It should not merely be a screen displaying numbers, but an intelligent organ capable of sensing risks, predicting trends, and responding autonomously.

Technical tools can replace the naked eye, but cannot replace decision-making. An excellent monitoring system provides experienced veterans with a pair of "digital eyes" that can see through darkness and observe microscopic changes. When we can precisely control every temperature fluctuation and every change in humidity, we have truly mastered the art of fermentation.