Designing the IoT System for a Smart Mushroom Growing Environment

Building a smart agricultural system involves much more than simply placing sensors inside a room.

The sensors need to be selected appropriately, positioned correctly, connected to a reliable monitoring system and integrated with the equipment responsible for controlling the environment.

As part of the BRIDGE-AI: Smart Mushroom project, I have been involved in exploring how an IoT-based environmental monitoring system can be implemented within a mushroom growing house.

Understanding the Growing Environment

A mushroom growing room is essentially a controlled environment.

The conditions inside the room need to be monitored because changes in environmental parameters can affect the cultivation process.

For our design, we focused on several important parameters:

- Temperature

- Relative humidity

- CO₂ concentration

- Light intensity

These measurements give the system an understanding of what is happening inside the growing space.

Sensor Selection

Different sensors are used for different measurements.

DHT22 - Temperature and Humidity

The DHT22 is used to measure both temperature and relative humidity.

We incorporated multiple DHT22 sensors into the design rather than relying on a single measurement point.

This is important because environmental conditions may not be perfectly uniform throughout the growing room.

SCD30 - CO₂ Monitoring

The SCD30 is used to monitor carbon dioxide concentration.

CO₂ is particularly relevant in an enclosed growing environment because its concentration can change depending on ventilation and biological activity.

Having continuous measurements allows the system to identify changes that may otherwise go unnoticed through occasional manual checks.

BH1750 - Light Intensity

The BH1750 provides measurements of ambient light intensity.

Although light may not be the primary environmental variable for every stage of mushroom cultivation, monitoring it gives the system another useful parameter for understanding and documenting the conditions within the growing space.

Sensor Placement Matters

One of the most important design considerations is where the sensors are placed.

It might seem reasonable to simply install a sensor anywhere inside the room. However, this can produce misleading measurements.

For example, placing a temperature and humidity sensor directly beside a heater could cause it to measure conditions that are not representative of the rest of the growing environment.

Similarly, placing a sensor directly in the airflow of an exhaust or intake fan could influence the readings.

The objective is therefore to position the sensors where they can provide measurements that are as representative of the overall growing environment as possible.

Beyond the Sensors

The IoT system doesn't stop at collecting measurements.

The growing house also incorporates equipment such as:

- Intake and exhaust fans

- A heater

- A humidifier

- CCTV monitoring

These components provide the physical means of influencing or observing the growing environment.

The broader system can therefore be viewed as a feedback loop:

Environment → Sensors → Data → Analysis → Control → Environment

The sensors observe the environment, the system processes the information, and appropriate control actions can then be taken.

From Monitoring to Automation

This is where the project becomes particularly interesting from an engineering perspective.

A basic IoT system might simply tell a farmer:

«"The humidity is currently 82%."»

The system could use that information to determine whether an action is necessary.

For example, if a measured parameter moves outside a defined range, the control system could potentially activate or deactivate the appropriate equipment.

This is the transition from monitoring to automation.

When combined with data analysis and AI, the system can potentially go even further by identifying trends and predicting changes before they become significant problems.

Engineering in Practice

Designing this system has been a useful reminder that engineering decisions are interconnected.

Choosing a sensor affects the data that can be collected.

Sensor placement affects the quality of that data.

Data quality affects the reliability of the analysis.

And the analysis ultimately affects the decisions made by the control system.

A smart system is therefore only as strong as the weakest part of that chain.

Lessons learnt from the Project

Working on the IoT component has shown an opportunity to connect concepts from Electrical and Electronics Engineering, embedded systems, sensors, control and IoT with an agricultural application.

It has also shown that designing a real-world system involves much more iteration than simply drawing a block diagram.

There are questions about placement, reliability, communication, power, environmental conditions and how the system will actually be used by the end user.

That practical thinking is perhaps one of the most valuable parts of the experience.

What's Next?

The next step is to continue refining the design and move closer to implementing and testing the system in the actual growing environment.

The ultimate objective is to create an IoT system that can reliably monitor the mushroom house, provide useful information and work alongside intelligent analytics and automated controls.

It's still a work in progress, but seeing the system develop from an initial concept into a physical design has been one of the most rewarding parts of the project so far.

Good engineering isn't just about building technology. It's about building technology that makes sense for the problem you're trying to solve.

#IoT #EmbeddedSystems #SmartAgriculture #ElectricalEngineering #Agritech #Engineering