Agriculture is increasingly becoming a field where technology can make a measurable difference. From monitoring environmental conditions to using data to make better decisions, technologies such as the Internet of Things (IoT) and Artificial Intelligence (AI) are opening new possibilities for farmers.

Recently, I had the opportunity to be part of a project exploring this intersection through BRIDGE-AI: Smart Mushroom.

The project brings together IoT, Artificial Intelligence, predictive analytics and agriculture to develop a smarter approach to mushroom cultivation.

Why Mushroom Farming?

Mushroom cultivation is highly dependent on environmental conditions.

Factors such as temperature, humidity and carbon dioxide (CO₂) concentration can significantly influence the growing environment. Maintaining suitable conditions manually can be challenging, particularly for smallholder farmers.

This creates an opportunity for technology to assist with monitoring and decision-making.

Instead of relying entirely on periodic manual measurements, a smart farming system can continuously collect environmental data and make that information available to the farmer.

The Idea Behind the Smart Mushroom Farm

The concept behind the project is relatively straightforward:

Sense → Collect → Analyse → Respond.

Sensors installed within the mushroom growing environment collect information about the conditions inside the room.

That information can then be transmitted to a monitoring system where it can be visualised and analysed.

With the addition of AI and predictive analytics, the system can potentially identify patterns and anomalies in the collected data and provide useful insights to the farmer.

The system is also designed with practical accessibility in mind, including remote monitoring and localised alerts.

The IoT Component

My contribution to the project has been focused on the IoT side of the system.

The IoT layer provides the connection between the physical mushroom-growing environment and the digital monitoring platform.

Among the environmental parameters being considered are:

- Temperature

- Relative humidity

- CO₂ concentration

- Light intensity

Different sensors are used to measure these parameters, including DHT22 sensors for temperature and humidity, an SCD30 sensor for CO₂, and a BH1750 sensor for light intensity.

The collected measurements form the foundation on which the rest of the smart system can operate.

More Than Just Monitoring

One of the things I find most interesting about this project is that the goal isn't simply to display sensor readings. Monitoring is only the first step. Once reliable data is available, it can be used to understand the behaviour of the growing environment and support better decisions. For example, if humidity begins moving outside the desired range, the system could identify the change and trigger an appropriate response through the relevant control equipment. This creates the possibility of moving from passive monitoring to intelligent environmental control.

Bringing Different Fields Together

Working on this project has also shown me how interconnected different engineering and technology disciplines can be.

An agricultural problem can require knowledge from:

Electrical Engineering → Sensors → Embedded Systems → IoT → Data Analysis → AI → Automation

None of these areas exists completely in isolation.

The challenge is bringing them together into a system that actually works in the real world.

What I'm Learning

One of my biggest takeaways so far is that engineering isn't only about designing individual components. It's about understanding how those components interact as a complete system. A sensor can be accurate, but if it is positioned incorrectly, the data may not represent the environment accurately. A monitoring platform can look impressive, but if the underlying data is unreliable, the system becomes much less useful.

This project has therefore been an opportunity to apply concepts I've encountered through Electrical and Electronics Engineering to a practical agricultural problem.

Looking Ahead

The Smart Mushroom project is still a learning journey, and there is much more to develop, test and refine.

What excites me most is the possibility of seeing the complete system operate as one: sensors collecting real-world information, IoT infrastructure transmitting it, analytics interpreting it, and intelligent systems helping farmers make better decisions.

Technology becomes much more meaningful when it can move beyond the laboratory and solve problems that affect people's everyday lives.

For me, this project is an opportunity to explore exactly that.

From sensors to data, and from data to decisions, this is what smart agriculture can look like.

#IoT #SmartAgriculture #ArtificialIntelligence #Agritech #ElectricalEngineering