// PROJECT SUMMARY
BeeConn is a smart beehive-monitoring platform developed by Slovenian company Strip's. The existing ecosystem allows beekeepers to remotely monitor their hives using connected sensors and gateways.
JPM Systems developed a new solar-powered IoT sensing system that listens to the sounds inside a beehive and uses acoustic analysis to detect signs associated with swarming.
The first application focuses on recognizing characteristic queen signals and notifying the beekeeper early enough to take action before part of the colony leaves the hive.
// THE PROBLEM
Swarming is a natural process in which a honeybee colony divides and a large part of the colony leaves the existing hive.
For a beekeeper, missing this event can mean losing a significant part of a productive colony.
The challenge is that the beekeeper cannot continuously inspect every hive, particularly when multiple hives are distributed across remote locations.
However, the bees themselves provide information about what is happening inside the colony.
During the swarming process, virgin queens can produce characteristic signals known as queen piping. An emerged virgin queen typically produces tooting, while queens still inside capped queen cells can respond with quacking.
If these acoustic patterns can be detected automatically, they can provide an early indication that the beekeeper should inspect the hive.
// THE SOLUTION
We developed a connected acoustic monitoring system for beehives consisting of an in-hive sensor and an external communication gateway.
The sensor includes a microphone that continuously listens to the acoustic environment inside the hive, together with temperature and humidity sensing for additional environmental information.
The system analyzes the captured signals and looks for characteristic patterns associated with queen activity and the swarming process.
When relevant activity is detected, the information is transmitted through the BeeConn infrastructure and the beekeeper can be notified remotely.
The complete system was designed for autonomous outdoor operation and includes solar power, battery management and wireless communication, allowing it to operate at remote apiary locations without access to mains electricity.
// OUR WORK
JPM Systems was responsible for:
- – IoT system architecture
- – Custom electronics development
- – PCB design
- – Acoustic sensor integration
- – Microphone integration
- – Temperature and humidity sensing
- – Audio signal acquisition
- – Acoustic signal analysis
- – Embedded systems development
- – Firmware development
- – Swarming detection algorithms
- – Wireless communication
- – Sensor-to-gateway communication
- – Gateway development
- – Solar power integration
- – Battery management
- – Low-power electronics development
- – Integration with the BeeConn ecosystem
- – Prototype development
- – Testing and validation
// KEY CHALLENGES
Listening to Bees
The most important sensor in the system is not a conventional environmental sensor. It is a microphone.
The challenge was to capture useful acoustic information from a living beehive and distinguish characteristic signals from the complex background noise generated by thousands of bees.
This required combining electronics, acoustic sensing, signal processing and embedded software.
Detecting Queen Piping
The system isn't simply recording audio.
It needs to identify specific acoustic patterns that indicate something meaningful is happening inside the colony.
Queen piping — including tooting and quacking — provides one such signal.
The engineering challenge was therefore to transform an acoustic biological phenomenon into something that could be measured, analyzed and automatically classified by an embedded system.
From Detection to Action
Detecting an interesting sound has little value if the beekeeper doesn't know about it.
The sensor therefore had to become part of a complete IoT chain: beehive → sensor → signal analysis → gateway → cloud → notification → beekeeper.
The objective was not simply to collect more data about bees, but to turn that data into actionable information.
Autonomous Operation in the Field
Beehives are often located where there is no convenient electrical connection.
The complete system therefore had to operate autonomously using solar energy and battery storage.
Power consumption became an important part of the architecture because sensing, processing and wireless communication all consume energy. The electronics and firmware had to balance continuous monitoring, computational requirements, communication and available solar power.
A Platform for Understanding the Hive Through Sound
Swarming detection is the first targeted application, but the acoustic environment inside a hive contains significantly more information.
Once the hardware platform can reliably capture and process hive sounds, the same architecture creates opportunities for detecting other acoustic patterns associated with colony behavior and potentially its condition.
The project therefore establishes a foundation for expanding from connected hive monitoring toward acoustic analysis of hive behavior.
// THE RESULT
The project extends the BeeConn ecosystem with a new source of information: sound from inside the beehive.
By combining microphone-based sensing, environmental sensors, embedded processing, wireless communication and solar-powered operation, the system can automatically monitor remote hives and identify acoustic patterns associated with the swarming process.
Instead of requiring the beekeeper to continuously inspect every hive, the technology allows the hive itself to indicate when attention may be required.
The project demonstrates how IoT product development, custom electronics and signal processing can transform a biological signal into actionable information — connecting something as subtle as the sound of a queen bee to a notification on a beekeeper's phone.