Making snow monitoring smarter with IoT

ENERGY

As climate change accelerates, real-time insight into snow conditions and avalanche risk is becoming increasingly critical. In vulnerable winter environments, challenges range from protecting infrastructure to saving lives. To meet the growing need for reliable, rapid data, Knowit joined the Zygizo One project – an IoT-based initiative designed to monitor snow depth, predict avalanches, and assess flood risks in real time.

CHALLENGE

Automating snow monitoring in extreme conditions

Snow-heavy regions – including mountain passes, ski resorts, and urban areas – require automated data collection to manage risks effectively. Traditional methods are often manual, time-consuming, and prone to error. There was a clear need for a system that could:

Monitor snow conditions in real time using diverse sensor types
Analyze data locally and predict avalanches using AI
Track load on critical infrastructure such as bridges, buildings, and power lines
Operate reliably in harsh weather, with low power consumption and high stability

SOLUTION

Firmware development and smart communication in snowy terrain

Knowit contributed to the development of Zygizo One, an IoT-driven platform for intelligent snow monitoring and risk assessment in demanding environments. Our team handled both software and hardware components, with a focus on building a reliable, energy-efficient, and scalable system.

To enable accurate and continuous data collection, we developed firmware that integrates multiple environmental sensors – including temperature, humidity, snow depth and density, wind, and vibration sensors. This setup allows the system to gather high-quality data even in remote, weather-exposed locations – without compromising battery life or uptime.

The communication architecture was designed to function in areas with limited connectivity. We implemented low-power technologies like LTE-M and GNSS for real-time remote monitoring, and machine-to-machine (M2M) communication to enable autonomous sensor interaction. Thanks to edge computing, the system can analyze data locally and make rapid decisions without relying on a constant cloud connection.

Together with our hardware partners, we ensured seamless integration of the firmware with microcontroller units (MCUs), using protocols like SPI, I2C, and UART for sensor communication. Through extensive testing with logic analyzers and oscilloscopes, we fine-tuned performance and reliability – making Zygizo One a robust solution for snow monitoring in extremely demanding environments.

RESULT

Data-driven winter preparedness with AI and IoT

Zygizo One has proven to be a scalable and energy-efficient platform for real-time snow monitoring, purpose-built for extreme conditions. Users now gain access to reliable data from remote locations, with local AI-powered analysis of snow dynamics that enables avalanche prediction without requiring a constant internet connection.

The system reduces the need for manual measurements and significantly improves safety for both people and critical infrastructure. With verified performance in severe weather and minimal energy use, Zygizo One is a vital step forward in creating a smarter, more resilient approach to winter preparedness.

Jakub Kucz, Business Unit Director

Knowit.

How the solution contributes to Agenda 2030

Goal 9: Industry, innovation and infrastructure. Zygizo One demonstrates how IoT and edge technologies can be used to build resilient infrastructure in remote and climate-sensitive regions. The system is scalable, energy-efficient, and built to last – a sustainable investment in smart technology.

Goal 11: Sustainable cities and communities. By enabling early warning for avalanche risks and monitoring structural loads on infrastructure like bridges and power lines, Zygizo One enhances safety for communities and vital societal functions in high-risk areas.

Goal 13: Climate action. The system supports climate adaptation by delivering real-time data for informed risk management. Its use of local AI processing also reduces dependence on energy-intensive cloud services, helping to lower its climate footprint.