The main components of a swarm cube


Four young researchers develop a system for monitoring wide areas of land

The news has been full of dramatic footage recently – forest fires, completely out of control, wreaking havoc on natural habitats and endangering people, wildlife, and the environment by churning out huge volumes of carbon monoxide and dioxide. Four young researchers have now set themselves an ambitious goal as part of a project called Swarm Cubes. Their aim: to develop an early warning system that will prevent forest fires spreading to large areas. In the meantime, the IoT initiative has taken the project far beyond the original realms of forest fire diagnostics such that it now offers features that could be useful for the smart cities of the future.

David Kern, Annely Felicitas Böbel, Valentin Paulweber, and Akhil Hoque from Reutlingen – four ambitious researchers working on a common goal. For the last year, they have been conducting research at the high school student research center in the small Baden-Wuerttemberg city of Eningen. They recently won the youth research initiative Jugend Forscht, competed for the Artur Fischer inventors’ prize, and have appeared at the iENA inventors’ show in Nuremberg.

The most effective early warning system for forest fires is currently based on identifying smoke visually. One major disadvantage of this is that systems issue notifications for any kind of smoke-like pattern, such as chimney smoke or dust caused by harvesting, so as such, it is not entirely reliable for spotting forest fires. It is also not suited to identifying underground fires. The researchers from Reutlingen have taken an alternative approach to analyzing information. Their system comprises a mesh-like network of WiFi chips (so-called cubes) which transmit live information such as relative humidity, ground moisture, absolute temperature, and concentrations of different gases. This removes any dependence on having to detect smoke, not only making it possible to identify forest fires, but to a certain extent also allowing forecasts to be made. To enable the system to work on rechargeable batteries, Kern and his co-researchers are currently writing an algorithm that allows WiFi junctions to transmit information at coordinated intervals. This algorithm should ensure that the network recharges itself and uses energy efficiently. By combining this technology with different types of sensors, large areas can be analyzed in a user-friendly manner. The team is also designing a circuit board and housing to adapt the technology to different conditions.


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To make the innovative product interesting in financial terms, the Swarm Cubes use an ESP8266EX chip, a 32-bit processor core microcontroller with an SPI, and a wireless LAN interface. To ensure batteries and solar panels are as compact as possible, the researchers are setting up the network without routing tables and at certain intervals it will be put it into a deep sleep for variable periods. In sleep mode, energy consumption is in the microampere range, significantly reducing energy requirements. To ensure units do not self-ignite, the electricity supply will be fitted with safety features and mounted in a special housing.

Using an IoT network also makes it possible to offer some interesting ideas for smart cities. As miniature autonomous devices, Swarm Cubes establish a network using radio frequencies and pass on information. Such a technology could be used for monitoring public trash cans in order to plan more efficient waste management, for smart watering of public parks, for measuring particulate matter, or for measuring temperatures in specific places. This would allow municipal authorities to optimize their services, enhance efficiency, and use energy more efficiently.

The project has received strong support from public sector facilities, universities and the business sector, but managing a project of this magnitude requires significant resources. The researchers are therefore looking for further financial backing for materials, tools, circuit boards, electrical components, rechargeable batteries, and 3D printers. It’s an undertaking that will undoubtedly be worth it for the four ambitious young researchers!


Interested in finding out more about the project?

If you’re interested in hearing more about the research or supporting the young team of researchers, feel free to get in touch with them directly!


David Kern (author)
Friedrich List High School (Reutlingen)

Valentin Paulweber
Friedrich List High School (Reutlingen)

Annely Felicitas Böbel
Friedrich List High School (Reutlingen)

Akhil Hoque
Friedrich List High School (Reutlingen)