The starting signal for this portfolio expansion was given by an internal project in the course of which, among other things, experiments were conducted with various wireless transmission technologies and the question of whether the power consumption of devices equipped with sensors can be significantly reduced by optimizing the electronics and firmware used. This is an important point for many device manufacturers, as smart devices such as smoke detectors or temperature sensors remain in use unchanged for up to ten years - and spend most of that time in sleep mode. The result of the study: electricity savings of up to 90 % are possible.

As part of the 'LeberLab IoT' project and under the guidance of an experienced STL project manager, working students Leon Angele (Nuremberg Institute of Technology Georg Simon Ohm) and Kevin Steffan (Friedrich-Alexander-Universität Erlangen) spent several months testing various industrial measurement and sensor applications and transmission technologies such as LoRaWAN and MIOTY as well as 5G communication. Among other things, the application and optimization possibilities of LoRa chips or transceiver modules were researched, which were connected to various sensors - for example for temperature or humidity measurement.

The connected microcontroller, which transmits the data measured by the sensors to the LoRa chip, which then forwards it wirelessly to a LoRa gateway and makes it readable on the connected Raspberry Pi industrial PC, was also scrutinized. The main focus of the investigations was the power consumption of the microcontroller: The research team wanted to prove that optimizing both the hardware and software of microcontrollers can result in significant power savings.

For the experiment, the power consumption of the microcontroller used in the project was measured using an external measuring device for currents up to a few nanoamperes. It quickly became clear that power consumption increases significantly with each transmission interval or during data transmission - and that significant power is also consumed during the long idle periods. The team then developed various optimization scenarios - including the parameterization or adjustment of the spreading factor for LoRa transmission: faster data transmission implied a shorter range and increased susceptibility to interference on the one hand, but also significantly lower energy consumption on the other. This was also achieved by optimizing the installed hardware. For example, the team removed unneeded voltage regulators and disconnected LEDs and other elements that were not relevant to the task. "A microprocessor like this covers a wide range of different functions," explain Leo Angele and Kevin Steffan. "To reduce its power consumption, we deactivated or disconnected from the board all those that are not required for reading out and transmitting data. We also made sure that the processor goes into a special deep sleep mode at times when it is not transferring data - and that it wakes up again correctly and without delay afterwards."

The students will be presenting the results of the LeberLab experiment at the Systemtechnik Leber trade fair stand at Embedded World (June 21-23, 2022).