In order to maximize the operational time of battery powered wireless sensors or minimize the size of a harvester in case of an ambient powered wireless sensor it is important to minimize the power consumption of all components in the system. The energy required for data transmission substantially contributes to the total power consumption of a device. However, is is quite common that the information content in the data is limited, e.g. when the quantity of interest is fairly constant for most of the time. In this paper we present a loss-less data compression approach with low computational complexity. It is based on the idea of Huffman encoding and utilizes the fact that the relative frequency of small differences between subsequent samples is often dramatically higher than the relative frequency of larger differences. Additionally, we suggest an extension for the transmission of dynamically changing sensor samples to the ISO/IEC/IEEE 21451 Standard. In an application example we demonstrate a data rate reduction of about 62.5% for a wireless temperature sensor used in an automotive test bench.
|Name||2019 IEEE International Conference on Industrial Cyber Physical Systems (ICPS)|
|Konferenz||2019 IEEE International Conference on Industrial Cyber Physical Systems (ICPS)|
|Zeitraum||6/05/19 → 9/05/19|