Development of a Lossless Data Compression Algorithm for Multichannel Environmental Monitoring Systems

Data compression in environmental monitoring systems is indispensable, to save the power of the monitoring nodes and reduce the size of system database as well as increasing the efficiency of data throughput. In this article, a new lossless compression algorithm has been proposed based on combining of three famous compression methods which are: Delta encoding, Run-length encoding and Huffman encoding. The main advantage of the proposed algorithm is its simplicity, which makes it suitable for systems with very limited resources. The proposed algorithm has been applied to measured samples extracted from a research monitoring system. The results indicated that the compression ratio of the initial data by the proposed algorithm reaches 90%, which leads to a significant preservation of the storage space for the system.