Compression using Discrete Multi-Level Divisor Transform for Heterogeneous Sensor Data

TL;DR

This paper introduces a novel discrete multi-level divisor transform (DMDT) for compressing diverse sensor data types, addressing the limitations of traditional methods in multi-sensor systems.

Contribution

The paper proposes a new universal transform-based compression algorithm suitable for various sensor signals, outperforming existing algorithms.

Findings

Effective compression across multiple sensor data types

Demonstrated superiority over state-of-the-art algorithms

Applicable to diverse real-world sensor systems

Abstract

In recent years, multiple sensor-based devices and systems have been deployed in smart agriculture, industrial automation, E-Health, etc. The diversity of sensor data types and the amount of data pose critical challenges for data transmission and storage. The conventional data compression methods are tuned for a data type, e.g., OGG for audio. Due to such limitations, traditional compression algorithms may not be suitable for a system with multiple sensors. In this paper, we present a novel transform named as discrete multi-level divisor transform (DMDT). A signal compression algorithm is proposed for one-dimensional signals using the DMDT. The universality of the proposed compression algorithm is demonstrated by considering various types of signals, such as audio, electrocardiogram, accelerometer, magnetometer, photoplethysmography, and gyroscope. The proposed DMDT-based signal compression algorithm is also compared with the state-of-the-art compression algorithms.