An Automated and Centralized Data Generation and Acquisition System

Abstract

Data Generation and Acquisition (DGA) has become a major requirement for data processing and subsequent information analysis, especially in data science, big data, and pattern recognition (which is a cornerstone of machine learning techniques). A synchronized hybrid data generation and acquisition system has major advantages over traditional counterparts given the mixed-mode nature of its input signals (digital and analog) being aligned with its output signals. The proposed DGA system, in addition to being hybrid and synchronous, is a single-board programmable, compact and fully automated open-source hardware/software instrumentation device. This paper details the design methodology, the hardware/software interface, the end-usage and the possible applications of the device. When high accuracy and consistent fidelity are key features of a specific pattern generation/acquisition system, bulky and expensive interconnected instruments become the main hiccup. The system we are presenting does not compromise between compactness, centralization and portability on one side and flexibility, accessibility and efficiency on the other side.