Pmeas

Pmeas is a modular software framework for quantitative measurement and analysis of data streams. It provides a unified approach to collect, calibrate, and analyze measurements from laboratory instruments, field sensors, and simulation outputs. The design emphasizes reproducibility, configurability, and interoperability across hardware and software platforms.

Origin and development: The concept emerged in the early 2010s from researchers at the Northbridge Institute of Technology and was released publicly in 2013 as an open-source project. Subsequent major versions introduced pipeline-based processing, enhanced calibration, and cloud-native exporters. The project is maintained by a lightweight community consortium with corporate sponsorship.

Architecture: The core is a time-stamped data model and a pipeline engine. Measurements pass through configurable stages such as filtering, transformation, and calibration. Adapters connect to instruments and data sources, while exporters output formats including JSON, CSV, and time-series backends. Configuration is via YAML or JSON and supports plug-ins.

Features: Real-time streaming and batch processing, modular processing pipelines, calibration and uncertainty estimation, provenance tracking, and robust documentation. The design aims for cross-platform compatibility and minimal runtime dependencies.

Applications and reception: Pmeas is used in academic laboratories, industrial measurement, and environmental monitoring. It is noted for reproducible workflows and interoperability, with adoption varying by sector.

See also: data acquisition, time-series analysis, calibration, open-source software.