Smart Material Meter: An Open-Source, Modular Experimentation Platform

The Smart Material Meter aims to contribute to the growing initiatives towards open science by proposing an affordable, open-source platform for scientific experimentation, in particular laborato-ry automation and data evaluation. Existing general purpose computational lab workbenches typi-cally are designed around high-end laboratory equipment. In contrast, our approach targets ex-perimentation with custom-built lab gear that is based on affordable components and open-source hardware. In particular, our platform extends the well-established Grove system, a modular proto-typing system that takes a building block approach to electronic assemblies. Matching this ap-proach with our similarly modular software platform allows to quickly sketch systems that can be adapted and extended to suffice the needs of different materials and experiment conditions. Addi-tional software modules support efficient data acquisition and experiment automation. The Smart Material Meter platform is implemented in Python. This allows to make use of the vast set of avail-able frameworks and libraries for, e.g., computer vision or machine learning, to automate data annotation and analysis.
The example case presented in this poster is a weathering chamber that fits on a researcher’s desk and can be built on a budget of less than 500 euros, using common electronics and person-al fabrication tools - and basic circuitry knowledge. Scientists, makers, and enthusiasts alike can use the weathering module through a simple block-based interface. Users only need to define how the sensors and actuators should operate and add the corresponding automation parame-ters. For example, monitoring a shape-changing material that reacts to moisture would require setting time intervals, levels of humidity, etc. Furthermore, the existing library of modules can be extended by expert users to add new sensors or actuators to fit the needs of a particular experi-ment. Overall, the goal of this tool is to provide an initial working concept that can be re-used an expanded by a growing number of professional and amateur users interested in performing af-fordable, quick, yet reliable scientific experiments.