arxiv: 2605.10454 · v1 · submitted 2026-05-11 · 💻 cs.CE

Recognition: no theorem link

A Flexible Raspberry Pi-Based Data Logger Platform for Modbus Sensors with Ansible Deployment

Leon Keim , Steffen H\"agele , Vivien Langhans , Holger Class

Authors on Pith no claims yet

Pith reviewed 2026-05-12 04:35 UTC · model grok-4.3

classification 💻 cs.CE

keywords Raspberry Pidata loggerModbusenvironmental monitoringAnsibleopen sourceCO2radon

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The pith

A Raspberry Pi platform lets users deploy custom Modbus sensor networks for monitoring by editing one YAML file and has proven reliable in continuous field use.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

This paper presents an open-source system for logging data from environmental sensors connected via Modbus over RS-485 using a Raspberry Pi. The platform includes minimal and more capable hardware setups, a library for sensor interaction, and automation scripts that set up the entire system from a single configuration file. It supports sensors like those for CO2 and radon, logs data to CSV files, and the authors report it has been collecting data continuously in a karst environment since spring 2025 without interruption. A sympathetic reader would care because this offers a low-cost, reusable way to build monitoring stations for research, with costs around 60 euros and easy addition of new sensors. If true, it means researchers can focus on science rather than building custom loggers from scratch each time.

Core claim

The central claim is that LibrePiLogger provides a complete, flexible platform for Modbus-based environmental data logging on Raspberry Pi hardware, with Ansible-based deployment that reduces setup to editing one YAML inventory file, and that this system has demonstrated reliable long-term operation in real-world continuous monitoring of CO2 and radon levels.

What carries the argument

The key mechanism is the combination of Raspberry Pi hardware with RS-485 interfaces, a Python-based sensor communication library that uses a driver template, and Ansible automation scripts, which together allow rapid deployment and data logging to timestamped CSV files with metadata.

If this is right

Adding support for a new sensor requires only about 100 lines of Python code following the provided template.
Hardware costs stay between 54 and 63 euros depending on the configuration chosen.
The system produces timestamped CSV data files accompanied by JSON metadata for easy analysis.
All designs, code, and scripts are freely available under the GNU General Public License version 3.
The platform supports ongoing environmental monitoring projects with minimal ongoing intervention.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

Such automated deployment could enable rapid scaling of sensor networks across multiple sites with consistent configurations.
The open-source release may encourage adaptations for other communication protocols or sensor types not yet implemented.
Long-term reliability in harsh environments like karst areas suggests potential for use in similar remote or challenging field conditions.
Integration with existing data analysis tools could be straightforward given the standard CSV and JSON output formats.

Load-bearing premise

The load-bearing premise is that the hardware setups, sensor drivers, and deployment scripts will function without significant issues over extended periods, even though only a high-level summary of the deployment is given without error logs or maintenance details.

What would settle it

Collecting and publishing detailed system logs showing uptime percentages, any downtime events, sensor communication errors, or data gaps from the spring 2025 deployment onward would either support or contradict the claim of reliable long-term performance.

Figures

Figures reproduced from arXiv: 2605.10454 by Holger Class, Leon Keim, Steffen H\"agele, Vivien Langhans.

**Figure 2.** Figure 2: LibrePiLogger setup described in this article [PITH_FULL_IMAGE:figures/full_fig_p011_2.png] view at source ↗

**Figure 3.** Figure 3: Legacy setup using commercial data loggers [PITH_FULL_IMAGE:figures/full_fig_p011_3.png] view at source ↗

read the original abstract

This article presents LibrePiLogger, an open-source data logging platform based on the Raspberry Pi for environmental monitoring using Modbus sensors over RS-485. The system combines the AtmosPyre Python library for sensor communication with Ansible-based deployment automation, allowing researchers to deploy sensor networks by editing a single YAML inventory file. Two hardware configurations are described: a minimal setup using a Raspberry Pi Zero with an RS-485 HAT, and a maximal setup using a Raspberry Pi 4 with a USB-to-RS-485 converter. Currently implemented sensors include the Vaisala GMP252 for CO$_2$ and the RadonTech AlphaTRACER for $^{222}$Rn, with new sensors requiring approximately 100 lines of Python following a provided driver template. Data is logged to timestamped CSV files with JSON metadata. The system has been deployed for continuous CO$_2$ and $^{222}$Rn monitoring in a karst environment since spring 2025 and remains in active operation, demonstrating reliable long-term performance. All hardware designs, software, and deployment scripts are released under the GNU General Public License v3.0. Total hardware costs range from 54 to 63EUR (excluding housing), depending on the configuration.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Desk Editor's Note private letter to a colleague

Practical open-source Raspberry Pi logger for Modbus sensors with easy Ansible deployment, but the long-term reliability claim is asserted without metrics.

read the letter

Hi colleague, The main point is that this is a straightforward engineering paper delivering an open-source Raspberry Pi platform for logging data from Modbus sensors, automated with Ansible. They integrate the AtmosPyre library for sensor comms, provide minimal and maximal hardware setups, and reduce deployment to editing a YAML inventory file. New sensors need about 100 lines following their template. Data logs to CSV with JSON metadata. The whole thing, including hardware designs, is released under GPL v3 at low cost. It does well by focusing on real usability for field researchers. The system has been collecting CO2 and radon data in a karst site since spring 2025, which shows it can run without constant tinkering. The soft spot is the reliability evidence. They state it demonstrates reliable long-term performance, yet no uptime stats, data gap info, or error logs appear in the description. Without those, the claim stays at the level of assertion even though the code is public. This paper suits environmental scientists and engineers building sensor networks who want a ready template rather than starting from scratch. Readers in applied monitoring would get immediate value from the released configs and scripts. It shows solid, practical thinking with complete artifact release, so it deserves a serious referee. I recommend sending it to peer review, but ask the authors to include some quantitative deployment results to support the performance claims.

Referee Report

1 major / 2 minor

Summary. The paper presents LibrePiLogger, an open-source Raspberry Pi-based data logging platform for Modbus sensors over RS-485. It describes two hardware configurations (Raspberry Pi Zero with RS-485 HAT and Raspberry Pi 4 with USB-to-RS-485 converter), the AtmosPyre Python library for sensor communication, Ansible-based deployment via a single YAML inventory file, support for sensors including Vaisala GMP252 (CO₂) and RadonTech AlphaTRACER (²²²Rn), and logging to timestamped CSV files with JSON metadata. New sensors require approximately 100 lines of Python code following a provided template. The system is reported to have been deployed for continuous CO₂ and ²²²Rn monitoring in a karst environment since spring 2025 and remains operational, with all hardware designs, software, and scripts released under GPL v3.0 at a hardware cost of 54–63 EUR.

Significance. If the deployment claims hold, this work delivers a practical, low-cost, and extensible platform that lowers barriers for researchers conducting long-term environmental monitoring with Modbus-compatible sensors. The Ansible automation and open-source release under GPL v3.0 enable straightforward replication and community extension, while the dual hardware options accommodate different field constraints. This addresses a real need in geosciences and ecology for flexible data acquisition systems beyond commercial offerings.

major comments (1)

[Abstract] Abstract (final sentence): The claim that the deployment 'demonstrates reliable long-term performance' since spring 2025 rests on a high-level summary of components and operation without any quantitative metrics such as uptime, data completeness rates, error counts, gap statistics, or maintenance logs. This is load-bearing for the central demonstration of reliability, as operational success cannot be verified from code and architecture descriptions alone.

minor comments (2)

[Hardware Configurations] The manuscript would benefit from a brief table or bullet list explicitly comparing the minimal and maximal hardware configurations (e.g., cost, power draw, I/O expandability) to improve readability.
[Software Architecture] Consider including a short code excerpt or pseudocode for the sensor driver template to illustrate the ~100-line addition process for new sensors.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for the positive summary and recommendation of minor revision. We address the single major comment below.

read point-by-point responses

Referee: [Abstract] Abstract (final sentence): The claim that the deployment 'demonstrates reliable long-term performance' since spring 2025 rests on a high-level summary of components and operation without any quantitative metrics such as uptime, data completeness rates, error counts, gap statistics, or maintenance logs. This is load-bearing for the central demonstration of reliability, as operational success cannot be verified from code and architecture descriptions alone.

Authors: We agree that the abstract's phrasing 'demonstrating reliable long-term performance' is not supported by quantitative metrics, which are absent from the manuscript. The paper's focus is the platform architecture, Ansible deployment, and sensor integration rather than a performance evaluation study. The deployment statement is intended only to indicate that the system has been running continuously since spring 2025 and is still operational. We will revise the abstract's final sentence to read: 'The system has been deployed for continuous CO₂ and ²²²Rn monitoring in a karst environment since spring 2025 and remains in active operation.' This removes the unsupported claim while preserving the factual deployment context. No additional quantitative data will be added, as none were collected for the purpose of this platform-description paper. revision: yes

Circularity Check

0 steps flagged

No circularity: purely descriptive implementation paper with no derivations or fitted predictions

full rationale

The paper is a technical description of an open-source Raspberry Pi data logger using Modbus sensors, Ansible deployment, and released source code. It contains no equations, no derivations, no predictions of any kind, and no self-citations that could form a load-bearing chain. The deployment claim since spring 2025 is presented as an empirical fact supported by the released implementation rather than any self-referential reduction. This matches the default case of a self-contained descriptive account with external benchmarks (actual field operation and open-source release).

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

This is a system-description paper with no mathematical derivations, fitted parameters, or postulated scientific entities. The contribution is the integration and public release of existing open-source components and hardware.

pith-pipeline@v0.9.0 · 5522 in / 1186 out tokens · 49307 ms · 2026-05-12T04:35:32.645559+00:00 · methodology

discussion (0)

Reference graph

Works this paper leans on

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