LAS3R: A simple, secure, scalable, and robust framework fordeploying lab automation devices

Abstract

Laboratory automation can greatly accelerate experiments and data collection, yet building automated systems often requires substantial programming and electronics expertise, and few frameworks are targeted at deploying many devices. We present LAS3R, a low-cost, open-source framework that enables researchers with minimal technical expertise to rapidly prototype, deploy, remotely control, and collect data from multiple custom-built laboratory devices while maintaining strong security and reliability throughout the process--from early prototyping to routine operation. The system is built around a central hub to which multiple lab devices connect. This hub can be set up on a Raspberry Pi (a small, low-cost single-board computer) in under fifteen minutes. In the setup process, code is automatically generated for ESP32 microcontroller boards that control the hardware. Users can choose from a list of preconfigured ESP32 devices, for example a bioreactor, or use a template that provides base code for many common automation tasks, which they can then easily customise using the beginner-friendly Arduino platform. The ESP32 devices connect through a secure Wi-Fi network hosted by the Raspberry Pi that encrypts communication, and ensures only authorised hardware can join, helping safeguard experimental data and institutional networks, even while prototyping. We demonstrate the framework with two applications--a turbidostat bioreactor and a light-level controller--and show that it can simultaneously manage eight devices with 24 sensors. Robustness was evaluated through single-point-of-failure analysis, confirming continued operation during mains power or network interruptions. Comprehensive documentation, aimed at wet lab researchers, enables users to understand, build, and adapt the system, making it both a practical laboratory automation platform, including for those in low-resource settings, and a teaching resource. This paper is intended to be a technical evaluation of the architecture. Those wishing to deploy the system should refer to the online documentation at kavihshah.github.io/LAS3R.