BioShield AI-Py

Authors

  • Daiana Magalí Acosta Romero Faculta Regional Delta, Argentina
  • Enzo Nicolás Vargas Faculta Regional Delta, Argentina

DOI:

https://doi.org/10.18687/LACCEI2026.1.1.2635

Keywords:

Immutable Blockchain, Environmental Traceability, Optimized Audit, Green Engineering, Containers (Docker).

Abstract

The BioShield-AI project is a cutting-edge platform designed for the critical management of biosecurity and environmental traceability in real time. Its main goal is to offer a robust technological solution that ensures data integrity in biological risk scenarios, integrating advanced concepts of software engineering, cryptography, and sustainability. At the heart of the system lies an immutable Blockchain engine. BioShield-AI uses a chain-of-blocks structure through the SHA-256 algorithm, ensuring that any attempt to alter sensor data is immediately detected. This allows the integrity of the entire chain to be verified instantly, regardless of whether there are hundreds or thousands of records, guaranteeing an immediate response to incidents.The project features a Tactical Dashboard developed in Streamlit, which functions as a command center for researchers and managers. Through this panel, heat maps and scatter plots of simulated pathogens are displayed. The system incorporates a dynamic risk traffic light powered by artificial intelligence logic, which classifies threats into levels (Low, Moderate, High, and Critical), facilitating data-driven decision making. Under the principle of Green Engineering, the software includes a resource monitor that measures CPU, RAM consumption, and the carbon footprint of computational processes. Additionally, the project has been containerized using Docker, ensuring its adaptability and portability. Texto original Valora esta traducción Tu opinión servirá para ayudar a mejorar el Traductor de Google

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Published

2026-07-27

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

LACCEI retains copyright of all published articles under the terms of its copyright transfer agreement. As the copyright holder, LACCEI distributes the articles to the public under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0).

How to Cite

Acosta Romero, D. M., & Vargas, E. N. (2026). BioShield AI-Py. LACCEI, 1(14). https://doi.org/10.18687/LACCEI2026.1.1.2635

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