Daniel Avella Ordonez
Computer Systems Engineer
© 2026 All rights reserved.
Engineering Signal Analytics Dashboard
- DescriptionThe project demonstrates cybersecurity as a fundamental element of modern engineering, especially in energy and infrastructure systems. It underscores the importance of proactive security design and response, with lessons applicable to systems, electrical, and energy engineering roles.
- RoleIn this project, I independently served as the systems and electrical engineering developer, responsible for the full design, implementation, and deployment of the dashboard. I developed the data ingestion and preprocessing workflow, implemented statistical analysis techniques such as mean and standard deviation calculations, and applied engineering‑standard anomaly detection logic based on μ ± kσ thresholds. I designed an interactive user interface using Streamlit that allows real‑time signal selection, sensitivity adjustment, and time‑window analysis, and created dynamic, high‑resolution visualizations with Plotly to effectively communicate system behavior and detected anomalies. In addition, I implemented robust CSV validation and upload handling, managed application state, and deployed the project as a publicly accessible application using Streamlit Cloud, integrated with a personal portfolio website.
- ImpactThe Engineering Signal Analytics Dashboard demonstrates a strong connection between core electrical engineering theory and practical, software‑driven system monitoring solutions. By translating statistical signal analysis concepts into an interactive, real‑time visualization tool, the project showcases applied skills relevant to power systems monitoring, renewable energy analytics, and industrial control environments. The dashboard highlights proficiency in data‑driven engineering analysis, fault detection methods, and technical visualization, while also reflecting best practices in software design and deployment. As a portfolio project, it provides a clear example of how engineering principles can be transformed into scalable, user‑focused analytical tools, establishing a solid foundation for future extensions such as advanced fault classification, real‑time sensor integration, or frequency stability analysis.
Description
Personal
March 2026
An interactive engineering dashboard for real‑time analysis of voltage and frequency signals, featuring anomaly detection, statistical metrics, and dynamic visualization using Python and Streamlit.