Data

In an increasingly digital world, data collection is growing at a rapid pace. Fulton Schools faculty and student researchers are devising innovative approaches and tools that will help us better process, analyze, use, manage and access data. New computational tools, algorithms and data analysis techniques, including hardware and software approaches, machine learning, data analytics, data-driven decision-making and more will help advance scientific discoveries and collaborations across multiple fields where data use and capture is ubiquitous.

Shreeya Gundamaraju, Sreekar Shodhan Manuka, Aditya Gundamaraju, Harjas Kaur Ratol, Ikjot Singh Arneja and Harshavardhan Kuthadi of Industry Team 4 in SER 517.

Industry Team 4

Monitoring battery health across devices can be inconsistent, especially when data collection and storage are unreliable. This project addresses that challenge by developing a system with Fetherstill that tracks battery performance using an ESP32 and a React Native mobile application. The system collects data on voltage, current, temperature and recharge cycles over Bluetooth and preserves…

Jeteish Pratap Singh, Smit Mahesh Panchal, Somesh Sushil Chinnawar, Abhijna Venkatesh Maiya, Rajvi Alpesh Patel and Darshan Phaldesai of Industry Team 2 in SER 517.

Industry Team 2

Building Information Models contain large volumes of electrical system data, but accessing that information often requires manual navigation and technical expertise. This project addresses that challenge by developing Auto BIM Route AI, an assistant integrated within Autodesk Revit. The tool enables users to query electrical layouts, identify panel loads and generate visualizations using natural language….

Ritu Kishor Malav, Sejal Khedekar, Swati Uttamrao Chaudhari, Ashish Sangale, Misha Kumari and Siya Singh of Industry Team 1 in SER 517.

Industry Team 1

Building Information Models contain detailed electrical system data, but accessing and using that information often requires manual navigation and technical expertise. This project addresses that challenge by developing Auto BIM Route AI, an assistant integrated within Autodesk Revit. The tool allows users to query electrical layouts, identify panel loads and generate visualizations using natural language….

Auto BIM Route Interaction Smoothing

In the Auto BIM Route application project, the team focused on making route interactions smoother and more intuitive. They enhanced the user interface for drawing preferred paths, refined the zoom functionality for consistent proportions and improved route selection by adding visual emphasis and enabling keyboard shortcuts for easier navigation. Additionally, the team assisted in developing…

Auto BIM Route Project Browser

Auto BIM Route has developed an advanced PCB auto-routing and optimization tool to automatically generate routed circuits on virtual PCB designs, reducing the time and effort needed for routing. However, the current application takes too long to generate and display the routed designs due to the resources required for rendering. This ASU Capstone team aims…

Improving Auto BIM Route Zoom Functionality

The project focuses on optimizing Auto BIM Route, a construction data visualization tool, by improving its zoom functionality, interaction speed and overall rendering performance. The challenges include an outdated rendering engine that lacks GPU acceleration, limiting performance when processing large DSN files, and the need for deep analysis of the codebase to address bottlenecks affecting…