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Solar Graph on Viktor AI
In this portfolio project, the objective was to present an innovative and visually engaging solution by developing a web-based 3D interactive interface for calculating light transmission within an atrium or courtyard. The primary focus of the project is to propose and design an intuitive tool that provides users with a comprehensive understanding of light distribution. The interface incorporates advanced algorithms and utilizes Topologicpy.
Project Description
One of the key features of this interface is the provision of a dynamic and informative colored graph. The graph visually represents the brightness levels throughout the space, with vibrant yellow denoting areas of highest illumination and cooler blue indicating regions with lower light intensity. By leveraging this intuitive representation, users can effortlessly identify and analyze the brightest and darkest areas within the atrium or courtyard.
Model
Upon launching the application, users are greeted with a user-friendly prefix model that serves as an initial interface. The interface incorporates sliders powered by Viktor AI, offering a seamless and intuitive way to modify crucial elements such as the number of floors, length, breadth, and aperture of the building. With these interactive controls, users can effortlessly fine-tune and customize the architectural attributes of their virtual structure.
Why Web-based?
To ensure maximum accessibility and ease of use, our solution is designed to be web-based, allowing users to conveniently access and utilize the interface through their preferred web browsers. Additionally, the interface is compatible with Jupyter Notebook, providing users with the flexibility to run simulations and analyze data in a familiar and customizable coding environment.
By presenting this project in my portfolio, I aim to showcase my proficiency in designing and developing interactive web applications, as well as my expertise in utilizing innovative technologies to solve real-world challenges.
Data Visualization on PowerBi
Through my visualization dashboard, I aimed to address these, and several other key questions related to genres, artists, lyrics, tempo trends, and genre preferences over time. By providing visual representations and analytical tools, the dashboard makes it easy to answer and analyse these questions, enabling users to gain valuable insights from the dataset. This dashboard aims to provide valuable insights into the music industry by visualizing key metrics and trends. By evaluating the dashboard's design, functionality, and the insights it delivers, I will demonstrate how it successfully enhances data exploration and decision-making
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Why Power Bi?
Through this data visualisation dashboard, I have assessed the effectiveness of the Power BI dashboard to analyse the Spotify dataset, which contains audio statistics of the top 2000 tracks on Spotify. Spanning from 1956 to 2019, the dataset includes notable artists such as Queen, The Beatles, and Guns N' Roses. It offers a fascinating opportunity to explore the factors that contribute to a song's success in the Top 2000. The individual who abstracted the Spotify dataset had specific questions in mind that they hoped to answer through the dataset.
The Questions Addressed through the Visualizations
1. Which genres were more popular from the 1950s to the 2000s?
2. What genres of songs mostly landed in the Top 2000?
3. Which artists were more likely to have a top-charting song?
4. How does the average tempo of songs compare over the years?
5. Was there a trend of acoustic songs being more popular in the 1960s compared to the present day?
6. Are there any noticeable trends in genre preferences between different periods?
Grasshopper Experimentation
The project Aim is to Programmatically optimise 3D designs according to the fabrication tools and materials using the Laplacian Mesh Smoothing Method.
