Campus Navigation & Accessibility Service

SmartHub is at the forefront of revolutionizing indoor navigation and mapping solutions. With a commitment to innovation and excellence, SmartHub's cutting-edge technology offers precise and accessible indoor mapping services. This project's vision is to redefine indoor navigation, making it as intuitive and seamless as outdoor GPS navigation.

Client's Objectives

  • Enhance Indoor Navigation: Utilize advanced mapping technologies to provide accurate and user-friendly indoor navigation solutions.
  • Improve User Experience: Deliver a seamless and intuitive user interface that enhances the overall experience of finding locations indoors.
  • Increase Accessibility: Ensure that our indoor mapping solutions are accessible to a diverse range of users, including those with disabilities.


Admin Panel for Integrating and Comparing Complex CAD Files

The primary challenge in the SmartHub project was developing a comprehensive admin panel for SmartNe users. This panel needed to enable users to upload CAD files of university buildings and campuses and compare these with detailed schemes from the ArcGIS system. The task demanded a sophisticated solution capable of synchronizing, storing, and comparing large datasets of spatial information. Given the complexity of integrating disparate CAD files and the lack of an initial design for the admin panel, the project required a highly collaborative approach with the client to outline key functionalities and ensure the system's usability and effectiveness.

Processing Large-Scale CAD Files

The team encountered a substantial challenge in processing extensive CAD files, rich with detailed architectural information and complex geometries. The dense packing of data made it difficult to extract specific elements, such as doors and rooms IDs, efficiently.

Mobile Application Development and Testing

The project scope expanded to include the testing and validation of an existing mobile application linked to various universities. The task involved identifying and rectifying bugs in the current application. Furthermore, the client requested the development of a new application, necessitating research into using MongoDB as a local database and its integration into the project.


Converting AutoCAD Plans to Geospatially Accurate Maps

The transformation of AutoCAD building plans, into geospatially accurate map formats, presented a substantial challenge that development teams successfully navigated. A critical part of the solution involved creating processable building map data through data analysis and algorithms. The team faced the challenge of working with large CAD files that contained no explicit information about the entities they included, such as rooms, doors, and corridors. To address this, custom code was developed and implemented to identify these entities. This innovative approach enabled the automated discovery and cataloging of architectural elements within the CAD files. By analyzing the data and applying custom algorithms, the team was able to extract, classify, and save the relevant information, transforming it into a structured format suitable for geospatial applications.

Converting AutoCAD Plans to Geospatially Accurate Maps

Collaborative Wireframing

Without a predetermined design, the team engaged in a collaborative process with the client to create wireframes for the admin panel. This foundational step was crucial for visualizing the solution's key functionalities and ensuring that the final product would be both intuitive and efficient for end-users. By involving the client in the wireframe process, the team could align the project's direction with the client's vision and requirements, ensuring a product tailored to the client's needs.

Collaborative Wireframing

Agile Methodology for Iterative Feedback and Improvement

To address these challenges, the team employed an agile development methodology, breaking down the project into sprints. This approach allowed for rapid prototyping and continuous client feedback, ensuring that each iteration of the admin panel was closer to meeting the project's ambitious goals. Agile sprints facilitated a flexible development process, enabling the team to adapt to challenges and incorporate new insights and feedback efficiently.

Agile Methodology for Iterative Feedback and Improvement

Enhancing Efficiency in Processing Large-Scale CAD Files

To address this challenge, the development team embarked on a multi-pronged strategy to enhance the script's performance and efficiency. Recognizing the need for a robust solution capable of handling the files' complexity and size, the team implemented the following solutions


Algorithm Optimization
Algorithm Optimization
At the core of the solution was the refinement of the script's algorithms. The team analyzed the script's processing flow and identified bottlenecks that slowed down the analysis. By redesigning these algorithms to be more efficient, the script could process the complex geometries within the CAD files more swiftly, reducing overall processing time.
Parallel Processing
Parallel Processing
To leverage the computational power available, the script was modified to support parallel processing. This allowed the script to handle multiple parts of the file simultaneously, significantly speeding up the identification of doors and rooms IDs by distributing the workload across multiple processors.
Memory Management Techniques
Memory Management Techniques
The processing of large files demands substantial memory resources. The team implemented advanced memory management techniques to optimize the script's memory usage. By doing so, they ensured that the script could handle large files without exceeding memory limits, thus preventing crashes and ensuring stable performance throughout the processing task.

Deployment with AWS Lambda and Express

Serverless Architecture: By deploying our application on AWS Lambda, we embraced a serverless architecture, which allowed us to run our code in response to events without the need to manage servers. This architecture significantly reduced overhead and enabled automatic scaling according to the application's needs, ensuring that our solution was both cost-effective and capable of handling varying loads, especially critical given the resource-intensive nature of processing large-scale CAD files.
Integration with Express: The use of the Express framework within the AWS Lambda environment facilitated the creation of a robust, scalable web application backend. Express, known for its flexibility and minimalism, provided a solid foundation for routing and middleware functionalities. This integration ensured that our serverless application could handle requests efficiently, maintaining high performance despite the complex data processing requirements.
Cost Efficiency: The serverless model offered by AWS Lambda meant that costs were directly tied to the actual usage rather than the predetermined server capacity. This model was particularly advantageous for our application, where the computational demand could fluctuate significantly based on the volume and complexity of the CAD files being processed.

Deployment with AWS Lambda and Express
Deployment with AWS Lambda and Express

Mobile Application Development and Testing

Implemented Solutions:

Comprehensive Testing and Bug Fixing

The existing mobile application underwent thorough testing to identify and fix all existing bugs, enhancing its reliability and performance.

Development of a New Application

For the new application, the developer researched and tested using MongoDB for local database management. Initial tests with collections in MongoDB were conducted to ensure compatibility and performance.

Integration Challenges

Although the MongoDB was successfully connected to the project, the development of the new application was not completed, indicating an area for future focus and development.

Project Timeline
Step 1
Research and Wireframing
Step 2
Development and Testing
Step 3



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