The initial phases of our project revolved around researching topics of interest. We delved into researching potential ideas, exploring topics such as Spotify Wrapped and crime prediction/forecasting. While considering these ideas, we decided on a website centering around statistics. Originally these statistics were going to be based about crime information per area but we did not want to confine ourselves to just this data. With a general idea of our project decided, we then went about discussing potential supervisors that would suit this project, primarily ones with experience in web design and database management. After securing our supervisor and further discussing our idea with him, we decided on expanding our project idea to become a more well rounded concept revolving around area-wide statistics and features, not just on crime but also on information that would interest potential home owners such as schools in an area, house prices, rent, amenities, etc. With our idea fully agreed upon, we began creating a comprehensive project proposal, outlining the objectives, methodologies, and expected outcomes. We also created two repositories to manage our progress, one on GitLab as our main project, and a backup GitHub repository for storing rough and experimental versions of the project.
We dedicated this time to finalising our project proposal. After detailing the features and necessary details on our project, we sent it to our supervisor, who advised that we emphasise who the target market is for the website - we made the necessary changes and refined the proposal further to align more closely with the project's objectives. The refined proposal then earned the approval of our supervisor, which allowed us to progress with our idea further. We pushed the finalised proposal to our shared GitLab repository for further review.
Our main goal during this week was exploring potential API options for the different statistics to be provided on the site. Research efforts were also directed towards determining the most relevant and impactful statistics/features to integrate into the website. We considered information such as crime, transportation, traffic, home prices, amenities, schools, weather conditions, etc. We agreed upon the main topics of crime, home prices and rent, amenities, schools and transportation. We then focused on researching available APIs that aligned with the project's objectives. In conjunction with the API research, attention was dedicated to designing the general layout of the website. Key considerations included optimal user navigation, responsive design, and a visually appealing appearance to enhance the overall user experience. We used Canva as a tool for our design mock up. We also created our powerpoint presentation explaining our project and its aims which we then presented and got our approval for the project granted.
We found the ideal API for local amenities and crime statistics, which is really beneficial for our project. Furthermore, we discovered an interesting transport link API that has the potential to significantly improve our project. We have an API key that we secured to ensure that we may utilise this transport API. In order to maintain order and progress during this process, we have established a Trello Board where we will manage all of our tasks.
This week we searched Postman to find potential datasets related to school locations in different areas, which is crucial for our project. After that, we immediately started working on the backend. First, we created a Django project and set up all the necessary configurations. In order to supplement our backend effort, we started a React project starter at the same time. In addition, we have begun establishing the foundation for our project requirements, which will specify our goals and our strategy for achieving them.
We successfully secured access to the Amenities API and managed to integrate it into our project framework. But the Crime API didn't work the way we had hoped, thus we ran into trouble. Despite this setback, we didn't let it stop us from moving quickly to locate a substitute Crime API and start learning about its features and implementation. We also had a productive meeting with our supervisor to go over and improve the project requirements, making sure they were in line with our aims and objectives. Additionally, we've uploaded the completed project specification to GitLab.
We've invested a lot of effort into making our amenities feature more visually appealing and user-friendly by improving its layout and visual appeal by adding cards. In addition, we made significant progress by finding a comprehensive home database, which will significantly increase the amount of information our users have access to. To further improve the platform's usability and effectiveness, we've added a helpful search feature that lets customers quickly filter amenities based on the location they want.
Through the effective integration of a new crime database, we were able to collect and arrange data according to location, making use of nested JSON structures. But there were some obstacles in our way when we explored the Transport API because we couldn't fully grasp all of its features. Positively, we worked with school datasets and were able to simplify their accessibility and usability within our project framework by converting them into CSV files. Additionally, by developing simple navbar codes, we set the foundation for user navigation, which will make browsing easier and more natural for users.
We have concentrated on improving the navigation and user interface. We took our time when designing the navbar to make sure it was visually appealing and would link correctly to all pages of the website. Now that the navbar is incorporated into every page, users may quickly and simply move between sections. Additionally, we've created a lively homepage that acts as a main entry point for a variety of services and data. We used React Router DOM to enable seamless component rendering and routing based on user inputs, hence facilitating easy navigating between various areas.
We've advanced significantly in a number of important areas. First off, the Crime feature has paid off after our efforts; it is now completely functional and incorporated into our platform, offering users insightful data. However there are still difficulties with the transportation component. We have been working hard to optimise the Schools function so that it provides education data. Furthermore, we have strengthened our platform's functionality by installing Cors-Headers and Django Rest Framework into our backend setup.