The software development roadmap

A lot of planning has gone into ensuring pacenote.ai has a detailed and robust roadmap for future development so that everyone can see the vision of pacenote.ai and how it can be achieved. Development roadmaps are important as they break down the entire process of building the full application into bite-sized pieces that can easily be achieved. This allows for detailed cost and timing predictions as well as prioritising features.

Pacenote.ai’s roadmap is broken down into each specific feature we would like to bring to the platform. The successful development of each feature will culminate in a full, production-ready version of the application. There is no priority set for each feature within the roadmap since it is expected Pacenote.ai’s development journey will be shaped by feedback from potential customers. This feedback will allow us to decide what to focus our time and resources on.

Consequently, in no specific order, here are the features on Pacenote.ai’s roadmap:

1. Ability to detect distance travelled between corners and include this distance in meters in the output. This is core functionality that needs to be developed in order for the application to fulfil it’s purpose.

2. Ability to detect hazards along the stage that would need to be flagged to the driver such as parked cars, rocks, buildings and corners that should not be cut. This is also core functionality and therefore deemed imperative to creating a production version of Pacenote.ai.

3. Ability to detect elevation changes in the road such as jumps, crests and steep drops/climbs and add these to the output notes if they are a hazard.This is very important functionality that would make Pacenote.ai’s offering far more compelling to potential customers. However, while this is needed for Pacenote.ai to autonomously create pace notes, as a verification tool for human-generated pace notes this is not critical core functionality.

4. Web-based graphical user interface (GUI) which includes instructions for the users to calibrate their cameras and then upload a video to process. Processed videos are visible in this GUI along with their output files.This functionality is key for scalability. To appeal to as many customers as possible, pacenote.ai needs to be as easy to use as possible. However, a GUI is not critical for testing and early-release so long as users are provided with sufficient guides on the existing process.

5. Create a new output file in PDF format which more closely reflects traditional pacenotes in terms of formatting and layout. This is non-critical functionality that is designed to make the output more useful. However, it’s expected users of Pacenote.ai will process and format the output in their own specific ways so this functionality is not critical.

6. Ability to detect surface conditions (e.g wet, icy, rocky, smooth) of the road in the video and make changes to compensate for the changed conditions. This functionality is critical to making Pacenote.ai work across a wider set of stage conditions but it is not critical for testing and early-release which would likely be designed around a specific set of stage conditions.

7. General improvements to the current system accuracy with a focus on reducing false positives and red herrings. This is seen as critical functionality that will be an on-going task throughout the development of Pacenote.ai