The Top 35-under-35 competition was launched in 2014 by SAICA to provide a platform to recognise CAs(SA), both nationally and internationally, who are bringing about a valuable and notable contribution to not only to their businesses but also to society. Each Top 35 finalist boasts a unique and inspiring story to success.
To be selected as a Top-35-under-35 finalist is an outstanding accomplishment. It means that you have been recognised as top talent amongst thousands of other young CAs(SA). Your exceptional accomplishments and achievements in your career or business stand out from the crowd. Your innovative ideas, work ethic, leadership style and contributions to society have made a valuable difference that deserves some showcasing.
As part of my submission, I included the following project built using Unreal Studio (If you like to concept please vote on the following link (2018 Top 35-under-35 Entry: Christopher Edward Commin – Accountancy SA)
- What does Unreal Engine do for your project?
Our project began in September 2015, with chartered account and an IT supervisor with no previous game development experience nor exposure to any of the game development disciplines other than programming. Given the nature of business functions, one of our focus areas is to generate and interpret spreadsheet data (usually) excel in order to provide intelligence into the business.
As a fleeting thought, whilst on vacation, we stumbled upon the possible innovation, of recreating our current business model in a game engine allowing to view the business in a more interactive visual manner whilst still allowing us access to logic systems in order to perform financial modelling calculations. This innovation was then pushed further with a focus on interactively viewing our industry from a geographical stand point.
Our project details are as follows:
- Map of South Africa
Using height maps, we have recreated a scaled South African landscape using the land gizmo. The landscape has been textured using base material and on top of that, using open source maps, we have overlay-ed the South African street map. Currently, we can take this one step further and overlay any South African based information, which is represented on the South African texture map, and see that data reflected in the landscape texture.
Using the map, we have placed icons, using converted real world GPS co-ordinates, which enables us to view the competitive landscape of the real market in South Africa. We have started taking this one step further by placing our secondary market on the map. Whilst navigating the map, an icon can be interacted with in order to display the relevant information of that facility (i.e. name, address, telephone number and market intelligence). In addition, we have placed visual rings, with collision, which represent all the local municipalities in South Africa. On overlap of these collision cylinders, the user is provided with further market intelligence (i.e. population stats and renal prevalence) via the UI.
In addition, we have also included UI utilities, such as straight-line distance between points and current GPS location.
- Financial Reporting
Coding the base variables in C++, we have created a blueprint which represents the standard cost income statement for a renal facility. This will allow us to data warehouse our facilities financial and operation performance, supplier details and per item costing on a per facility basis. This can also be used to generate a model for a feasibility in order to access the impact of financial and operational decisions.
In addition, using tables, the core information can be pre-populated on a monthly basis in order to ensure that the business is working with the most-to-date information. The setup of the actor allows for it to be located anywhere in the world, therefore it can be inserted into the South African map on a per facility (instanced basis). Because all the actors are located in the same level, you can run per income statement line items scripts in order to extract market information (e.g. supplier pricing).
- Architectural Visualisation
Using the Datasmith plugin we can create 3D visual representations of our renal facilities in order to make financial and operational decisions. In addition, this allows us to create models of proposed facilities in order to view the facility before it is built. Lastly, the virtual facility can also act as a repository of company asset based information. (e.g. number/location of plugs/fridges/taps/key-assets and so on).
- Innovations we are looking at exploring (not yet implemented)
Currently, we are also looking at importing live (with a few seconds delay) GPS data into the engine which would update key variables. Using this GPS data (received via device or RF technologies), we should be able to re-base data on a per level basis allowing us to track a vehicle moving anywhere on our Map South Africa or track the movement of staff inside a facility on a “real-time” basis. This would provide invaluable time-in-motion data which could be used in assessing a facilities overall performance.
Lastly, if built correctly, this in theory could be pushed to VR, allowing management to view ghosted employees moving through a unit in “real time”.
- What does UnrealStudio do for your workflow? - does it let you be more creative? - does it save you from doing boring work? - does it help you be more competitive? - does it open up new business for you?
For our project we have and will be using UnrealStudio in two main workflows, the importing of a renal dialysis facility and the importing of a detailed static mesh repository.
In terms of the facility, we import the masonry, ironmongery and joinery for the facility as a complete scene of a few million triangles. Then we use UnrealStudio to import a set of detailed static meshes into a dummy level, the aggregate triangle count of these meshes also reaching into the millions. These meshes are then used for set dressing purposes where we attempt to dress the facility as per our reference photography.
Because our project entailed, amongst other things, the scaled recreation of the South African landscape, we spent a significant portion of time testing the static mesh triangle import limits of the engine. What this did is create an awareness in us, forcing us to generate static meshes which sacrificed visual fidelity for triangle count. After been added to the UnrealStudio program, we let go of these preconceptions and focused on modelling detail into the static meshes instead of concerning ourselves with baking normal maps. This allows us to be more efficient and get meshes into the engine.
This is a huge help because we have not studied the skills required in the game development industry and given further, that this is an innovation project within the business, we still need to perform our main functions within our organisation, so any time saving for us is a good one.
- How much more efficiently does UnrealStudio help you work? Please provide in terms of efficiency, 50%, 200%, etc.
The UnrealStudio tool increased our efficiency on importing scene and models 2 fold. At one point we imported a repository of static meshes using the traditional drag-and-drop import of an FBX and then we reimported the same data using the UnrealStudio tool and the comparisons are unparalleled.
- On this project, can you give us details about: How complex is the scene in terms of polygons and objects?
Included below is a copy of the Swarm and Log with the key details for the Light mass bake.
13:46:07: Measured CPU frequency: 3.31 GHz
13:46:07: FStaticLightingSystem started using GKDOPMaxTrisPerLeaf: 4
13:46:07: Number of texture mappings: 225
13:46:07: Number of fluid mappings: 0
13:46:07: Number of landscape mappings: 0
13:46:07: Number of BSP mappings: 0
13:46:07: Number of static mesh instance mappings: 225
13:46:10: Scene surface area calculated at 18.507 million units (92.292% of the estimated 20.053 million units)
13:46:10: Importance volume surface area calculated at 17.645 million units (167.780% of the estimated 10.517 million units)
13:46:11: Collision Mesh Overview:
13:46:11: Num Triangles : 3563321
13:46:11: MeshInfos : 0.0Mb
13:46:11: UVs : 29.1Mb
13:46:11: LightmapUVs : 29.1Mb
13:46:11: Embree Used Memory : 263.3Mb
- What GPU did you use with Unreal?
Our project was built across two main CPU’s/GPU’s:
The first was a MSI GP72 Leopard Pro with an Intel® Core™ i7 5700HQ processor at 3.3GHz running 8GB DDR3 RAM. The system came with a NVIDIA GeForce GTX 950M which has 2GB DDR3. (Unfortunately, this was stolen). The second is a Wacom MobileStudio Pro 13 with an Intel® CoreTM i7 at 3.3GHz, 512GB SSD, 16GB DDR3 and Intel® IrisTM Graphics 550.
Although we initially started designing the project on the MSI, we have been able to reproduce the entire project on the Wacom Mobile Studio. Furthermore, the system has been able to handle the creation and running of our project with little hassle, despite the achieved frame rate.
- What frame rate did you have in Unreal?
On the Wacom MobileStudio Pro 13 the current frame rate is around 17 fps, but bear in mind that we are not necessarily pushing for performance here. Our project is designed rather to work in the editor and we use PIE to obtain visual information on a needs basis. We have pushed the 3D modelling harder than it should be in order to produce a performant project, but as is, the project runs on our hardware and meets our visual needs.
Using my teammates MSI (same specs as above) the frame rate ranged between 40 and 60 FPS. We also tested the facility scene on a CPU: Intel Kaby Lake Core i7-7700, GPU: AORUS GeForce GTX 1080 Xtreme Edition, RAM: 16GB DDR4-3000, Motherboard: AORUS Z270X-Gaming 9 and capped out at 120fps.
- General quote about UnrealStudio:
UnrealStudio has made a tremendous improvement to our workflow. As a team comprised of no one from a game development or architecture background, we have been able to push our modelling, and with the rapid importing of data and ease of iteration provided by the engine, been able to produce a project which combines our careers with our passion for gaming.