Healthy Catering — Alessandro Carella

Healthy Catering is a 3D serious game developed as part of my bachelor's degree in Computer Science at the University of Bari. Created in collaboration with Saverio Cassano , this project combines gaming entertainment with educational content focused on nutrition, pathologies, and environmental sustainability. The game places players in the role of a restaurant manager who must serve appropriate dishes to customers based on their medical conditions and dietary requirements.

Developed for the Multimedia Design and Production course, the game targets students from hospitality institutes and nutrition science courses. The project emphasizes the correlation between food choices, health conditions, and environmental impact through an engaging first-person gameplay experience.

The game was later extended with VR capabilities by my collaborator as part of his bachelor thesis. The current version with VR support is available at this project repository, though this page focuses on the original PC version I contributed to. You can also find Saverio's thesis repository in the sidebar of the page.

This project provided me with experience in game development and interdisciplinary collaboration. Working with Unity and C# deepened my understanding of game engine architecture, 3D graphics programming, and real-time interactive systems. I learned how to implement game mechanics involving inventory management, scoring systems, and dynamic UI elements that respond to player choices.

The serious game nature of the project taught me how to balance educational content with engaging gameplay. I discovered the importance of progressive difficulty curves, clear feedback mechanisms, and intuitive tutorials. Designing systems that teach players about nutriScore , costoEco (environmental cost), and pathology-diet relationships required careful consideration of how information is presented and reinforced through gameplay.

Project management skills were essential throughout the development. I learned to estimate time requirements accurately, track progress across multiple development phases, and adapt to changing requirements. The structured approach using flowcharts, storyboards, and prototypes proved crucial for maintaining alignment between design vision and implementation.

User testing opened my eyes to the gap between developer intention and player experience. Conducting alpha and beta tests, observing player behavior, and gathering feedback through SUS (System Usability Scale) questionnaires taught me the value of iterative design. The testing phase revealed issues we hadn't anticipated, such as difficulty balancing problems that required adjusting score thresholds to prevent player frustration.

Collaboration was central to the project's success. Working closely with another developer, coordinating with external contributors for music, 3D assets, and UI design taught me effective communication and improved my skills at version control practices using Git. I learned to divide responsibilities, integrate work from multiple sources, and maintain code quality across team contributions.

The game was built using Unity 2021.3.5f with C# as the primary programming language. Visual Studio 2019 served as the development environment, providing robust debugging and code completion capabilities. For asset creation and editing, we utilized Adobe Photoshop 2022 for textures and UI elements, Adobe Illustrator 2022 for vector graphics and logos, and Blender for custom 3D modeling when needed.

The project leveraged several Unity asset packs including Polygon City , Polygon Farmer , and Polygon Prototype Pack for environmental 3D models. Character animations were sourced from Mixamo , while the soundtrack was custom-composed by Alessandro Congedo . Version control was managed through GitHub, enabling asynchronous development and collaborative workflows.

The game's architecture revolves around several interconnected systems. The customer interaction system manages client profiles, including their pathologies (diabetes, hypertension), dietary restrictions, and dish preferences. Each customer is generated with specific health parameters that determine which dishes are suitable for them.

The scoring algorithm evaluates dish selections based on multiple factors: affinity with customer pathologies and diet, nutriScore ratings (A through E), and costoEco values (environmental impact from 0-41+). The calculation awards base points of 100 for appropriate dishes or -10 for poor choices, then applies percentage-based bonuses or penalties based on nutritional quality and environmental sustainability.

The inventory management system tracks ingredient quantities and enforces constraints on dish preparation. Players can only prepare dishes when all required ingredients are available in sufficient quantities. The shop system allows purchasing new ingredients using earned money, creating a resource management loop that encourages strategic planning.

A dynamic price calculation system determines earnings per dish served. The formula considers ingredient base costs plus a 10% profit margin, then applies affinity bonuses (+5% for correct choices, -5% for incorrect ones) and ranking bonuses (3%, 2%, or 1% for dishes in the top three positions of the sorted dish list).

The UI employs a consistent visual language using the Roboto-Bold Sans Serif font for clarity and readability. A color-coding system helps players quickly identify information categories: green for correct choices, red for incorrect ones, yellow for ingredients, orange for dishes, blue for pathologies, and purple for diets.

The in-game interface includes multiple views: a customer interaction menu displaying medical records and dish options, an inventory management system accessed through a virtual computer, a shop interface for purchasing ingredients, and a recipe book showing all available dishes with their ingredients and technical specifications. An integrated help menu provides contextual guidance accessible at any time by pressing the H key.

Players assume the role of a restaurant manager who has inherited their uncle's establishment. The core gameplay loop involves serving customers by selecting appropriate dishes from available options, earning money and points based on choice quality, managing ingredient inventory, purchasing supplies from the shop, and progressing through increasingly challenging levels.

The game features three levels with escalating difficulty. Level 0 serves as an interactive tutorial introducing movement controls, customer interaction mechanics, inventory management, and the shop system. This level requires serving 5 customers and achieving a score of 700. Level 1 focuses on diabetes-related dietary knowledge, requiring 15 customers served and a score of 1400. Level 2 addresses hypertension, demanding 20 customers served and a score of 2000.

The educational content is seamlessly integrated into gameplay rather than presented as separate lessons. Players learn about pathology-appropriate nutrition by making decisions and receiving immediate feedback. Incorrect dish selections trigger informative pop-ups explaining why specific ingredients are incompatible with certain conditions or diets.

NPC characters scattered throughout the game world provide contextual tips about dish selection, nutriScore interpretation, and environmental considerations. The recipe book serves as an in-game reference, allowing players to research dish compositions, nutritional ratings, and environmental impacts without breaking immersion.

The tutorial system employs a gradual reveal approach, introducing concepts only when necessary to avoid overwhelming players with information. Each tutorial segment combines textual explanations with video demonstrations and requires players to successfully complete the action before proceeding, ensuring active learning rather than passive reading.

Difficulty increases through multiple mechanisms: higher score requirements, more customers to serve, stricter failure thresholds, and more complex pathology-diet combinations. The game maintains tension through resource scarcity, players must balance immediate food service needs with long-term inventory investment decisions.

Failure conditions include running out of both ingredients and money (below 5 currency units), or failing to reach the level's score threshold within the maximum number of customer servings (10 for Level 0, 25 for Level 1, 30 for Level 2). This creates strategic pressure to make optimal choices rather than merely acceptable ones.

The project began with comprehensive planning documentation including requirement specifications, target audience analysis, and style guidelines. We defined minimum and recommended system requirements, ensuring the game would be accessible on modest hardware (minimum 1GB RAM, integrated graphics) while supporting high-end configurations (up to 1920x1080 resolution, GEFORCE GT graphics cards).

Design documentation included detailed flowcharts mapping navigation between all game screens and gameplay states, storyboards specifying visual layout and color schemes for each interface, and prototypes demonstrating key interactions. This upfront design work proved crucial for maintaining consistency and coordination between developers.

Development followed a phased approach tracked through weekly progress monitoring. The schedule allocated time for content acquisition (5 hours), material verification and validation (5 hours), interface definition (17 hours), material refinement (8 hours), core development (48 hours), testing (30 hours), and publication (2 hours).

Actual development tracking revealed the fluid nature of game development. Early weeks saw concentrated effort on asset acquisition, interface design, and material refinement, with development intensity increasing mid-project. The final weeks focused exclusively on testing and bug fixing before publication.

The project team consisted of two primary developers with support from external contributors. Alessandro Congedo composed the original soundtrack, Francesca Caranzano assisted with UI design, Angelica Garofalo contributed 3D art assets, and Vincenzo Francesco Pio Grande provided text review and editing.

Technical resources combined owned assets (Polygon packs), free Unity Asset Store resources, online sound effect repositories, and custom-created materials. This hybrid approach balanced quality requirements with the zero-budget constraint imposed by the academic context.

Alpha testing focused on functional correctness, structural integrity, and performance across different hardware configurations. We evaluated interface pleasantness, simplicity, command learning curve, response accuracy, and feature functionality. Testing was conducted on four machines ranging from modest (i5-4690K with GTX 1650 Super) to high-end (Ryzen 7 5800H with RTX 3060) configurations.

Key issues discovered during alpha testing included framerate-dependent animation timing that caused inconsistent behavior across different PCs, and persistent game state variables that weren't being reset when levels were reloaded. The animation issue was resolved by implementing framerate-independent timing, while the state issue required explicit variable reinitialization on level load.

Performance testing showed stable frame rates across all test configurations, with CPU usage ranging from 27-50% and GPU usage from 20-62% depending on hardware. Even the lowest-spec machine maintained stable performance at maximum graphics settings, validating our optimization efforts.

A critical discovery during alpha testing was difficulty balancing. Initial testing revealed that achieving level objectives required perfect performance with no margin for error. This created excessive challenge and potential player frustration. We responded by lowering score thresholds for each level, providing a more reasonable error margin while maintaining meaningful challenge.

Navigation consistency checks revealed missing confirmation dialogs when players attempted to return to the main menu mid-level, potentially causing accidental progress loss. Audio system testing uncovered rare cases where footstep sounds would continue playing when menus opened, requiring explicit audio suppression during menu states.

Beta testing involved five users representing both target users (students from relevant educational backgrounds) and experienced gamers who could provide technical feedback. Testing occurred in controlled environments with developers present for observation and note-taking.

The System Usability Scale (SUS) questionnaire yielded a final score of 91.5 out of 100, indicating excellent usability. Individual responses showed consistency across metrics, with particularly strong scores for feature integration, ease of learning, and minimal need for external support. Users rated the game as simple to use (scores of 3-4 out of 4) and felt comfortable during play.

Qualitative feedback from beta testers highlighted the game's intuitive controls and clear visual communication. The color-coding system for information categories received positive mention, helping players quickly parse complex nutritional data. The tutorial system's gradual introduction of concepts was praised for preventing information overload.

Some users initially found the scoring system's complexity challenging to understand, particularly the interaction between nutriScore, costoEco, and pathology affinity bonuses. This feedback validated our decision to include detailed help documentation accessible at any time during gameplay, and suggested the tutorial could spend additional time on scoring mechanics.

The completed project successfully met its educational objectives while maintaining engaging gameplay. The game runs stably across a wide range of hardware configurations, features an intuitive interface validated by SUS testing, and effectively teaches players about nutrition-pathology relationships and environmental food impacts. The structured development approach, comprehensive testing, and willingness to iterate based on feedback resulted in a polished final product that serves its serious game purpose effectively.