System Architecture

The platform was designed to create a reliable order pipeline from customer device to concession fulfillment.

Customer Phone
↓
WordPress Ordering Interface
↓
RestroPress Order Processing
↓
Concession Stand Server / Order Queue
↓
Thermal Receipt Printer
↓
Order Fulfillment by Staff
↓
Twilio SMS Notification to Customer

This approach ensured that staff received orders in a familiar format while customers received timely updates on their purchases.

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Key Features

Geo-Restricted Ordering

To ensure that only guests physically present at the drive-in could place orders, ordering access was restricted using GeoIP filtering.

This prevented external users from accessing the ordering system and ensured that only customers on theater property could submit concession orders.

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Mobile-Optimized Ordering Experience

The interface was designed specifically for mobile devices since customers would be ordering from their cars.

The ordering flow emphasized:

• fast menu browsing
• simple checkout
• large touch-friendly interface elements
• minimal steps to complete an order

This ensured that customers could place orders quickly and easily from their phones.

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Real-Time Concession Workflow

When an order was placed, it was immediately transmitted to a server located inside the concession stand.

Each order was automatically printed to a thermal receipt printer, creating a workflow similar to a restaurant kitchen ticket.

This allowed concession staff to continue working within a familiar process while handling digital orders.

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SMS Pickup Notifications

Once an order was prepared, concession staff could press a Notify Customer button in the system.

This triggered an automated text message sent through the Twilio SMS API, informing the customer that their order was ready for pickup.

This system reduced crowding inside the concession stand and allowed customers to remain in their vehicles until their food was ready.

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Engineering Challenge: System Capacity

One of the most critical questions during development was whether the system could handle full drive-in capacity during peak ordering times.

Because live testing with hundreds of customers was impractical before deployment, I designed a custom automated load testing framework to simulate realistic ordering activity.

The goal was to replicate the behavior of hundreds of customers placing orders during the two-hour pre-show window.

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Load Testing Strategy

To accurately simulate real-world conditions, I implemented a multi-layer testing system.

Simulated User Accounts

Ten automated user accounts were created on the development server to act as independent ordering agents.

These simulated separate customers interacting with the ordering system.

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Randomized Order Generation

To prevent repetitive or unrealistic testing patterns, I built a spintax-based order generator that randomized product selections using product IDs.

This allowed the test environment to generate unique order combinations that more closely resembled real concession purchases.

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Browser-Level Automation

Instead of sending direct server requests, I used JavaScript browser automation to simulate the full customer ordering process.

The automation replicated:

• menu browsing
• item selection
• checkout
• order submission

This ensured the system was tested under realistic user interaction conditions.

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Maximum Capacity Simulation

The load testing environment simulated the theater’s full operational capacity:

500 potential concession orders

This scenario represented the maximum possible demand during a busy pre-show period.

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Test Results

The stress test was executed three separate times under simulated peak demand conditions.

Results included:

• Successful processing of 500 simulated orders per test
• No server crashes or failures
• Stable order queue processing
• Reliable thermal printer output
• Successful delivery of SMS notifications

The results confirmed that the system could support full theater capacity without operational disruption.

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Outcome

Although the system ultimately was not required due to evolving pandemic restrictions, the platform proved to be fully operational and production-ready.

The project demonstrated how a traditional entertainment venue could rapidly transition to a digital ordering infrastructure without disrupting staff workflows.

The platform successfully combined web technologies with real-world operational systems to create a scalable solution for concession ordering.

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Technologies Used

WordPress
RestroPress
PHP
JavaScript
Twilio SMS API
GeoIP Filtering
Thermal Receipt Printer Integration
Browser Automation
Spintax Order Generation

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Skills Demonstrated

Full-Stack Web Development
System Architecture Design
Automation Engineering
API Integration
Operational Workflow Design
High-Traffic System Planning
Load Testing and Performance Validation

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Impact

• Designed to support 500 concurrent drive-in guests
• Enabled fully contactless concession ordering
• Integrated web ordering with real-world concession operations
• Successfully validated through automated high-volume testing

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Key Takeaway

This project demonstrates the ability to design and engineer scalable systems that connect web platforms with physical operational environments.

By combining automation, infrastructure design, and performance testing, the system ensured that a high-capacity venue could safely and efficiently manage concession orders during peak demand.