Smart Reverse Vending Machine Software Development
Budget: $30 – $250 USD
Develop the software code and touchscreen user interface (UI) for a Smart Reverse Vending Machine (RVM) that:
• Accepts PET bottles and aluminum cans
• Validates items (we will provide the object detection result)
• Issues receipts or on-screen confirmation
• Logs counts and statistics locally
• Allows local admin access via password
⸻
What You Will Do (Freelancer Scope)
• Build an offline, embedded Linux-based UI using a framework of your choice (e.g. Python + Flask PyQt, GTK, etc.). The program with run in full screen in Kiosk Mode on a Raspberrypi
• Develop code that interacts with the following (via GPIO or serial):
• Sensor or detection module (input: true/false or material type)
• Motor or bin opening trigger (via GPIO – just call a function or toggle a pin)
• Optional printer module (just trigger a print function or generate PDF)
• Implement a multi-language UI (Kurdish, Arabic, English – we will provide translations)
• Add a local admin panel, protected by password, to:
• View and reset counters
• Export or view daily logs
• Show simple analytics (items per day, receipts issued, etc.)
• Make it user-friendly and fast, optimized for touchscreen
• Ability for remote updates
⸻
System Details
• OS: Linux-based system (e.g., Raspberry Pi or similar)
• Language: Preferably Python (open to suggestions)
• UI Display: 10.1” capacitive touchscreen or bigger!
• All hardware (GPIO wiring, sensors, buttons, printer, etc.) will be connected and handled by us
⸻
Flow Summary
1. User inserts item → detection module sends material type
2. System accepts/rejects → shows result on screen
3. If accepted → increase counter → print/show receipt
4. Admin can log in locally → see stats → reset/export logs
⸻
Deliverables
• Clean, well-commented source code
• Simple documentation for local setup and editing
• User interface files and assets
• Language switch button
• Admin login interface
⸻
Notes
• You don’t have to touch the hardware – I will connect sensors, screen, and printer
• You just simulate their behavior with mock functions for testing
• Accepts PET bottles and aluminum cans
• Validates items (we will provide the object detection result)
• Issues receipts or on-screen confirmation
• Logs counts and statistics locally
• Allows local admin access via password
⸻
What You Will Do (Freelancer Scope)
• Build an offline, embedded Linux-based UI using a framework of your choice (e.g. Python + Flask PyQt, GTK, etc.). The program with run in full screen in Kiosk Mode on a Raspberrypi
• Develop code that interacts with the following (via GPIO or serial):
• Sensor or detection module (input: true/false or material type)
• Motor or bin opening trigger (via GPIO – just call a function or toggle a pin)
• Optional printer module (just trigger a print function or generate PDF)
• Implement a multi-language UI (Kurdish, Arabic, English – we will provide translations)
• Add a local admin panel, protected by password, to:
• View and reset counters
• Export or view daily logs
• Show simple analytics (items per day, receipts issued, etc.)
• Make it user-friendly and fast, optimized for touchscreen
• Ability for remote updates
⸻
System Details
• OS: Linux-based system (e.g., Raspberry Pi or similar)
• Language: Preferably Python (open to suggestions)
• UI Display: 10.1” capacitive touchscreen or bigger!
• All hardware (GPIO wiring, sensors, buttons, printer, etc.) will be connected and handled by us
⸻
Flow Summary
1. User inserts item → detection module sends material type
2. System accepts/rejects → shows result on screen
3. If accepted → increase counter → print/show receipt
4. Admin can log in locally → see stats → reset/export logs
⸻
Deliverables
• Clean, well-commented source code
• Simple documentation for local setup and editing
• User interface files and assets
• Language switch button
• Admin login interface
⸻
Notes
• You don’t have to touch the hardware – I will connect sensors, screen, and printer
• You just simulate their behavior with mock functions for testing
Related categories:
Perl
Python
Linux
CSS
User Interface / IA
HTML
Raspberry Pi
Flask
Embedded Systems
Object Detection