Cash Registers TRIZ Cases

Automated suspicion scoring filters continuous footage into targeted clips, reducing manual theft review time by up to thirtyfold.

A camera-based evaluator compares electronic-watermark and discount-seal IDs before output to prevent duplicate commodity registration at POS terminals.

This case replaces staff visual checks with biometric passport matching to confirm identity and user qualification for tax exemption.

Item exception agents identify and display the problematic item, helping attendants resolve checkout issues without questioning customers.

A geolocated virtual POS appears in augmented reality, enabling digital-wallet payments while reducing hardware costs and card exposure.

Sensors route anomaly signals to selected POS terminals, tailoring alerts by context so staff respond without disrupting transactions.

A multi-port switch links internal cameras, the scanner board, and external devices for coordinated data and power delivery.

This case combines remote customer service, modular dispensing, and a secure inventory vehicle for accurate retail transactions.

A server analyzes customer facial expressions, appearances, and actions to alert clerks to suspicious activity at self-service checkout.

Cameras and a trained computer model flag suspicious customer actions, appearances, or expressions and send clear warnings to clerks.

A payment acquisition device captures invoice images and extracts the amount for faster, more accurate transaction processing.

Independent gesture and object models detect missed scans while upgrading existing checkout devices at lower construction cost.

Co-located LED sub-groups at different wavelengths activate in sequence to match camera modules and improve optical-code capture.

A scanner and remote database verify user age across ID formats and block unauthorized repeat activations.

Multiple sensors and independent models capture interruption details, enabling remote staff to resolve self-checkout issues in real time.

A loyalty host mediates POS and offer data, while dual displays provide real-time information and automate transaction modifications.

A filtered message bus lets stateless PIN pads share dynamic gateways, reducing dedicated infrastructure and allocation delays.

Replacing continuous fields with discrete elements helps one computer handle simultaneous inputs across two POS touchscreens.

This case combines beam-breaker occupancy sensing with RFID timing to resolve multi-lane exit ambiguity and improve account matching.

A control circuit scores transactions and directs workers to verify selected items, reducing unpaid-item loss and exit wait times.

A detector and processor switch notification modes and light states to support paid-customer passage with less clerk oversight.

Movable frames and panels improve cleaning access beneath self-checkout bagging stations while adjusting surface area.

This case uses a multi-level touch interface to organize data, update merchant availability slots, and distribute promotions.

Cameras and a management server estimate facility groups, present results for confirmation, and support accurate collective payment.

Multiple optical views and machine learning automate checkout-plane item recognition while preserving human clerk assistance.

This case updates payment-terminal attestation criteria using transaction feedback to detect tampering and fraudulent activity.

This case uses optical identifiers to associate swapped POS components with checkout zones and configure them without manual programming.

Multiple cameras, raised-dot tray feedback, and audio cues guide item placement when visual checkout recognition is difficult.

This case integrates RFID, barcode, and vision inputs through one driver, prioritizing item codes and using online lookup when needed.

A server compares validated terminal functions with update requirements to target only necessary application updates and conserve memory.

Beacons link shoppers to self-checkout payments, reducing manual checks and theft risk.

A gateway standardizes diverse POS hardware protocols for simpler retail management.

AI identifies payment terminals from camera data and guides users with haptic or sound feedback to initiate tap-to-pay.

A unified driver prioritizes item codes from scanners and vision apps, resolving conflicts without changing existing checkout front ends.

This case combines AI vision, sensor fusion, and load-cell weighing in a cart-mounted checkout device for faster retail checkout.

Top-down and side cameras combine with barcode scanning to validate item identities and reduce checkout interruptions and shrinkage.

Sensors and a central server suspend pending POS transactions, check device status, and resume preserved data on operational terminals.

Separate baskets share item data in real time, consolidating group purchases for streamlined self-checkout payment.

A wireless cart links item scanning with inventory and checkout to expand product access while streamlining secure in-store shopping.

IoT monitoring captures checkout demand and exit-device capacity, while machine learning adjusts operations for faster customer flow.

This case combines computer vision with shopping history and inventory data to reduce self-checkout misidentification and shrinkage.

A weighing module, scanner, and state-controlled light strip guide checkout by signaling correct scans and weight errors.