Overview
Zebra MC32N0-GI4HCHEI3-U Rugged Mobile Computer
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Bundle Summary
Overview
Zebra MC32N0-GI4HCHEI3-U Rugged Mobile Computer
The Zebra MC32N0-GI4HCHEI3-U is a compact handheld mobile computer engineered for field mobility in warehouse, logistics, and retail environments. This refurbished unit combines integrated 1D/2D barcode scanning capability with rugged construction to deliver reliable data capture and mobility in demanding operational settings. Built on Windows CE 7 operating system, the MC32N0-GI4HCHEI3-U delivers proven performance for inventory management, order fulfillment, and asset tracking applications.
Overview
Designed as a comprehensive mobile data collection platform, the MC32N0-GI4HCHEI3-U integrates scanning, wireless connectivity, and computing into a single ruggedized form factor. The 3-inch color TFT display provides readable feedback in varied lighting conditions. With IP54 rating per IEC specification and 1.2-meter drop tolerance, the unit withstands typical warehouse handling and environmental exposure. WiFi connectivity enables real-time communication with backend systems, while the dual-core 800MHz processor and configurable memory options support mid-weight workload execution without requiring cellular connectivity.
Key Features
- Integrated 1D/2D Barcode Scanning: Captures both traditional linear and matrix barcodes including QR codes and Data Matrix, reducing need for secondary scanning devices
- IP54 Ruggedness: Rated to IP54 per IEC specification, protecting against dust and splash exposure common in warehouse and logistics operations
- 1.2-Meter Drop Rating: Tolerates accidental drops to concrete, minimizing downtime from equipment damage during typical field handling
- 3-Inch Color Display: TFT color screen provides clear visual feedback and touchscreen capability for menu navigation and data verification
- WiFi Connectivity: 802.11a/b/g/n support with channels 36-165 (5180-5825MHz) enables wireless connection to facility networks and backend systems
- 4800mAh Battery: Provides full-shift operation without mid-day recharging, critical for high-volume scanning environments
- Dual-Core 800MHz Processor: Executes warehouse management software and barcode capture routines efficiently
- 512MB RAM / 2GB Storage Options: Configurable memory supports application requirements and offline data buffering
- Audio Support: Integrated speaker, microphone, and headset jack enable scanning feedback and hands-free communication
- Windows CE 7 Operating System: Mature, proven platform with extensive logistics software support and established deployment patterns
Integration and Deployment Context
The MC32N0-GI4HCHEI3-U integrates into existing WiFi infrastructure without requiring dedicated cellular plans, making it suitable for facilities with coverage already in place. The Windows CE 7 environment supports proven warehouse management applications and custom barcode capture workflows developed over multiple product generations. Dual-core processing and 512MB/2GB memory configurations support moderate-complexity applications including real-time inventory lookups and order verification tasks. The integrated 1D/2D engine eliminates the need for external scanning peripherals, reducing cable management and charging complexity. IP54 rating and drop tolerance position the unit for direct use in loading docks, warehouse floors, and delivery vehicle environments without protective enclosures.
System Design, Deployment & Technical Support
Support services and planning resources for commercial surveillance, access control, and infrastructure deployments.
Fixed scope • Fixed price
System Design Assistance
- Get help validating product compatibility
- Coverage requirements
- Storage planning and deployment architecture before you buy.
Deployment & Configuration Support
- Access fixed-scope support for rollout planning
- User setup guidance
- Migration and system standardization across single-site or multi-site deployments
Guides, Tools & Calculators
- PoE requirements
- Storage retention
- Camera selection and deployment methodology