Long Range Usb 1d Wired Qr Code Scan Gun Handheld Barcode Scanner Inventory Laser Barcode Reader for

Logistics Supermarket

Key Components:

Light Source: Illuminates the barcode (Laser diode, LED array, or imaging sensor illumination).

Optics/Lens: Focuses the reflected light onto the sensor.

Sensor/Photodetector: Converts the reflected light pattern into an electrical signal.

Laser Scanners: Use a moving laser beam and a single photodiode.

Linear Imagers (CCD): Use an array of LEDs and a linear sensor chip to capture an image of the barcode.

2D Area Imagers: Use LEDs and a 2D camera sensor to capture an image of the entire code (can read 1D and 2D codes

from any orientation).

Decoder Circuitry: Processes the electrical signal, deciphers the pattern according to symbology rules (e.g., UPC,

Code 128, QR), 

and outputs the decoded data.

Interface: Transmits the decoded data to the host system (USB, RS-232, Keyboard Wedge, Bluetooth).

Housing/Ergonomics: Designed for comfortable grip, often with a trigger for activation. Rugged models feature reinforced

casings.

Feedback: Audible beep and/or LED light indicate a successful scan.

Scanning Technologies:

Laser Scanners: Traditional, fast, excellent for 1D barcodes at longer distances. Requires precise aiming. Cannot read

2D codes or damaged/printed codes well.

Linear Imagers (CCD): Use LED illumination, no moving parts (more durable than laser). Can read 1D barcodes from

printed labels, screens, and curved surfaces better than lasers. Still cannot read 2D codes.

2D Area Imagers: Most versatile and dominant today. Use a camera sensor to capture an image of the entire code.

Key advantages:

Read both 1D and 2D codes (QR, Data Matrix, Aztec, PDF417, etc.).

Read codes omnidirectionally (any orientation).

Read codes from screens (phone displays, monitors).

Read poorly printed, damaged, or dirty codes more reliably.

Capture images and signatures (advanced models).

Read barcodes at longer distances (long-range models).

Perform OCR (Optical Character Recognition) on text (some models).