Home Coral USB Accelerator Object Detection Kit with Raspberry Pi 4 + Camera
Coral USB Accelerator Object Detection Kit with Raspberry Pi 4 + Camera
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Coral USB Accelerator Object Detection Kit with Raspberry Pi 4 + Camera

SKU: CDN-KIT-2515 Brand: Compoden Category: Electronics > Edge AI & Computer Vision > Project Kits
Rs. 23,900.00
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Raspberry Pi 4 Coral USB Object Detection Kit — Build a Real-Time Edge AI Benchmarking Lab

Every part needed, pre-tested for compatibility, with an AI build companion trained on this exact project. Shipped from Bengaluru in 3-5 days.

Difficulty: Intermediate Build Time: 4-5 hours Age: 16-21 Skill: Edge AI latency benchmarking

This kit transforms a Raspberry Pi 4 and Google Coral USB accelerator into a real-time object detection system that identifies 90 everyday objects from a live camera feed. Powered by the SSD MobileNet model optimized for the Coral Edge TPU, the system achieves near real-time inference speeds. You will measure every millisecond of latency, building a dedicated benchmarking lab to understand the full pipeline from image capture to classification output.

What You'll Build

You will construct a self-contained computer vision station that streams camera frames, runs object detection locally, and overlays bounding boxes with class labels and confidence scores. A logging interface captures inference latency per frame, enabling you to analyse performance bottlenecks. The final setup becomes a repeatable testbed for comparing model variants, frame rates, and precision trade-offs on embedded hardware.

What You'll Learn

  • Deploy a TensorFlow Lite SSD MobileNet model on a Google Coral Edge TPU
  • Integrate the Coral USB Accelerator with Raspberry Pi 4 and Pi Camera Module 2
  • Measure and benchmark inference latency metrics (milliseconds per frame, throughput) with custom Python scripts
  • Tune pipeline parameters to balance detection accuracy and frames per second for real-world edge applications

Kit Contents

Component Quantity
Raspberry Pi 4 Model B 4GB x1
Coral USB Accelerator x1
Pi Camera Module 2 x1
MicroSD Card 32GB x1
USB-C PSU x1

Why Buy This Kit Instead of Sourcing Parts Separately

Factor Sourcing Separately Compoden Kit
Compatibility checks You verify every part Pre-tested as a system
Build support Forums and scattered tutorials AI companion trained on this exact project
Time to first working build Days of debugging Hours, with step-by-step guidance
Shipping coordination Multiple sellers, multiple delays One shipment from Bengaluru in 3-5 days

Who This Kit Is For

CBSE Class 11–12 students pursuing the AI elective will find a tangible way to explore neural network inference. B.Tech ECE, CSE, and EEE undergraduates can use this for mini-projects, final‑year work, or Smart India Hackathon entries centred on real‑time computer vision. Makers at ATL Tinkering Labs and engineering colleges like IIT, NIT, VIT, and BITS will appreciate the repeatable benchmarking framework.

Built and Backed by Compoden

Every Compoden kit ships with an AI build companion trained on this exact project — accessible via a QR code on the box, with WhatsApp and email backup. We've spent 10 years building projects for makers, schools, and institutions across India. If a part fails because of a manufacturing defect, replace it free within 7 days.

What if I get stuck during the build?

Our AI companion walks you through debugging in real time, and you can reach the WhatsApp support team Monday to Saturday for personalised guidance on any roadblock.

Can I use this kit for a college major project submission?

Yes. The build guide includes a full report template covering model selection, deployment, and latency analysis, making it directly usable for final-year B.Tech projects in ECE, CSE, or EEE.

Does this kit work with a different camera module?

The kit is pre-tested with the Pi Camera Module 2 for consistent latency benchmarks. Other USB cameras may function but require additional configuration and may alter performance results.

How does the latency benchmarking work?

You'll run a provided Python script that captures frames, performs Coral‑accelerated inference, and logs the time for each detection. The toolkit includes graphing utilities to visualise latency trends across different resolutions and model settings.

SSD MobileNet on Google Coral USB detects 90 object classes at near real-time speeds on Pi 4 — latency benchmarking lab.

What's in this kit

Shipping Information

  • Prepaid Orders: ₹75 for orders up to ₹999, FREE shipping above ₹999
  • COD Orders: ₹125 shipping + ₹50 COD fee = ₹175 total
  • Delivery Timeline: Dispatch in 1-2 days, delivery in 2-7 days depending on location

Returns & Warranty

  • 7-Day Return: Manufacturing defects only (approval required)
  • Warranty: 7 days from delivery
  • Non-Returnable: Batteries, consumables, cut wires, clearance items

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