Logo
  • Cases & Projects
  • Developers
  • Contact
Sign InSign Up

© Copyright 2025 Many.Dev. All Rights Reserved.

Product
  • Cases & Projects
  • Developers
About
  • Contact
Legal
  • Terms of Service
  • Privacy Policy
  • Cookie Policy
Edge-Based Real-Time Image Classification Platform with Intel NCS2 Integration
  1. case
  2. Edge-Based Real-Time Image Classification Platform with Intel NCS2 Integration

This Case Shows Specific Expertise. Find the Companies with the Skills Your Project Demands!

You're viewing one of tens of thousands of real cases compiled on Many.dev. Each case demonstrates specific, tangible expertise.

But how do you find the company that possesses the exact skills and experience needed for your project? Forget generic filters!

Our unique AI system allows you to describe your project in your own words and instantly get a list of companies that have already successfully applied that precise expertise in similar projects.

Create a free account to unlock powerful AI-powered search and connect with companies whose expertise directly matches your project's requirements.

Edge-Based Real-Time Image Classification Platform with Intel NCS2 Integration

onix-systems.com
Manufacturing
Healthcare
Environmental Services
Education
Retail

Challenges in Industrial Image Classification

Industrial enterprises face complex image classification challenges impacting operational efficiency, product quality, and safety. These include defect detection, quality control, component recognition, anomaly detection, inventory management, and barcode verification. Current solutions suffer from cloud dependency, latency issues, data privacy risks, and high infrastructure costs.

About the Client

Industrial enterprise specializing in electric drive systems development seeking AI-driven operational optimization

Project Goals for Edge-Based Image Classification

  • Enable real-time image classification without cloud dependency
  • Ensure data privacy through edge computing implementation
  • Reduce infrastructure costs by eliminating cloud processing requirements
  • Provide scalable solution for multiple industries including manufacturing, healthcare, and retail

Core System Functionalities

  • Real-time image classification using Intel NCS2 edge devices
  • Model optimization with OpenVINO toolkit integration
  • User feedback mechanism for adaptive model improvement
  • Multi-industry use case support (manufacturing QA, medical imaging, wildlife tracking, retail inventory)
  • Automatic hardware detection and task routing to NCS2

Preferred Technologies for Image Classification Platform

Python
OpenVINO
MobileNet
TensorFlow
FastAPI

Required System Integrations

  • Intel Neural Compute Stick 2
  • OpenVINO Toolkit

Critical Non-Functional Requirements

  • Sub-100ms processing latency for real-time classification
  • Edge-based data processing with zero cloud transmission
  • Horizontal scalability across 1000+ edge devices
  • Cross-platform compatibility with Windows/Linux
  • Model accuracy retention post-optimization

Expected Business Impact of Edge AI Implementation

The solution will reduce image processing latency by 80% through edge computing, eliminate cloud data transmission costs, and enable scalable deployment across multiple industries. Manufacturers will achieve 30% faster quality control processes, healthcare providers will gain instant diagnostic support, and retailers will benefit from automated inventory management while maintaining strict data privacy compliance.

More from this Company

Development of Integrated Digital Platform for CNC Machine Management and E-commerce
Interactive VR Museum Gamification Platform for Cultural Heritage Engagement
Development of a Scalable Fantasy Gaming Platform for Reality TV Enthusiasts
Development of a User-Centric Beauty Services Booking Platform with Enhanced UX
Development of Gamified Language Learning App with Child-Centric UX/UI and Brand Identity