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Real-time Vehicle Tracking and Video Analytics Platform
  1. case
  2. Real-time Vehicle Tracking and Video Analytics Platform

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Real-time Vehicle Tracking and Video Analytics Platform

neurosys.com
Security
Logistics
Agriculture
Traffic Management

Challenge

Current video surveillance systems often lack real-time, intelligent object detection and tracking capabilities, limiting their effectiveness in scenarios requiring proactive monitoring, automated analysis, and rapid response. Existing solutions may be resource-intensive, difficult to scale, or lack flexibility to adapt to diverse environments and object types.

About the Client

NeuroSYS is a technology company specializing in AI-powered video analytics solutions for various industries, focusing on real-time monitoring, object detection, and intelligent insights.

Goals

  • Develop a scalable and robust real-time vehicle tracking system.
  • Implement accurate and reliable object detection and tracking using deep learning.
  • Enable flexible deployment across various platforms (web, server-client, peer-to-peer).
  • Provide a versatile platform adaptable for tracking diverse objects beyond vehicles.
  • Offer a REST API for seamless integration with other systems.

Functionality

  • Real-time vehicle and object detection and tracking.
  • Support for multiple video stream sources (IP cameras, webcams, video files).
  • Flexible processing modes (single frame, continuous stream analysis).
  • REST API for accessing detection and tracking data.
  • WebRTC-based peer-to-peer livestreaming with low latency.
  • Server-client livestreaming architecture for reliable streaming to multiple clients.
  • Support for various object types (vehicles, people, animals, plants).
  • User-defined detection directions.

Technologies

OpenCV
Multiprocessing
AsyncIO
TypeScript
Redux
ReduxSaga
StyledComponents
WebRTC
HLS

Integrations

  • IP Camera Systems
  • Web-based video platforms
  • Existing security systems

Non-Functional Requirements

  • Low latency (target: 450ms for single-frame processing, ~2 seconds for livestreaming).
  • Scalability to support multiple concurrent streams and users.
  • High reliability and availability.
  • Security to protect video data and API endpoints.
  • Performance to handle high-resolution video streams.

Business Impact

This project will enable clients to enhance security, improve traffic management, optimize agricultural monitoring, and gain valuable insights from video data. The real-time capabilities and flexible architecture will provide a competitive advantage by offering a more proactive and adaptable video analytics solution. Improved efficiency and faster response times will lead to cost savings and enhanced operational effectiveness.

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