Real-Time video Analytics Engine is a Platform that utilizes advanced image processing algorithms to turn video into actionable intelligence. Large Scale Video Processing is the greatest challenge holding a great potential for Analytics. Real-Time Video Analytics can be used for Monitoring Traffic Control, Retail Store Monitoring, Surveillance and Security. 


XenonStack's Real-Time Video Analytics Platform is real-time, low cost, accurate analysis of live videos using Open Source Big Data Technologies including OpenCV, Apache Kafka, Apache Spark, HDFS, Tensor Flow, and Amazon S3. 



Business Challenge


  • Traditional Computer Vision System suffers from a limitation, that a server along with CV library collects and process the data at the same time. A failure in the server  causes loss of Streaming Video Data.

  • Detecting a node failure and switching the processing to another node may result in fragmentation of data.

  • Major challenge relies on running an image processing algorithms in a dynamic environment.


Thus managing and efficiently analysing this data brings us with a challenge to build a system which can eliminate the addressed problems.


Solution Offered


XenonStack Team came up with a solution to perform real-time video analytics backed by open source big data technologies.


The system is divided into three main components -


  • Video stream collector

  • Stream data buffer

  • Video stream processor

Looking For More Details

Download Now




Apache Spark, Apache Kafka, OpenCV, Amazon S3, HDFS, Apache Zookeeper, Tensor Flow

Transforming to a Data-Driven Enterprise

Talk to Experts for Assessment on Infrastructure Automation,  
DevOps Intelligence, Big Data Engineering and Decision Science

Reach Us
Success Your Information has been submitted successfully. We will get back to you soon.
Data not sent. Error Occuered on Server Side.

Real Time IoT Analytics

Platform with
Artificial Intelligence