Hailo AI - AI in Video Management Systems - Ep 3

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The future of Video Management Systems (VMS) lies in AI scalability, and in this episode, we explore how AI enhances VMS capabilities to meet modern-day security challenges. Traditional video analysis systems rely heavily on manual monitoring, leading to inefficiencies and high costs. AI changes this by automating video analytics, providing faster and more accurate results across multiple video feeds.

Through deep learning and neural networks, AI enables real-time object detection, gesture recognition, and density estimation, helping security personnel focus on what matters most. The impact is seen not only in surveillance but also in industries like retail, healthcare, and transportation, where video analytics play a crucial role in decision-making.

AI products, like the Hailo-8 Century PCIe card and Hailo-8 M.2 module, are transforming Video Management Systems (VMS) across various industries. By incorporating AI into video analytics, Hailo enables scalable, high-performance solutions that reduce manual intervention, enhance accuracy, and improve overall system efficiency.

Chapters

(00:00) Introduction to Scaling Up Video Management Systems

(00:15) What is a video management system?

(02:00) AI-powered video analytics are being rapidly adopted for VMS

(04:07) AI is fundamental for more accurate and safer VMS

(04:21) Detect - The first layer of AI video analytics

(06:10) Respond - The second layer of AI video analytics

(07:53) Analyze - The third layer of AI video analytics

(09:14) Hailo Provides Powerful & Scalable Solutions for VMS: Superior AI solutions

(10:21) Hailo AI Seamless integration into VMS

(11:35) Hailo AI Robust VMS Ecosystem

(12:06) Outro on VMS Solutions

Follow Us:

Hailo AI LinkedIn

Hailo AI Facebook

@Hailo_ai

https://www.youtube.com/@hailo2062

  continue reading

7 episoder

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Manage episode 459459354 series 3622405
Indhold leveret af Hailo AI. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Hailo AI eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

The future of Video Management Systems (VMS) lies in AI scalability, and in this episode, we explore how AI enhances VMS capabilities to meet modern-day security challenges. Traditional video analysis systems rely heavily on manual monitoring, leading to inefficiencies and high costs. AI changes this by automating video analytics, providing faster and more accurate results across multiple video feeds.

Through deep learning and neural networks, AI enables real-time object detection, gesture recognition, and density estimation, helping security personnel focus on what matters most. The impact is seen not only in surveillance but also in industries like retail, healthcare, and transportation, where video analytics play a crucial role in decision-making.

AI products, like the Hailo-8 Century PCIe card and Hailo-8 M.2 module, are transforming Video Management Systems (VMS) across various industries. By incorporating AI into video analytics, Hailo enables scalable, high-performance solutions that reduce manual intervention, enhance accuracy, and improve overall system efficiency.

Chapters

(00:00) Introduction to Scaling Up Video Management Systems

(00:15) What is a video management system?

(02:00) AI-powered video analytics are being rapidly adopted for VMS

(04:07) AI is fundamental for more accurate and safer VMS

(04:21) Detect - The first layer of AI video analytics

(06:10) Respond - The second layer of AI video analytics

(07:53) Analyze - The third layer of AI video analytics

(09:14) Hailo Provides Powerful & Scalable Solutions for VMS: Superior AI solutions

(10:21) Hailo AI Seamless integration into VMS

(11:35) Hailo AI Robust VMS Ecosystem

(12:06) Outro on VMS Solutions

Follow Us:

Hailo AI LinkedIn

Hailo AI Facebook

@Hailo_ai

https://www.youtube.com/@hailo2062

  continue reading

7 episoder

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