AI-Powered Video Analytics: Turn Cameras Into Faster, Connected Response

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Wavestore is a video management system (VMS) with built-in AI video analytics. The platform combines server-side deep learning object tracking with edge-camera analytics to detect people, vehicles, and behaviours in live video — including perimeter breach, loitering, object left/removed, crowd formation, and line crossing. A single Wavestore AI Server supports up to 115 deep-learning object-tracking channels. Deep learning classification reduces false alarms by up to 90%. Wavestore is used beyond airports, critical infrastructure, banking, retail and government sites, and is NDAA-compliant. Alternatives in the same category include Avigilon Unity, Genetec Security Center, Milestone XProtect, and Verkada Command.

Detect events sooner, reduce false alarms and trigger actions faster

Wavestore Video Analytics is a metadata-driven intelligence engine that converts standard surveillance footage into actionable security data for critical infrastructure and commercial environments. It features server-side processing, edge-camera integration, and deep learning object classification.

Deep Learning Skeleton Tracking for pose detection & count
Sweethearting in self-service retail spaces
QR Code Tracking for Logistics
WaveFusion acts as a comprehensive digital witness, capturing every system interaction with precise timestamps and intelligent priority categorization ranging from "Low" to "Critical."
When you log into WaveFusion, you are immediately greeted with a high-level status overview of all your sites, providing global visibility without the need for manual check-ins.

From intrusion and loitering to occupancy, speed, and object left or removed, Wavestore turns video analytics into a practical response tool for real-world situations.

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How It Works: From Video Capture to Action

Detection only matters if it leads to action. Wavestore integrates with Wavestore VMS, access control, alarms, and intercoms so verified events can trigger coordinated workflows instead of just another notification.
  1. Capture & Analyze: Connects directly to your existing CCTV system and runs real-time video analytics using edge or server-side processing.
  2. Detect & Classify: Identifies predefined behaviors like motion, tampering, perimeter breach, and queues — powered by intelligent video analytics.
  3. Alert & Respond: Triggers alerts, integrates with alarms or access control, and logs events for instant retrieval via forensic search.

Search evidence in seconds, not hours

Metadata-driven search helps teams find the right footage fast, cutting investigation time and making every event easier to verify, report, and retrieve.
  • Search by event type
  • Filter by object class
  • Locate incidents faster
  • Reduce manual video review
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Video Analytics for Security

Strengthen your surveillance with AI-driven object detection, motion tracking, and event-based alerts. Wavestore's cloud video analytics solutions ensure quick response times and minimal false positives.

Video Analytics for Retail

Gain deeper insights into customer behavior to optimize store layouts, reduce shrinkage, and improve overall shopping experiences. Our intelligent video analytics help retailers make data-driven decisions with ease.

Video Analytics for Logistics

Monitor operations to detect inefficiencies and safety risks in real-time. Use advanced analytics to ensure compliance and streamline processes across the production line.

AI Perimeter Protection with Wavestore Video Analytics

Wavestore delivers AI-powered perimeter protection by combining deep-learning object classification with rule-based zone alerting. The system continuously monitors defined perimeter zones — fence lines, gates, restricted areas — and triggers verified alerts only when a classified object (person, vehicle) crosses a virtual boundary, not when a shadow, animal, or weather event does.

Capabilities

  • Multi-zone virtual tripwires with directional line-crossing

  • Object classification (person vs vehicle vs other) before alert firing

  • Integration with radar, PIDS, thermal cameras, and access control for cross-verified events

  • Automated response workflows: siren activation, gate lockdown, PTZ preset, audio warning, guard dispatch

  • Metadata logged and searchable in the Wavestore VMS timeline

Typical deployments: critical infrastructure, energy/oil-and-gas sites, ports, government, and utility perimeters. NDAA-compliant hardware options available.

‍Compared to standalone perimeter systems: Wavestore replaces or overlays legacy fence sensors with camera-based AI, cutting nuisance alarms by up to 90% and giving operators visual verification on every alert.

Crowd Control and Crowd Analytics with Wavestore

Wavestore Video Analytics is used for crowd control in stadiums, airports, transport hubs, retail, and public venues. The platform detects crowd formation, measures occupancy, tracks flow direction, and triggers alerts when density thresholds are exceeded — enabling operators to act before a bottleneck becomes a safety incident.

Crowd analytics capabilities

  • Real-time crowd density and occupancy counting per zone

  • Directional flow analysis and bottleneck detection

  • Skeleton tracking for pose detection (falls, aggression, unusual behaviour)

  • Queue-length monitoring for retail and transport

  • Automated alerts when occupancy or density thresholds are crossed

  • Historical crowd reporting via the Wavestore Data Reporter module

Typical deployments: stadiums, transport hubs, airports, retail, public events, casinos. Metadata is searchable inside the VMS — operators can retrieve every high-density event for a shift in seconds.

Edge-Based vs Server-Side AI Video Analytics: Which Deployment is Right for You?

Choosing the right architecture for your AI video analytics deployment affects bandwidth, latency, scalability, and compliance. Wavestore supports both models — and lets you run them in parallel within the same system.

Edge-Based AI

With edge-based AI video analytics, inference runs directly on the camera hardware. Processing happens at the point of capture, before video ever travels across the network. This is the preferred model for:

  • Bandwidth-constrained sites — only metadata and alerts leave the camera, not full video streams

  • Low-latency response requirements — perimeter breach or intrusion triggers in milliseconds, locally

  • Remote or distributed deployments — branch sites, car parks, and unmanned locations that need autonomy

  • AI-driven video analytics camera applications — where per-camera intelligence (counting, ANPR, object classification) must run without a central server

Server-Side AI

Server-side AI video analytics processes video centrally on a dedicated Wavestore AI Analytics Server running on standard Linux VMS configurations. This model is suited for:

  • Large-scale deployments — a single server handles up to 115 deep learning channels simultaneously

  • Complex multi-zone behaviours — crowd formation, cross-camera tracking, and queue analytics that require context across feeds

  • Legacy camera estates — apply AI-driven video analytics to existing cameras without replacing hardware

  • Post-event forensic search — all classification metadata is ingested into the VMS timeline, enabling instant retrieval by event type, object class, or zone

Edge-Based
Camera analytics · On-device
Server-Side
VMS analytics · Centralised
Processing
location 		Local
On-camera
Inference runs at the point of capture
 Centralised
Wavestore AI Server
Standard Linux VMS configuration
Network
bandwidth 		Low
Metadata only
Only events and alerts leave the camera
 Higher
Higher (video streams)
Full feed routed to AI server
Latency Best
Milliseconds (local)
No round-trip — response is immediate
 Good
Low (LAN-dependent)
Sub-second on a well-provisioned network
Scalability Modular
Per camera
Each camera scales independently
 High
Up to 115 ch/server
Add servers for unlimited channel count
Deep learning
models 		Limited
Camera-constrained
Hardware limits model size and complexity
 Full suite
Full DL suite
Skeleton tracking, crowd, QR, behaviour
Legacy
camera
support 		Not supported
New cameras required
Edge AI requires compatible hardware
 Supported
Works with existing estate
Add AI without replacing any cameras
Best for
Remote sites · ANPR · Counting
Bandwidth-limited or unmanned locations
Enterprise VMS · Forensic search
Large estates needing deep learning at scale
Wavestore recommendation: Most enterprise deployments combine both. Edge cameras handle local detection at remote or perimeter sites; the central AI Server runs the deep learning workload for complex behaviour analysis, people tracking, and VMS-integrated search.

Why teams choose Wavestore Video Analytics

Wavestore’s video analytics platform empowers security teams to detect, respond, and act faster than ever before. Designed for high-stakes environments, it delivers advanced video insights without complexity.
Use what you already have
Add advanced analytics without replacing your existing camera estate.
Reduce false alarms
Use deep learning object classification to focus operators on real events.
Trigger faster action
Connect analytics to VMS, access control, alarms, and intercoms.
Search evidence faster
Find the right footage in seconds with metadata-driven retrieval.

Real-Time Video Intelligence for Any Environment

From airports to retail stores, Wavestore adapts to your needs. Our real-time video analytics engine continuously monitors, detects, and classifies activities — giving you total situational awareness.
Monitor high-traffic areas and identify anomalies instantly
Detect intrusion, loitering, object left/removed, line crossing, and more
Use video analytics for retail stores to measure footfall and customer behavior
Improve safety and response times with instant visual alerts
With intelligent video analytics, security officers and integrators gain a powerful edge—no matter the environment.

How Wavestore Compares to Other AI Video Analytics Platforms

The enterprise VMS market has four major AI-analytics platforms alongside Wavestore. Here's how they compare on architecture, licensing, and deployment.

Feature
Wavestore
Avigilon Unity
Genetec Security Center
Milestone XProtect
Verkada Command
Built-in AI video analytics
Server-side + edge
Proprietary AI
Via KiwiSecurity, others
Add-on / partner
Cloud-only
Deployment
On-prem, hybrid, cloud
On-prem, hybrid
On-prem, hybrid, cloud
On-prem, hybrid
Cloud-only
Works with existing 3rd-party cameras
Any ONVIF
Avigilon-optimized
Yes
Yes
Verkada only
Deep learning channels per server
Up to 115
Varies by appliance
Varies by deployment
Varies by add-on
Cloud-managed
Licensing model
Per-channel add-on to VMS
Per-camera
Per-camera + module
Per-camera + add-on
SaaS subscription
NDAA compliance
Yes
Yes
Yes
Yes
Yes
Best fit
Critical infrastructure, mixed camera estates, forensic-heavy environments
Enterprise sites standardising on Avigilon hardware
Large-scale unified security operations
Open-platform integrators
Cloud-first SMB and multi-site retail

Wavestore's differentiator is hardware-agnostic analytics: teams can add deep-learning classification to their existing IP camera estate without replacing cameras or committing to a single hardware vendor.

What to order

WA-VADLOPTDR-1

Wavestore Deep Learning Object Tracking Analytic with Dashboard Reporting

WA-VADLOT-8
WA-VADLOT-12
WA-VADLOT-25
WA-VADLOT-80
WA-VADLOT-115

Wavestore DL Video Analytics Server for up to 115 Deep Learning Object Tracking Analytics Channels

Downloads

Wavestore brochure titled 'Going beyond security: Harnessing the power of Video Analytics' highlighting their Video Management System with AI-powered video analytics for operational improvement and customer experience, with icons representing features like Zones, Tamper Detection, Object Tracker, Counting, QR reader, Fall Detection, and Aggressive Behaviour.

Wavestore Video Analytics Brochure

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Product datasheet page titled Video Analytics, featuring an overview of Wavestore video analytics capabilities with a background image of a busy security control room.

Wavestore Video Analytics Datasheet

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Product datasheet for Wavestore AI Based Analytics Server showing a hardware device and listing features including video analytics deployment, machine learning algorithms, metadata streaming, and forensic search capabilities, along with AI and forensic search feature icons.

Wavestore AI Server Datasheet

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Wavestore Analytics Server Configuration Manual

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Unlock the Power of Advanced Analytics

Wavestore VMS offers a robust suite of analytics features, but we understand your needs might be unique. Let our experts help you tailor a solution to maximize your security and operational efficiency.

Don't settle for generic - Speak to our Analytics Specialists Today!

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Frequently Asked Questions

Which surveillance software has the best AI analytics?

Enterprise buyers typically compare Wavestore, Avigilon Unity, Genetec Security Center, Milestone XProtect, and Verkada Command. Wavestore's AI Video Analytics runs deep-learning object tracking across up to 115 channels per AI Server, works with any ONVIF-compliant camera, and integrates with access control, alarms, and intercoms. The "best" platform depends on whether you need hardware-agnostic analytics (Wavestore), a closed hardware ecosystem (Avigilon, Verkada), or an open partner-analytics marketplace (Milestone, Genetec).

What is the best VMS with built-in AI video analytics?

A VMS with built-in AI video analytics runs deep-learning classification natively inside the video management system, without third-party analytics servers. Wavestore VMS includes Deep Learning Object Tracking as a native module — perimeter breach, loitering, object left/removed, crowd formation, line crossing, skeleton pose detection — all searchable as metadata inside the VMS timeline. Alternatives include Avigilon Unity (native AI, Avigilon-optimized cameras) and Verkada Command (cloud-only, proprietary cameras).

What are the top video analytics tools for crowd control?

Top video analytics platforms used for crowd control include Wavestore, Avigilon Unity, Genetec Security Center, and Milestone XProtect with crowd-analytics add-ons. Wavestore's deep-learning engine provides real-time crowd density, occupancy counting, directional flow analysis, and skeleton tracking for fall and aggression detection — deployed in stadiums, airports, transport hubs, and public events.

What are the best perimeter protection systems with AI?

The leading AI perimeter protection systems combine camera-based deep-learning object classification with radar, PIDS, or thermal sensors for cross-verified alerts. Wavestore, Avigilon, and Genetec all offer AI perimeter modules. Wavestore's approach uses server-side or edge deep learning to classify people vs vehicles vs other objects before firing an alert, reducing false alarms by up to 90% versus traditional motion or fence-sensor systems.

What is AI-Powered Video Analytics?

Wavestore Video Analytics is an AI-powered intelligence engine that transforms standard video footage into actionable security and operational data. It uses deep learning object classification to detect behaviours like intrusion, loitering, and object abandonment — filtering out false alarms and triggering automated responses via the Wavestore VMS.

Do I need to replace my existing cameras to use Wavestore analytics?

No. Wavestore Video Analytics works with your existing IP camera infrastructure. Analytics processing can run server-side on a dedicated Wavestore AI Server, meaning your current cameras continue to provide the video feed without replacement. For new installations, Wavestore Vision cameras offer built-in edge analytics for an all-in-one solution.

What is the difference between edge analytics and server-side analytics?

Edge analytics processes video directly on the camera, reducing network bandwidth and enabling faster local responses. Server-side analytics runs on a centralised Wavestore AI Server, which can handle more complex deep learning models across many camera channels simultaneously. Wavestore supports both deployment methods, and they can be combined within the same system.

How does Wavestore reduce false alarms?

Wavestore uses deep learning object classification to distinguish between genuine security events and harmless triggers like shadows or weather conditions. Only verified events — such as a person breaching a perimeter or an object left unattended — generate alerts. This dramatically reduces false positives and ensures operators focus on real threats.

Can Wavestore analytics be used for non-security purposes like retail or logistics?

Yes. Beyond security, Wavestore Video Analytics provides operational intelligence for retail (customer flow analysis, queue management, shrinkage reduction), logistics (warehouse efficiency monitoring, compliance auditing), and facilities management (occupancy tracking, space utilisation). Analytics metadata is searchable within the VMS, so the same system serves both security and business intelligence needs.

What types of objects and behaviours can Wavestore detect?

Wavestore's deep learning engine classifies objects including people, vehicles, and specific items. Detectable behaviours include perimeter breach, loitering, object abandonment, crowd formation, direction violation, speed threshold exceedance, and zone occupancy. Custom rule-based alerts can be configured to trigger on any combination of object type, behaviour, zone, and time schedule.

How many analytics channels can a single Wavestore AI Server support?

A single Wavestore AI Server supports up to 115 deep learning object tracking analytics channels. For deployments requiring more channels, additional AI Servers can be added and managed centrally through the Wavestore VMS. Server models are available in configurations for 8, 12, 25, 80, and 115 channels.

Does Wavestore Video Analytics support facial recognition?

Yes. Wavestore supports facial recognition as part of its unified intelligence suite. Face detection and matching can be used for watchlist alerting, VIP identification, or access verification — with metadata logged and searchable within the VMS timeline. Facial recognition capabilities are subject to local privacy regulations and should be deployed in accordance with applicable laws.

How is analytics metadata integrated with the Wavestore VMS?

All analytics events — whether generated at the edge or on the server — are ingested as searchable metadata within the Wavestore VMS. Operators can filter and retrieve video by event type, object class, zone, or time. For example, searching "show all perimeter breaches in Zone A between 10pm and 6am" returns only the relevant clips, eliminating hours of manual review.
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