Growing Safety and Compliance Pressure

Australia’s WHS framework requires businesses to eliminate workplace risks where reasonably practicable, or minimise them where elimination is not possible. AI powered security systems can support existing safety measures by detecting risks such as missing PPE, restricted-zone entry, unsafe behaviour, smoke or fire and alerting teams when action may be required.

Rising Security Complexity and Monitoring Costs

As businesses operate more cameras, sites and monitored areas, relying on operators to continuously watch every video feed becomes difficult to scale. Security automation solutions can analyse video continuously, identify relevant events and direct operator attention to incidents that require investigation or response.

Together, these pressures are pushing physical security from continuous manual monitoring towards more proactive, AI-assisted operations.

For many businesses, adopting AI in physical security does not mean replacing the existing camera network. AI can add an intelligence layer to compatible video infrastructure, progressively moving cameras from simply capturing footage to identifying objects, understanding activities and recognising situations that may require action. This reflects the broader evolution of physical security AI from motion and object detection towards activity and contextual understanding.

Image and Object Analysis

The first layer helps cameras understand what is in the scene. Computer vision can identify and classify people, vehicles, equipment and other visible objects, turning raw footage into information that security and operations teams can use.

Typical applications include:

• People, vehicle and object detection

• PPE and safety gear detection

• Smoke and visible fire detection

• Licence plate recognition

• Parcel or unattended-object detection

• People and vehicle counting

In practice, the same capability can support very different business needs. A warehouse might use it to identify workers without required PPE, while a secure facility could detect an unauthorised vehicle entering a controlled area.

The value is not simply better object recognition. AI powered security systems can continuously monitor predefined visual conditions and bring relevant events to operators, improving monitoring consistency while reducing the amount of routine footage that needs human attention.

Behaviour and Activity Analysis

The next layer adds an understanding of what people and objects are doing over time.

By combining detection with movement, location, duration and interaction, AI video analytics can identify activities such as:

• Restricted-zone entry or line crossing

• Loitering and excessive dwell time

• Tailgating

• Wrong-way movement

• Falls or prolonged inactivity

• Unsafe pedestrian and vehicle interactions

• Objects being left behind, removed or moved

This distinction matters. Detecting that a person is present may have little security significance on its own. Detecting that the person has crossed into a restricted area, remained there unexpectedly or followed another person through a controlled entrance provides much more useful operational context.

Behaviour analysis therefore shifts monitoring from watching camera feeds to monitoring activities. Security teams can spend less time looking for events and more time verifying and responding to the activities that actually require attention.

Contextual and Anomaly Analysis

More advanced AI goes beyond predefined objects and behaviours to consider whether an event is unusual or significant within its specific environment.

This may involve analysing:

• Activity occurring at an unusual time or location

• Changes from expected movement patterns

• Unusual interactions between people, vehicles or equipment

• Multiple risk conditions occurring together

• Site-specific safety or security scenarios

Context is important because the same event can mean different things in different environments. A person standing still for several minutes may be completely normal in a reception area but unusual beside a restricted loading zone after operating hours.

Context-aware analysis can also combine multiple visual signals. Instead of generating separate alerts for person detected, PPE missing and restricted zone entered, an advanced system can identify the more meaningful situation: a worker without required PPE has entered a hazardous area.

This is where AI can support more tailored intelligent video monitoring. Detection can be configured around the risks, workflows and operational rules of a particular site rather than relying only on generic analytics.

KPS's Agentic Vision, for example, is designed to work with existing cameras and IoT infrastructure, continuously detect safety, security, compliance and operational incidents, and trigger configurable response workflows.

AI is shifting physical security from passive recording towards earlier detection, better situational awareness and more focused response. For Australian businesses, adding AI to compatible existing camera infrastructure can also be a more cost-efficient way to improve security capabilities without replacing an entire surveillance system.

For businesses considering these capabilities, explore KPS physical security solutions to see how AI and video technologies can be applied across different operating environments.

Start with the risks and operational problems the system needs to address, then assess whether the solution can work with your existing infrastructure. Businesses should also consider detection accuracy in real site conditions, integration capability, privacy and security requirements, workflow flexibility and how easily the system can adapt as operating needs change.