SAIL: Surveillance Artificial Intelligence for Lifesaving
Tracks
Southport Room 2
| Tuesday, July 28, 2026 |
| 1:25 PM - 1:45 PM |
| Southport Room 2 |
Overview
Matthew Ingersole, Surf Life Saving NSW
Details
Three Key Learnings
1. Time critical impact: AI adds value by shortening the interval between a person in distress and a lifesaver response. Seconds can determine outcomes.
2. Human-AI partnership: SAIL enhances, rather than replaces, human decision making, integrating alerts into existing workflows while keeping operators in control.
3. Operational resilience: Success depends on technology that functions reliably in real world conditions, glare, weather, crowd density, and fatigue, and is measured by real rescues, not theoretical accuracy.
Speaker
Mr Matthew Ingersole
Chief Information Officer
Surf Life Saving NSW
SAIL: Surveillance Artificial Intelligence for Lifesaving
Abstract
SAIL (Surf AI for Lifesaving is Surf Life Saving NSW’s applied artificial intelligence program focused on one outcome: reducing the time between a person getting into trouble and a lifesaver intervening.
Drowning is a time critical problem. In dynamic coastal environments, human surveillance is constrained by distance, glare, crowd density, fatigue, and competing operational demands. SAIL addresses this gap by augmenting lifesavers with persistent, automated detection capability.
The program uses shore based camera systems combined with computer vision models trained on real surf conditions. These models continuously analyse the water to identify high-risk behaviours and patterns such as swimmers in rip currents, prolonged submersion, abnormal movement trajectories, and separation from flotation devices. When credible risk is detected, alerts are delivered to operational staff, enabling faster verification and response.
SAIL is not a standalone technology experiment. It is integrated into Surf Life Saving NSW’s operational ecosystem, including communications, incident management, and rescue workflows. Design priorities include reliability in harsh coastal conditions, explainable alerts, controlled false-positive rates, and usability under pressure. Performance is assessed against real rescue outcomes, not theoretical benchmarks.
The program is already delivering measurable impact, with multiple rescues initiated or accelerated by AI detections. These are operational interventions, not simulations.
SAIL demonstrates a pragmatic model for AI in public safety: narrowly scoped, outcome driven, ethically deployed, and embedded within human decision making to improve rescue capability and outcomes.
Drowning is a time critical problem. In dynamic coastal environments, human surveillance is constrained by distance, glare, crowd density, fatigue, and competing operational demands. SAIL addresses this gap by augmenting lifesavers with persistent, automated detection capability.
The program uses shore based camera systems combined with computer vision models trained on real surf conditions. These models continuously analyse the water to identify high-risk behaviours and patterns such as swimmers in rip currents, prolonged submersion, abnormal movement trajectories, and separation from flotation devices. When credible risk is detected, alerts are delivered to operational staff, enabling faster verification and response.
SAIL is not a standalone technology experiment. It is integrated into Surf Life Saving NSW’s operational ecosystem, including communications, incident management, and rescue workflows. Design priorities include reliability in harsh coastal conditions, explainable alerts, controlled false-positive rates, and usability under pressure. Performance is assessed against real rescue outcomes, not theoretical benchmarks.
The program is already delivering measurable impact, with multiple rescues initiated or accelerated by AI detections. These are operational interventions, not simulations.
SAIL demonstrates a pragmatic model for AI in public safety: narrowly scoped, outcome driven, ethically deployed, and embedded within human decision making to improve rescue capability and outcomes.
Biography
Matt is the Chief Information Officer at Surf Life Saving NSW, leading enterprise technology, data, and digital strategy for Australia’s largest volunteer emergency service organisation.
