SERVICE D'INCENDIE RURAL DE NOUVELLE-GALLES DU SUD
« Il n'y a rien de comparable » : Plateforme de renseignement personnalisée sur les feux de brousse
15 000 incidents recensés. Propagation des incendies prévue en quelques minutes.
Kablamo built Athena, a custom bushfire intelligence platform for the NSW Rural Fire Service. Since launch, Athena has tracked over 15,000 fire incidents with 100% uptime, predicting fire spread within minutes and providing a 12-hour growth horizon.
“There's nothing like this, certainly in Australia.”
NSW Rural Fire Service, Bushfire Intelligence Platform
The Challenge
The 2019-20 Australian 'Black Summer' bushfire season burnt more than 18 million hectares of land. In the wake of the NSW Bushfire Enquiry, it became clear that the NSW Rural Fire Service needed a fundamental shift in how incident information is gathered, validated, and turned into operational decisions. The enquiry specifically recommended that RFS investigate new technologies and embrace AI to bolster its capabilities during future fire seasons.
Before Athena, critical context was scattered across systems, tools, and communication channels. Incident teams lost valuable time validating information during fast-changing events. Physical servers were unable to cope with incoming data volume during peak fire activity, and manual analysis was creating dangerous delays. Disconnected systems across agencies hindered coordination. Maintaining a shared operational picture at scale was nearly impossible.
The goal was not just to digitise existing processes. It was to create a new kind of capability: intelligence, not just information. RFS needed a platform that could ingest almost limitless data sources including satellite imagery, wind forecasts, and social media, and turn that data into actionable intelligence in minutes rather than hours.
The Approach
RFS collaborated with Kablamo to build and deploy Athena, a custom bushfire intelligence platform. Named after the Greek goddess of wisdom and strategy, Athena was developed over two years with a dedicated Kablamo team working alongside RFS operational and technical leadership.
Athena provides a common operating picture, bringing incident context, activity, and risk into a single interface so incident teams can coordinate and act on the best available signal. The platform displays predicted fire spread within minutes using Phoenix and Spark models, then supports analyst review and endorsement. It shows growth over the next 12 hours and highlights assets that may be threatened within the next two hours. The system displays comprehensive state maps integrating data from government, public, and private sources, including deployed firefighting vehicle and personnel locations, weather data and forecasts, wildfire history, RFS station locations, critical assets such as schools, hospitals, helipads, and aerial imagery.
Athena can also ingest geotagged social content as an additional intelligence source, flag items for human analysis, and learn over time from validation. The Social Intelligence module monitors social media platforms including Twitter to identify unreported fires through keyword tracking and geo-referenced image analysis. AWS Rekognition performs real-time image recognition from social media. The more the system is used operationally, the more it refines its predictions.
The platform covers the full incident lifecycle: preparation through short- and long-term hazard insights, detection with confidence metrics and risk ratings, response with predictions in minutes as impacts change, and recovery with operational records of decisions, assessments, and learnings. Built with a serverless architecture using AWS Lambda, RDS Aurora, S3, Fargate, Step Functions, and Event Bridge, with fire prediction engines from CSIRO (Spark) and Fire Prediction Services (Phoenix RapidFire). Development followed an agile sprint methodology with continuous iteration based on operational feedback.
A second phase introduced additional modules including an Aviation Safety Module that assesses minimum aircraft types required for specific fires, evaluates weather conditions and aircraft classifications, generates risk assessments with red/amber/green operating environment ratings, and integrates with the national aviation tasking system. A Risk Response Engine identifies coverage gaps and recommends proportional response based on fire conditions and available resources.
The Results
The platform launched in November 2022 with approximately 200 trial users during the 2022-23 fire season. Athena was used operationally from its first deployment, with incident controllers relying on its predictions and common operating picture during live fire events. Since going live, the platform has tracked over 15,000 fire incidents with 100% uptime despite continuous zero-downtime deployments to the production environment. Output predictions have been validated operationally across multiple fire seasons. The Social Intelligence module received a Best-in-Class Australian Good Design Award. The system was expanded to approximately 700 operational RFS personnel for the 2023-24 season, with plans to extend access to other firefighting and partner agencies.
Mobile Data Terminals are being rolled out to firefighting trucks, and Computer-Aided Dispatch integration with push-notification capabilities enables volunteer coordination in the field. The integration means that volunteer crews arriving at an incident can receive the latest predictions and threat assessments directly on their in-vehicle screens, rather than relying on radio updates alone. Discussions are underway with other firefighting agencies for system adaptation and integration, with potential for deployment beyond Australia.
Looking Forward
The collaboration between NSW RFS and Kablamo produced Athena, a platform that has changed how NSW approaches bushfire operations. By consolidating intelligence, prediction, and coordination into a single system, Athena replaced the fragmented tools that had limited decision-making speed during previous fire seasons.
The platform continues to evolve with each fire season. This project is featured on aws.amazon.com as a partner case study, and it has been recognised with a Best-in-Class Australian Good Design Award for the Social Intelligence module.
