Objectives

The primary objective of our collaboration with GRAF was to test the efficacy of FireAI in real-world firefightingscenarios. We aimed to:

• Enhance situational awareness for firefighting teams
• Improve the accuracy and speed of fire detection and monitoring, especially at night.
• Reduce response times and increase the safety of firefighting personnel.

Implementation

The collaboration involved deploying Fire software in various field tests conducted by GRAF. Our technology, equipped with advanced AI algorithms and high-resolution cameras, was integrated into drones to provide real-time data and insights during firefighting operations.

1.  Field Testing: GRAF conducted multiple field tests to evaluate the performance of FireAI. These tests included controlled burns and real fire incidents where our technology was used to monitor fire spread, identify hotspots, and provide real-time data to the command centre via a .kml file export.
2. Data Collection & Analysis:During the tests, the Fire software collected vast amounts of data, which was then analysed to assess the accuracy and reliability of the system. The data helped in fine-tuning the algorithms to improve detection capabilities and reduce false positives.
3. Training and Support: We provided comprehensive training to GRAF’s firefighting teams on using the Fire Software.This included hands-on sessions and detailed manuals to ensure that the teams could effectively operate the technology in high-pressure situations.

Outcomes

The collaboration with GRAF yielded significant positive outcomes, demonstrating the potential of FireAI in enhancing firefighting operations.

1. Improved Situational Awareness: The software provided real-time aerial views and data, allowing firefighting teams to make informed decisions quickly. The technology’s ability to detect and monitor fire spread accurately helped in strategising and deploying resources more effectively.
2. Increased Safety: By providing real-time data and identifying hotspots, the software reduced the risk to firefighting personnel. Teams could avoid dangerous areas and focus their efforts where they were needed the most.
3. Enhanced Efficiency: The use of the software led to faster response times and more efficient firefighting operations. The technology’s ability to provide accurate data in real-time meant that teams could act swiftly and decisively.
4. Positive Feedback: GRAF provided positive feedback on the performance of the fire software,highlighting the accuracy, reliability, and ease of use. The collaboration has paved the way for further enhancements and a potential wider adoption of the technology in firefighting operations.

The collaboration with GRAF has been a significant milestone for Robotto, showcasing the potential of our AI-driven technology in real-world firefighting scenarios. The successful implementation and positive outcomes have reinforced our commitment to developing innovative solutions that enhance emergency response capabilities and ensure the safety of personnel.