AI-driven Disaster Management for a sustainable future

Key challenges

As a startup in the environmental industry, our client aimed to develop a long-term Disaster and Disruption Management System (DDMS) for its customers using Satellite Imagery, Weather Data, and Analytics

Manual analysis and decision-making processes followed in the industry hindered the ability to leverage advanced analytics for outage prediction and resource allocation in their DDMS. Our customer partnered with us to transform this process using Automation

Without Automation, the scalability and real-time updates of data in the DDMS posed challenges, limiting the effectiveness in vegetation and disaster management

Client in spotlight

Our client is dedicated to creating a greener, cleaner, and safer planet, is at the forefront of climate-resilient infrastructure and sustainable practices. Their products have garnered global recognition, and they were named America's Best Startup Employers in 2023 by Forbes. Leveraging Data Engineering and AI, their mission is to utilize satellite imagery, real-time weather data, and vegetation data to build an agile and user-friendly platform for vegetation management and disaster and disruption management.

Unlocking Digital success

Ideation

Creating a comprehensive vegetation management system that utilizes historical data and weather patterns to predict bushfires to develop preventive measures and strategies.

Our approach

Implemented advanced techniques such as satellite image processing and Data Analysis to identify areas at risk and detect vegetation near electrical wires.

Outcomes

Proactive risk mitigation by reliable conclusions, reports, and recommendations that facilitated proactive decision-making, and improved overall disaster and disruption management.