FIND-911 aimed to harness the unparalleled flexibility, elasticity, and availability offered by AWS to meet the ever-evolving demands of search and rescue operations. Through this partnership, FIND-911 envisioned an infrastructure robust enough to cater to its present needs and scale seamlessly for future requirements. Central to this vision was the deployment of an MVP during Phase 2, built atop the AWS setup from Phase 1, encapsulating the core features of the existing system and laying the foundation for future AI/ML model integrations.
Search and rescue missions demand speed, accuracy, and adaptability. With the sheer volume of data collected through drones and ground robots, processing this data in real-time to make mission-critical decisions becomes a daunting task. Furthermore, the vast variety of data, ranging from images to videos, requires a streamlined and organized approach for efficient processing and analysis. Achieving real-time data feed from the sensors and effectively utilizing AI/ML for refined data analysis posed significant technical and operational challenges.
Cloud303's engagements follow a streamlined five-phase lifecycle: Requirements, Design, Implementation, Testing, and Maintenance. Initially, a comprehensive assessment is conducted through a Well-Architected Review to identify client needs. This is followed by a scoping call to fine-tune the architectural design, upon which a Statement of Work (SoW) is agreed and signed.
The implementation phase kicks in next, closely adhering to the approved designs. Rigorous testing ensures that all components meet the client's specifications and industry standards. Finally, clients have the option to either manage the deployed solutions themselves or to enroll in Cloud303's Managed Services for ongoing maintenance, an option many choose due to their high satisfaction with the services provided.
To navigate these challenges, the following solution was conceptualized and implemented:
- Creation of a webpage-based interface with cloud hosting and processing on AWS.
- Backend databases were developed alongside S3-based organizational data structures.
- The introduction of AWS Cognito ensured a fortified security layer.
- Fargate was integrated using celery to enable elastic compute capabilities, ensuring efficient backend processing.
User Interface Enhancement
A comprehensive user interface was crafted, allowing:
- User access controls and organization creation.
- Case and search criteria specifications, including color and thermal attributes.
- Facilitating facial and object recognition.
- Analytical review of marked images for refined processing.
Backend Processing Upgrades
- Image streams were segmented into individual images and stored on S3.
- Parallel analysis was conducted using AWS elastic compute, marking images for priority review.
- Novel algorithms were introduced to detect color anomalies in images.
- AWS Simple Notification Service was utilized to send real-time progress/status alerts.
- Webpages were developed using React, based on the Figma prototype.
- Sample search data execution allowed iterative improvements in UI and search models.
- Final deployment to production servers ensured seamless user experience.
Our project with Climup Tech was a challenging yet fulfilling venture that required an intricate mesh of AI, machine learning, and cloud services. Using Amazon SageMaker, AWS Rekognition, and AWS Textract, we were able to develop an efficient, automated, and scalable solution for assessing fire hazards.
Meeting New Insurance Requirements
The AI/ML solution, jointly developed by Climup Tech and Cloud303, successfully enabled Climup Tech to assess fire hazards to enable insurance companies to comply with the new insurance requirements. The system's high accuracy, automation, and scalability made it a valuable tool for insurance companies and their clients.
Leveraging AWS for a Cutting-Edge Solution
By leveraging AWS services like Amazon SageMaker, AWS Rekognition, and AWS Textract, Cloud303 was able to showcase their AI/ML expertise and build a robust, efficient, and scalable solution with Climup Tech. This collaboration enabled Climup Tech to help CA insurance companies to meet the stringent insurance requirements; it has positioned Climup Tech as pioneers in adopting cutting-edge AI/ML technologies for property risk assessment.
Attracting Insurance Companies
Furthermore, the system has enabled Climup Tech to attract insurance companies as potential clients. The solution's comprehensive features and seamless integration with existing workflows have made it attractive for insurance providers looking to automate and streamline their fire hazard assessment processes.
The partnership between Climup Tech and Cloud303 has successfully deployed an innovative AI/ML solution using AWS services to address the challenge of assessing the proximity of flammable materials to insured structures. The solution has not only helped Climup Tech clients comply with new insurance guidelines but has also enhanced Climup Tech’s reputation as a technology-driven company in the property management and insurance space.
Equipping for the Future
With Cloud303's expertise in AI/ML and the power of AWS services, Climup Tech is now better equipped to tackle the challenges of a dynamic insurance landscape while offering improved services to their clients.
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