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Transforming Flood Mapping with UiPath Apps and RPA

Client Background

A leading organization responsible for flood mapping and disaster management faced a critical challenge in efficiently processing flood map requests. Traditionally, this involved manual data entry and coordination between users and systems. To streamline this process, improve accuracy, and expedite flood map retrieval, the organization embraced UiPath Apps and Robotic Process Automation (RPA).

Business Challenge

The organization encountered several challenges in its flood mapping process:

  • Manual Data Entry: Users manually input flood map requests, a time-consuming and error-prone process.

  • Data Retrieval: The flood maps needed to be retrieved from the FEMA portal, requiring manual navigation and data entry.

  • Information Sharing: Once flood maps were acquired, they needed to be quickly shared with the Line of Business (LOB) for critical decision-making.

  • Efficiency: The process was slow and resource-intensive, leading to delays in disaster response and mitigation.

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Solution Overview

To address these challenges, the organization implemented a solution that combined UiPath Apps and RPA to automate the flood map retrieval process. The workflow included the following steps:

  • UiPath Apps Form: Users filled out a form created using UiPath Apps to submit flood map requests. This form was connected to an RPA queue for seamless integration.

  • Transaction Initiation: Once a transaction was added to the queue, the RPA bot was triggered to commence automation.

  • FEMA Portal Access: The bot navigated to the FEMA portal, accessed the Flood Lookup section, and entered the provided address or coordinates.

  • Flood Map Retrieval: The bot retrieved the flood map view of the specified area and captured an image of it.

  • Image Sharing: The captured flood map image was shared with the LOB for rapid decision-making and further actions.



The implementation of UiPath Apps and RPA for flood map retrieval delivered substantial benefits to the organization:

  • Accuracy: Automation improved data accuracy, resulting in a remarkable 98% accuracy rate in flood map retrieval.

  • Efficiency: The process was expedited, enabling rapid access to critical flood maps during disaster response.

  • Resource Optimization: Human resources could focus on higher-level decision-making instead of manual data entry and retrieval.

  • Enhanced Collaboration: Real-time sharing of flood map images with the LOB improved decision-making and collaboration.


Leveraging UiPath Apps and RPA, the organization revolutionized flood map retrieval, achieving an impressive 98% accuracy rate. This automated solution demonstrated the power of automation in simplifying complex tasks involving dynamic data and user interactions. The enhanced accuracy and efficiency facilitated faster decision-making during critical disaster scenarios.

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