ReportFarm
A dashboard design to incorporate generative AI and IoT systems.
Category
UI/UX
Tools
Miro, Adobe Illustrator, Figma
Location
Cary,
North Carolina
Role
Prototype builder
and Visual Designer
Project Information
This project was done during a SAS-sponsored studio with North Carolina State University. During this project development, we routinely met with SAS’s design team for feedback.
The Project was focused on a theoretical food company called Deca Foods pushing food sustainability through a digital dashboard that works with IoT (Internet of Things) systems and AI.
Setting our Direction
To explore more about different aspects of the interface, the class was split up to focus on simulating, visualizing, and reporting.
My group was tasked with creating an interface focused on how to provide a reporting experience that could reduce food sustainability.
Defining Reporting
Since our dashboard would be focused on reporting, it became clear that we had to clarify what “reporting” meant for our interface. This is because reporting could mean a finalized report, which is usually a moment in time, or a widget reporting live data on the dashboard.
Live
Live is the raw data being provided from sensors and systems shown to the user on the dashboard.
Predictive
Predictive reporting notifies the user of potential problems that could happen during operation.
Moment of Time
This type of reporting is meant to represent a capture of what the system was showing at a given time.
Delores, Data Analyst
Delores, our main persona, is a data analyst at Deca Foods and utilizes sensors to track the overall performance of farms and warehouses across the country. She’s able to spot trends, and gaps to suggest improvements in detailed reports.
Opportunities
- Increasing efficiency when working with real-time data
- Co-creation with AI to build shared reports
- Streamlining the collaboration and feedback processes
The Walkthough
Our interface offers a streamlined approach for data analysts to collaborate with AI in generating reports. With access to real-time data, it enables effortless teamwork and co-creation, ensuring the seamless delivery of high-quality reports.
Live Reporting
The map view on the landing page of the dashboard offers real-time updates on the locations and status of products in transit. It condenses sensor data and other analytical insights, providing users with a comprehensive overview at a glance.
This feature allows users to quickly grasp the current situation and make informed decisions based on the summarized information displayed on the map.
Co-Creation
Throughout the report creation process, users have a dynamic view of their inputs transforming into the report content in real-time. Additionally, they can observe AI-generated suggestions for report elements and have the freedom to customize and edit them as they see fit.
Editing Levels
Users have the option to generate moment-in-time reports at either the micro or macro level, providing them with flexibility in their workflow. This approach enables users to tailor their work according to their preferences and needs, allowing them to zoom in or out of the presented information as necessary.
Collaboration
For seamless and real-time collaboration, when additional users are added to a project, they gain visibility into each other's cursors and can track their movements. Moreover, users can leave comments within the project, which are automatically scanned by AI for potential resolution with just one click.
This feature enhances collaboration efficiency and facilitates smooth communication among team members.
Looking Back...
Reflecting on the potential expansion of our interface: How might conversational AI be effectively introduced into other complex systems? Considering this idea as a means to enrich our interface, I am confident that conversational AI has the capacity to streamline systems and elevate user experience.
