ORCHID
Spine is a NSA-sponsored Data Synthesis support system that helps Target Network Digital Analysts at Language and Analytical Sciences to query, generate reports and draw connections between data for suspicious activity through wifi and cellular networks. Spine uses Large Language Models and Generative AI and outlier detection to synthesize the anomalies in network detection software.
Role
UX Research
Product Strategy
UI Design
Duration
12 Weeks
Process work
This process involves competitive analysis of various sensors in food storage and farming, Choosing a particular food to research, discovering problems in current mechanisms, elaborating the persona, user journey maps, researching precedents, Ideation of features,Low-fidelity wireframe creation, High fidelity wireframe creation, Hi-fidelity prototype
Problem statement
This project involves with understanding the power of data in making decisions. We were given a prompt to create an interface primarily focusing on at least one of these concepts Visualizing, Simulating, Deciding, and reporting.Our team was given simulation.
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Painpoints and opportunities:
We selected rice as our crop of interest because, despite being a non-perishable food, it faces unique challenges during and after harvest. Issues such as moisture content, flooding, and temperature fluctuations can significantly affect its quality, storage, and overall shelf life, necessitating effective monitoring and management solutions.-
Competitive Analysis:
Persona
Luigi the logistic manager, Faces numerous hurdles throughout his schedule while trying to understand the situation of crops back in india due to power cuts as a result of flooding in monsoons.
Brainstorming:
This project involves with understanding the power of data in making decisions. We were given a prompt to create an interface primarily focusing on at least one of these concepts Visualizing, Simulating, Deciding, and reporting.Our tem was given simulation.
Technology
We have taken inspiration from maps, 3d assets and inventory design in video games such as civilization, clash of clans and combined them with visualizing sensor data and incorporating all of that in a dashboard for a logistic manager to use.
Initial layouts:
Low-Fidelity wireframes:
Task-Flow:
After creating the low-fidelity wireframes, we mapped the actions and tasks to the designed screens to determine the prototyping process.
Hi- fidelity Wire frames:
We received feedback to use red and green cautiously, as these colors can disrupt the experience for users with red-green color blindness. For the mobile interface, it was suggested to position the swipable choice cards at the bottom of the screen to make them easier to swipe with a thumb.
Demo Video
We integrated our User Journey and high-fidelity prototypes to create a video showcasing the various features and capabilities of Orchid. The video highlights how AI recommendations assist Luigi in making quick decisions. Additionally, it demonstrates the functionality of digital twins in a scenario where electricity and communication systems are disrupted.
Main features:
3D Digital Models:
Hi-fi models help make systems legible. They display weather, time, faults, and more
in an interactive & engaging model.
Flexible, multi-platform AI:
Constantly learning, the Orchid AI provides transparent decision making tools. Both mobile and desktop versions increase reactive abilities for users.
Impact:
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Designed a digital twin interface enabling logistics managers to monitor and manage rice farm conditions in real time, bridging geographical and operational gaps.
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Integrated IoT sensor data to predict temperature and humidity fluctuations in storage units, reducing spoilage risk and improving supply chain reliability.
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Delivered weather change alerts for monsoon onset and flood warnings, allowing timely interventions during critical harvest and storage periods.
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Empowered stakeholders with actionable visual insights, reducing manual monitoring efforts and optimizing resource allocation in a developing-country context.
Vaishnavi Parni
vparni@ncsu.edu
© 2035 by Vaishnavi Parni.
Created on Wix Studio.
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