Role
UX Designer
DURATION
30 days
Platform
Website
Type
Research
This project explores the future of drone operations by integrating generative AI into FlytBase’s ecosystem. Instead of focusing on manual control, the concept shifts toward AI-assisted orchestration, enabling proactive, hands-free, and intelligent drone management. The goal was to rethink how users interact with drones—moving from execution to decision-making.
FlytBase enables autonomous drone operations, but:
Operations still require manual intervention
Workflows are complex and fragmented
Users act more as operators than decision-makers
Key Problem:
How might AI reduce operational complexity and transform drone usage into a more intuitive, intelligent system?
To explore how AI can enhance drone operations, I analyzed existing workflows within autonomous drone systems and identified key friction points in manual control and decision-making. The research focused on understanding how operators manage missions, monitor multiple drones, and respond to real-time changes. Drone operations are highly manual and control-heavy Workflows are reactive, requiring constant monitoring Managing multiple drones increases cognitive load Systems lack predictive and decision-support capabilities
To understand the current landscape, I analyzed how drone operators interact with existing systems and workflows. The focus was on identifying inefficiencies in manual control, fragmented decision-making, and the cognitive load required to manage multiple operations. This helped uncover opportunities where AI could assist, automate, and enhance user capabilities.
Users spend significant effort on manual monitoring and control
Workflows are reactive rather than proactive
High dependency on technical expertise
Limited support for decision-making assistance
Operations lack seamless orchestration
USER PERSPECTIVE
Drone operators often work in high-stakes environments where precision and efficiency are critical. However, they are burdened with constant monitoring, adjustments, and manual inputs. Instead of focusing on outcomes, they are tied to execution. A system that anticipates needs and assists in decision-making would significantly improve both efficiency and experience.
Users act as system operators, constantly managing inputs, monitoring performance, and reacting to changes. Their workflow is linear and control-heavy, requiring continuous attention. They would benefit from a shift toward supervision and orchestration, where AI handles execution and users focus on strategy.
KEY INSIGHTS
Execution over decision-making
Manual control limits scalability
Reactive workflows reduce efficiency
High cognitive load in operations
Lack of AI-driven support
Reduced manual intervention
Proactive system assistance
Simplified and unified workflows
Better decision-making support
More accessible and intuitive interaction
PROBLEM STATEMENT
Drone operators need a more intelligent and streamlined way to manage operations because current systems rely heavily on manual control, increasing complexity and cognitive load.
HYPOTHESIS STATEMENT
If generative AI is integrated into drone operations, then users can shift from manual control to intelligent orchestration, resulting in improved efficiency and reduced effort.
VALUE PROPOSITION
Transforming drone operations from manual control to intelligent, AI-driven orchestration.
03 IDEATION
CONCEPT DIRECTION
Shift:
From → Manual execution
To → AI-powered orchestration
Three Interaction Models Identified:
Assistive AI (guides users)
Generative AI (suggests actions)
Autonomous AI (executes tasks)
OPPORTUNITY AREAS
AI-assisted workflows
Autonomous decision-making
Real-time adaptability
Reduced cognitive load
AI-Assisted Command System
Multi-Drone Mission Control
Autonomous Dynamic Replanning
Conversational Interaction
Accessibility-First Operations
04 DESIGN
Key Features
USER FLOW
DELIVERABLES
Increased operational efficiency
Reduced training dependency
Scalable drone ecosystem
Improved decision-making speed
This project reimagines drone operations by integrating generative AI into FlytBase’s ecosystem. By shifting from manual execution to intelligent orchestration, it enables users to focus on outcomes rather than processes. The concept highlights how AI can transform complex systems into intuitive, scalable, and future-ready experiences.
