The Core Challenge:
From Chaos to Control
The primary UX hurdle was bridging the operational asymmetry between highly technical shore-side managers (focused on procurement and regulatory audits) and ship-side crews operating under high stress with low internet bandwidth.
"Nobody really does research for animals for the sake of animal welfare the way you are, specifically for the good of the animal. But a lot of the times when people do recordings of the animals, it's to get a better understanding of them as an animal model to hopefully move whatever treatment they're trying into humans. So, there is definitely up-to-date technology and up-to-date research on how to measure activity from animals, I do not doubt."
Ahmad Israwi
Multi-Persona Ecosystem Mapping
A platform built for everyone means designing highly targeted operational workflows. We mapped out exact system permissions and primary actions based on discrete maritime roles.
System Architecture & User Journey Flows
To scale across enterprise accounts, we designed an end-to-end journey that moves from initial risk assessment to transaction fulfillment seamlessly.

Key Feature Deep-Dive & UI Architecture
Pillar A: The Vessel Compliance Radar
After attending the "Computational Neuroscience" event at kite UHN, by Dr. Brokoslaw Laschowski, I discovered the potentials at the intersection of machine learning and neuroscience
"In our research lab, we develop new computational and machine learning models to decode neural signals from the brain which encode information about procesies such as cognition and motor intent."
Dr. Brokoslaw Laschowski
Computational Neuroscientist, Research Scientist and Principal Investigator at the Toronto Rehabilitation Institute, Assistant Professor at the University of Toronto

A large competitive study by Dr. Laschowski to systematically test different signal processing, feature extraction, and classification algorithms to determine the optimal combination for EEG Neural Decoding.
Stakeholders

Secondary Research and information maps

User Journey NOW (As-Is) and Proposed Future (Pave)
Perceptual map and product value
Key findings
01
Product considerations
Product needs to be comfortable for the animal, adjustable for different breeds and ages, stable while they're active, feasible to make, sustainable solutions and materials, and user-friendly.
02
Materials
Breathable, soft, and light fabrics suitable for sensitive skin of the animal.
Stretchy and adjustable materials to fit the animal.
Reusable/rechargeable wireless sensors instead of disposable electrodes to stay environmental friendly.
03
Technology
Since I chose to do non-invasive technologies, the wearable will include EEG electrodes for receiving data/brain scan, and tDCS for stimulation (delivering electrical signals).
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The AI model will collect the listed information to take actions for sending and recieving data.
Solution
Pave the path of communication and bonding
Pave is the communication bond between human and animals using Neurotechnology, through an app and a physical wearable for dogs and cats.
By leveraging non-invasive EEG technology, this system scans animal's brain and displays the translated brainwaves data in the app for the owner to monitor their pets' emotional and cognitive states. Using Neurostimulation capabilities (tDCS) users can send training cues, direct monitored communication cues, or therapeutic signals back to the pet’s brain as well.
Unlike traditional pet wearables that focus on GPS tracking or heart rate monitoring, Pave delivers real-time emotional and neurological data, empowering owners to take proactive action for their pet’s health, behavioural training, and emotional well-being; as well as communication features.

Design process
Phase 1: Ideation to Low-fidelity
The process started with +20 early sketches and ideations on how the wearable could look like.
Then by choosing two raw ideas, I started creating low-fidelity prototypes with magnets and papers and tested on small dog sculpture.
Later I started generating refined versions of the drawings using AI (MidJourney and Dali) to have an easier decision making and visualization of the concepts.
Meanwhile, I also started making flow maps of the app, including sign up to create a user journey while collecting the determined user data.

Early Sketches

Low Fidelity

Generated Concept
System Design: Scan process (receiving/collecting data)


System Design: Communicating process (sending/stimulatig data)


Phase 2: Mid-fidelity
The physical prototype continued after 3D printing a real-life dog and a cat model, while researching the exact measurements and materials.
With taking inspiration from products like VR headsets and dog goggles, I came up with the idea of a cap with attachable parts that are stretchy to fit the animal's skull.
The parts include a piece surrounding the neck, a piece that covers the top of the head, and a piece between the ears that connects the top piece to the neck piece. This was later simplified into two pieces as I decided to create two sizes of the product.

Mid Fidelity

3D Renders
My strategy to design the app was through Modular Design and Atomic Design approach to define small elements and assemble them into larger structures.
Since this idea is very unique, I couldn't find much inspiration for it, except data visualization widgets and dashboard layouts.
01
Define features
02
Design widgets for each feature
03
Mapping out pages
04
Adding widgets based on page map and features
Phase 3: High-fidelity
neurocap™ (wearable)
The final wearable called Neurocap™ includes two sizes of small (cats and smaller dog breeds) and large. It's made out of polyester fabric on the sides, soft woven elastic and 3D printed PLA buckles for resizing and adjusting the helmet. There's stretchy cotton used for the top piece to adjust and breathable for the animal skin, and includes 4 aluminium grommets to attach the sensors to.
The sensors have two parts which includes a top piece that is printed in PLA Silk+ and TPU on the tip (electrode) to easily click into the grommets.

To stay sustainable, the sensors were designed to be rechargeable. They come with a charging case, like AirPods.
Pave mobile app
Pave mobile app is a companion tool that visualizes the emotional and health data of the user's pet in real time using brainwave and muscle activity analysis. Paired with the wearable device, it offers live insights, behaviour trends, training feedback, and communication cues.

Packagine
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