jsjing.design

The Problem

Athletes in combat sports often have less technological access to improvement compared to the more mainstream sports, such as basketball, golf, soccer, etc.  Multiple sports use sensors in balls to track power, speed, accuracy, angle, and other factors that impact individual performance of said athletes. Combat sports heavily lack these training methods; Strike Sense solves this problem and by analyzing the same data applied to combat sports. Strike Sense’s intelligent connected ecosystem solves this by integrating smart pads, wearables, and an AI assistant to provide precise metrics, personalized coaching, and seamless multi-device guidance that enhances every training session.

My Role

My goal is to bridge the gap between technology and combat sports: I designed a simple system that allows current technology from other sports to seamlessly integrate into combat sports. I also designed the UI interface for the Phone, AI assistant, and interactions with the user and server to create an intuitive fighting app.

My process

I approached the app through the lens of a fighter: I myself have experience competing internationally, and at the highest level of competition the only form of technology review is watching videos of yourself sparring/fighting.  Through this perspective, I was able to identify the wants and needs of a competitor/main consumer of said app.

Ecosystmes and Journeymaps

5. Components Overview (1 short paragraph + component table): Provide a brief overview of your five components, then insert your component table.

Component

Experience Goal

Tech Specs / Requirements

1. Primary Intelligent Hub — StrikeISense Cloud & Smart Mat

The hub is the brain of the StrikeIQ ecosystem. It gathers data from all connected devices, including smart mats, sparring pads, and sensors. It processes this data using AI analytics to give real-time feedback and personalized training insights. It supports predictive coaching, such as “rotate hip +5°,” and tracks progress over time.

Hardware: Smart mat with embedded pressure and impact sensors (capacitive + force-sensitive resistors), Wi-Fi 6, Bluetooth 5.3.Software: Cloud backend (AWS or Google Cloud), AI model for movement recognition (TensorFlow Lite).Data Inputs: Motion, impact, stance detection.Data Outputs: Feedback via app, LED mat indicators, or voice assistant.Compatibility: iOS, Android, web dashboard integration.

2. Mobile/Tablet App — StrikeSense App (Main Control Surface)

The mobile app is the primary interface for athletes and coaches. It displays training data, manages workouts, and offers insights driven by AI. Users can look back at previous sessions, change training modes, and monitor their performance trends. The app also acts as the hub for setting up devices and personalizing features.

Platform: iOS (Swift) and Android (Kotlin).APIs: Bluetooth Low Energy (BLE) for device pairing, REST API for cloud sync.UI Framework: React Native or Flutter.Features: Adaptive dashboards, predictive notifications, data visualization.Compatibility: Integrates with smart mats, sparring pads, and voice assistant.

3. Smart Sparring Pads — Embedded Sensor System

The smart sparring pads measure impact force, accuracy, and strike location during training or sparring sessions. They provide instant visual or haptic feedback to improve precision and reaction time. Data syncs automatically to the StrikeIQ app and cloud for performance tracking and coach review.

Hardware: Impact and pressure sensors (piezoelectric + FSR), accelerometer for direction tracking, Bluetooth 5.3, rechargeable battery (8–10 hrs), LED/haptic feedback.Software: Embedded firmware (C/C++), BLE data transmission, StrikeIQ Cloud API integration.Data Inputs: Strike location, impact force, timing.Data Outputs: Real-time feedback + synced analytics.Compatibility: Pairs with mobile app, cloud dashboard, and “Kai” AI assistant.

4. AI Agent — “Kai” (StrikeIQ Conversational Coach)

Kai is the StrikeIQ voice and chat-based AI coach. It gives real-time guidance, motivation, and post-session summaries. Kai adjusts to the user’s skill level, offering encouragement for beginners and detailed analytics for advanced athletes. You can access it through the StrikeIQ app or a smart speaker.

Platform: Amazon Alexa, Google Assistant, or in-app chatbot.Tech: NLP engine (Dialogflow or GPT-based model), speech synthesis (AWS Polly or Azure Speech).Inputs: Voice or text commands (“How was my last session?”).Outputs: Verbal coaching, feedback summaries, progress notifications.Compatibility: Connected via StrikeIQ Cloud API; integrated with app and coach dashboard.

5. Human-in-the-Loop — Coach Dashboard & Manual Review

This component ensures human expertise remains central to the training experience. Coaches can review AI-generated insights, analyze performance videos, and adjust personalized training plans. It balances automation with trust, ensuring safe and effective training outcomes.

Platform: Web-based dashboard (React.js + Firebase or AWS).Features: Session review, progress tracking, AI insight validation, communication tools.Data Flow: AI analyzes performance → coach reviews/refines → updated plan syncs to user’s app.Compatibility: Accessible via web or tablet; syncs with StrikeIQ Cloud and mobile app.

The interaction starts off by opening the app and either pressing start session, reviewing previous session, or putting on the pads and starting training: once the app is open, it starts tracking speed, force, and accuracy (if hitting pads) of the respective gears for legs, fists,and head. These numbers are sent to the server, collecting and analyzing data and sending it back to the phone or any other mobile application. Using the data analyzed in the server the app can tell you your average speed, power, accuracy, your current stats, your all time high, and how to improve said stats.

Solutions and Hi-Fi

Include short captions explaining the intent or purpose of each image. 

Starting page

Home page: quick access to view stats, replay last session, sets that you do, and starting a new session.

Clicking the play button starts a session: alternatively having the app open and hitting pads also starts the session. Using sensors in the pad (wearable device)

Stat screen after finishing your session.

A fuller breakdown of the statistics with visual graphs and the option to talk to the agentic AI agent.

Video Demo

This video goes over the process, hi-fi, and a video advertisement to bring Strike-Sense to life.

self reflection

• What you learned about designing across devices.

I learned how to reuse assets from other aspect  ratios to another, In turn I also learned how to keep read-ability the same and respect the design from the other aspect ratio. I also explored this in responsive design when coding in HTML.

• How could AI be used (or used better) to meaningfully solve user problems in your ecosystem?

It helps streamline the feedback from the data given by the user: it cuts down research that designers or devs need to do for the intended project and just focus on the interactions and look of the app.

• What are the ethical implications of your system?

The replacement of physical trainers in just the pure statistics sense: when it comes to combative sports having a coach to teach strategy is always going to be important. In this app the coach is just purely for athletics either replacing another coach or almost taking over the job of the sparring coach. 

• Where the system could be more intelligent or more human-centered.

During the feedback the system should for sure be more human centered as the AI can fail to react to human injury, human will, having off days, etc… or doesn’t push the person enough when they want to quit. Reading stats such as speed and strength is for sure something that can be more intelligent as getting numbers like that will always be a job of a computer.

• Key tradeoffs or constraints you encountered

I traded some personal connection with my project: I’m sure this is not the response you wanted to hear, however its something that deeply affected me as a designer. I want to pour my soul and mind into each project and having an AI do the foundation of a project leaves me uninterested in it as a whole. I understand that I need to adapt, just this is not what I imagined design to be when I first wanted to be a designer.