Contact person: Business Client

Phone:Show

Email:Show

Location: Brindisi, Italy

Budget: Recommended by industry experts

Time to start: As soon as possible

Project description:
"I am developing a professional electronic fencing training system intended for gyms, clubs, and high-level training environments.

The system is composed of: an electronic mannequin with multiple touch sensors and LEDs, a compact wireless sword unit, and a standalone user console based on Raspberry Pi (8 GB RAM) with a touch display.
The mannequin and the sword unit are based on ESP32-class microcontrollers (Adafruit Feather and QT Py) and communicate wirelessly in real time with the Raspberry Pi console.
This project aims to build a fully independent training machine, comparable in concept to professional sport ergometers, without requiring a smartphone or tablet for normal operation.
System Architecture
Electronic Mannequin
ESP32-based (Adafruit Feather), handling sensors, LEDs, and training logic.
Wireless Sword Unit
Ultra-compact ESP32 (QT Py), handling hit detection and wireless communication.
Standalone Console
Raspberry Pi (8 GB with HDMI touch display, responsible for:
graphical user interface (GUI),
session management,
data processing,
local storage,
cloud synchronization.
Cloud Backend
Used for data storage, statistics, rankings, and future AI-based training features.
Objectives
Monitor and improve fencers’ performance through structured training sessions
Provide local (gym-level) and global rankings
Enable data-driven and AI-assisted training programs
Support OTA firmware updates for ESP32 devices
Deliver a reliable, professional-grade MVP suitable for commercial evolution
Core Functional Areas (MVP)
Real-time training feedback (hit / miss / reaction time)
Session statistics and historical performance tracking
Local and global rankings (cloud-synced)
Device management and diagnostics
Secure cloud communication and data storage
Advanced AI logic, monetization, and premium content are planned for later phases.
What I Am Looking For
Strong experience with ESP32 (Feather, QT Py)
Experience with Raspberry Pi GUI development (Linux-based)
Wireless communication between embedded devices
Cloud APIs and backend integration
Ability to work with milestones and verifiable deliverables
Project Status
Hardware platform selected and validated
Firmware logic partially implemented
Seeking a professional partner to complete the MVP architecture and implementation
Final Note

This project focuses on long-term product quality and scalability, not on a quick prototype or a simple app." (client-provided description)