Mohammad Shauzab
FAST
· 2021
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I17 - 0407
Email
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Academic
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CGPA
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Year
2021
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DOB
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Career
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Skills
Arduino, Proteus, Adafruit.io, IoT, NodeMCU ESP8266, Load Cell, RFID
Verbatim text
The exact text the LLM saw on the page (or the booklet text from the old import).
This is what powers semantic search.
HitBOX (Martial Arts Strike Trainer) Technology advancement has infiltrated all types of fields in recent years and the realm of martial- arts is no different. Instead of old training methods passed down from generation to generation, athletes are becoming more inclined to use effective tech-based training tools which is starting to impact the standards of international martial arts competitions. For developing countries, to be able to compete with these athletes on the international stages, there is a need for a cheaper alternative to their smart training tools. HitBOX(Martial Arts Strike Trainer) is an IOT-based training tool designed for modern combat athletes which senses and records user strikes and displays relevant strike parameters in real-time and in forms of graphs for comparison and contrast. A single-point load cell along with an HX-711 load cell amplifier is used for this project. Data from the sensor is sent to the microcontroller, i.e NodeMCU ESP8266 to process Impact Force, Reaction Time, and Strike Velocity. These values are sent to the cloud and displayed on a user interface that is designed using a personalized dashboard on Adafruit.io. The entire system starts once a player is detected using an RFID module. The project provides a cost-effective, alternative training tool that presents reasonably accurate data. Technology Used: Arduino, Proteus, Adafruit.io Supervisor Name: Engr. Aamer Munir Group Members: Mohammad Shauzab (I17 - 0407)
AI enrichment
Mohammad Shauzab is a student who developed HitBOX, an IoT-based martial arts strike trainer using NodeMCU ESP8266, load cells, and RFID. The project processes impact data and displays real-time metrics on an Adafruit.io dashboard to provide a cost-effective training alternative.
Skills (AI)
["IoT", "NodeMCU ESP8266", "Arduino", "Proteus", "Adafruit.io", "Load Cell Sensors", "RFID", "Data Visualization"]
Status: ai_done
Provenance
Source file: Graduate Directory FAST School of Engineering - 2022 Final Version (07-06-2022).pdfFrom job #22 page 60
Created: 1778170281