Developing a 3D Body Scan App for Tailored Sportswear
Personalized performance gear can give athletes a crucial edge. Tailored sportswear, designed to fit an athlete’s precise body dimensions, can improve comfort, reduce friction, and enhance performance. When a U.S.-based sports event organizer approached QSoft to develop a tablet-based application for scanning athlete body measurements, the stakes were high. The challenge was to create a 3D scanning app that would be both fast and accurate—capturing detailed body measurements with a minimal margin of error to deliver custom-fitted sportswear on demand. This post explores the complexities of this project, from ensuring measurement accuracy to streamlining data collection, and the innovative technical solutions that made it possible.
Ensuring High Accuracy in Body Measurements
One of the most critical challenges in developing the 3D body scan app was ensuring high accuracy in the measurements. Athletes rely on perfectly fitted sportswear to optimize their performance, and even minor errors in fit can result in discomfort or decreased mobility. Achieving precision with a margin of error within 2mm required advanced scanning technology and intelligent data processing. Traditional body measurement methods, such as tape measurements or manual fitting, were time-consuming and prone to human error. The new solution needed to eliminate these inefficiencies while maintaining exceptional accuracy.
QSoft addressed this challenge by integrating cutting-edge 3D scanning technology with advanced machine learning algorithms to capture precise body measurements in real-time. The app was built using Apple’s ARKit, a powerful framework designed to create augmented reality experiences on iOS devices. ARKit allowed the application to leverage the tablet’s camera and depth-sensing capabilities to capture 3D data points from the athlete’s body. By using ARKit’s TrueDepth sensor, the system generated a detailed 3D map of the body in under 60 seconds. This map included depth information from various angles, ensuring comprehensive coverage of the athlete’s physical dimensions.
The data captured by the 3D scan was processed using TensorFlow, an open-source machine learning framework. The integration of TensorFlow enabled the app to process raw 3D data and convert it into precise body measurements by recognizing patterns and refining calculations in real-time. To further increase accuracy, QSoft implemented a neural network model trained on thousands of data points from real-world athletes. This model was capable of interpreting subtle variations in body shape, which allowed the system to account for different body types and adjust its measurements accordingly.
One key feature of the app was the use of edge computing, which allowed most of the data processing to occur directly on the tablet. By processing the 3D scan data locally, the app minimized the need for data transmission to external servers, reducing latency and speeding up the overall process. This also ensured that measurements could be taken quickly and efficiently at live sports events, where athletes may have only a limited time window for fitting.
Additionally, the app was built with a feedback mechanism that displayed the scan results to the user in real-time. If any measurement inconsistencies were detected—such as missed areas or artifacts from movement during scanning—the app prompted the user to rescan the affected sections. This allowed for immediate corrections, ensuring that no data inaccuracies would compromise the final measurements.
Results: By integrating ARKit with machine learning algorithms, QSoft delivered a solution that achieved an impressive 2mm margin of error in body measurements. The precision of the app allowed sportswear manufacturers to create custom-fitted gear tailored to each athlete’s unique body shape, improving comfort and performance. Moreover, the rapid scanning process enabled the app to capture measurements in under 60 seconds, streamlining the fitting process at large-scale sporting events.
Rapid Data Collection and Processing for Real-Time Results
Another significant challenge was ensuring the app could rapidly collect and process data to deliver real-time results. At large sports events, where hundreds of athletes needed to be measured in quick succession, the system had to be fast, efficient, and capable of handling high volumes of data without delays. Traditional measurement techniques were not feasible in this context, as they would lead to bottlenecks and logistical challenges, impacting the overall event experience.
To solve this, QSoft designed the app to use AWS Lambda, a serverless computing service, for real-time data processing. AWS Lambda allowed the app to automatically scale its processing capacity based on demand, enabling it to handle fluctuating workloads without compromising on speed. As each 3D scan was completed, the measurement data was instantly uploaded to the cloud, where Lambda functions processed the data and generated the athlete’s measurements in seconds. This ensured that even at peak usage times, the system could handle the influx of data from multiple devices simultaneously, providing results in real-time.
The app also leveraged Amazon S3 for scalable storage of 3D scans and measurement data. Amazon S3’s durability and low-latency access ensured that all athlete data was securely stored and readily available for retrieval by sportswear manufacturers. In addition, QSoft implemented Amazon RDS (Relational Database Service) to manage athlete profiles and measurement records. This provided a reliable and secure database solution that supported real-time queries and allowed authorized users, such as sportswear manufacturers, to access the data as needed.
To further enhance performance, QSoft optimized the app for parallel processing. By breaking down each 3D scan into smaller, manageable tasks, the app was able to process multiple segments of the scan simultaneously. This significantly reduced the overall processing time, allowing the system to generate accurate measurements almost instantaneously after the scan was completed.
The app’s UI was built using React Native, a cross-platform development framework that allowed for a smooth and responsive user experience on both iOS and Android devices. React Native’s flexibility enabled the development team to create a consistent interface that could be used by event staff and athletes alike, while ensuring compatibility across different devices. The app’s intuitive interface guided users through the scanning process step-by-step, minimizing the risk of user error and ensuring that data collection was fast and efficient.
Results: With AWS Lambda, Amazon S3, and parallel processing, QSoft built an app that could handle the demands of live sports events, enabling the system to process and store athlete data in real-time. The app reduced data collection and processing times to under 60 seconds per scan, allowing for rapid measurement of hundreds of athletes in a short period. This efficiency not only streamlined the event operations but also enabled sportswear manufacturers to quickly access the data needed to produce custom-fitted gear without delay.
Revolutionizing Sportswear Fitting with 3D Scanning and AI
By addressing the dual challenges of measurement accuracy and rapid data collection, QSoft delivered a state-of-the-art solution that transformed the way athletes were fitted for custom sportswear. The integration of 3D scanning technology, machine learning, and cloud computing resulted in an application that combined precision, speed, and scalability to meet the unique needs of the sports industry.
The app’s ability to achieve a 2mm margin of error in body measurements, combined with its real-time processing capabilities, provided sportswear manufacturers with the tools they needed to deliver custom-tailored gear that improved athlete comfort and performance. With measurements captured in under 60 seconds, the system enabled large-scale events to proceed smoothly, without bottlenecks or delays.
For companies seeking to leverage advanced technologies to revolutionize their processes, QSoft offers expertise in AI-driven solutions, cloud-based architecture, and real-time data processing. To learn more about how QSoft can help your business develop innovative solutions, visit our services page.