Page 35 - MSDN Magazine, April 2018

Figure 2 Activity Signature for Turns in Skiing or Snowboarding
g-forces engendered during each millisecond, the analytics of sports is being redefined. In this article, we detail how we detect these activity signatures; in this case, the activity in question is turns made while skiing or snowboarding.
Using Azure Artificial Intelligence (AI) in the cloud, we ingest the sensor data, transform it for rich analytics, and tap ML to extract even more useful information for the athlete and coach. ML models make it possible to classify expertise level at each skill execution, and even perhaps predict the progress and future
may want to go further to leverage logic or code to transform the data into consumable analytics reports or predictive ML models. We offer several code sets that recognize specific athletic activities and the per- formance measures of those activities, for example, turns and the acceleration realized out of the turn. The Sensor Kit SDK is written with cross-platform development in mind, as a cross-platform .NET Stan- dard 2.0 C# library and it compiles with Xamarin, so you can use it in Android, iOS and Windows apps.
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Sensors Athlete and Coach
SensorKit Data Pipeline
Coach and Team View
performance of an athlete at an upcoming competitive event. The beauty of shared data standards is this allows athletes to benchmark relative to themselves or their community to understand differ- ences, weak points and advantages. And with new advances in the ability to implement AI at the edge, we can push activity recog- nition, predictive model scoring and performance measures out to the device, for rapid availability to the athlete on their device or in a mixed reality display. We hope this set of open source resources nur- tures and accelerates innovation in the sports community.
Sensor Kit Overview
The Sensor Kit is a set of open source cross-platform data pro- ductivity tools, including working code samples for data ingestion, analysis and ML, as well as sensor hardware reference designs. The Kit helps sports scientists, coach- es and athletes capture an athlete’s movement with millisecond pre- cision, and ML models evaluate the data for movement analysis. The Kit is designed to help equip- ment manufacturers, data and sports scientists, and coaches interested in modern methods of sports science, including ML and
AI. Figure 3 gives a high-level view of the elements of the Sensor Kit. In the sections that follow, we describe many elements of the Sensor Kit, from hardware, data ingestion and data transforma- tion, to analytics, ML and presentation.
The Kit is designed to allow the sports enthusiast or professional to use parts or all of its components. For example, the analyst may simply want a way to ingest the sensor data signals and transform that data into an analytics-ready format. Data pipeline code sam- ples are available for several typical raw data formats. Or the analyst
Figure 1 The Winter Sports Mobile App with Sensor Kit Integration, Illustrating the Forces Impacting a Skier
Power BI
Azure ML
Analytics
Sensor Sensor
SensorKit SDK
Cross-Platform Mobile App
Cosmos DB and/or Any Storage
Figure 3 Sensor Kit for Sports Applications msdnmagazine.com