What happens when you introduce a group of intelligent, curious computer-engineering students to the problems and the challenges of the sports industry? Pure magic. During the past 15 weeks of Spring 2015, Carnegie Mellon students taking the Internet of Things course have blown me away with a set of unique ideas that will impact a variety of aspects in sports. The students have worked in groups to build prototypes of innovations that could impact training (visual pacing-feedback system for runners, smart cleats for soccer), crowd flow and facility management (beacons), the fan experience at home (Oculus and Kinect-based virtual-reality systems), and the fan experience in the stands (smart beverage cup).
I am personally grateful to all of the sport teams and executives who have visited Carnegie Mellon, who have interacted with these students to provide feedback on the early prototypes, and who have provided the critical business and industry insight to sharpen the students’ thinking and focus.
Here are the inspiring innovations of the class of Spring 2015.
PaceMate: Visual Pacing-Feedback System for Runners
Joshua Antonson and Aayush Agarwal
PaceMate is a visual pacing-feedback system for runners which dynamically updates a runner’s pace in response to their run. PaceMate is a portable, non-invasive, easy-to-install system which uses LED lights to guide runners as they run around a track or route, and runners just have to follow the moving LED lights to keep their run at their desired pace. With PaceMate, runners no longer have to juggle timing calculations in their head and get distracted during their runs, and they can focus on getting the pace of their run just right.
Beacon-Enabled Population-Flow Tracking for Stadiums
Kedar Amladi and Chengxiong Ruan
Crowds and lines can create frustrations for sports fans at stadiums and ballparks, especially with high attendance games and events. This project uses Bluetooth Low Energy beacons to help spectators at events navigate around crowds and away from lines by letting users see at a glance where the longest lines and biggest crowds are, helping users plan which concession stands to go to, and helping event organizers and venue owners provide spectators with a more pleasant experience.
Oculus-Enabled Virtual Reality System for Immersive Fan Experience
Gillian Tay and Ajmal Thanikkal
Virtual reality is a cost-effective way for sports fans to experience their favorite games from a new and compelling immersive perspective. This project builds a cost-effective system using the Oculus and Kinect platforms in order to provide sports fans with a unique fan experience by combining sensors and tracking technology with an immersive virtual reality system, to enable sports fans to interact with their favorite sports and sports teams.
Embedded Smart Cleats for Individual Kick-Motion Training
Jacob Nelson and Andy Choi
It is challenging for young athletes to train themselves effectively on their own in the mechanics and specialized basic motions in sports, such as proper kicking technique in soccer, without the continuous supervision of coaches. It is difficult to monitor your own body or know if your movement was correct without any past data or feedback. This project developers a cost-effective, removable insole system that integrates into existing sports cleats to monitor, record, and analyze athletes’ motions, and provide them with feedback to help them improve their own skills.
MCUp: Smart Cups for a Better Beverage Experience at Events
Peter McHale and Elena Feldman
Currently, it is challenging to effectively sell beverages such as beer to spectators at stadiums because of a lack of communication between roving hawkers and spectators. The MCUp attempts to solve this problem by embedding sensors in a cup to detect the amount of beverage left in a user’s cup. Then, by communicating with the user’s smartphone, each user’s MCUp knows when the user has finished his or her beverage and is ready to purchase more from the beverage hawkers. Additional features which can be provided include counting the number of beverages consumed, and estimating the user’s Blood Alcohol Content based on the amount of alcoholic beverage consumed.