So, what does the future look like based on what we saw at Junction 2018? In short, it looks bright in many ways. First off, due to all the solutions presented. Secondly, because of the people presenting them to us. So, not only do we have many great ideas to make payments easier and frictionless, we also saw that there are many future talents to help make things happen.
We already presented our winning teams in an earlier blog post. Now it’s time to return to some of the other teams’ solutions. Teams Flyby, Payhere, and Navik – it’s your turn to get time in the spotlight.
FLYBY literally showed us how to pay while flying by. Their focus was on cafeteria and lunch restaurants where transactions should be as fast and frictionless as possible. By using one’s feet (or other body parts) to pay instead of hands, people can fly through serving lines.
The team used a Raspberry Pi with RFID reader and Neopixel LED strip to simulate a point of sale. A successful transaction triggers Android push-notification through Ionic framework (Angular) or sends an SMS message (46elks). By using active tags and more powerful receivers, the system would be actually usable in the real world. Small dedicated single-chip solution would be easy and cheap to manufacture.
PAYHERE started solving a problem regarding the inefficiency of payments, particularly for fixed-price services with a clearly defined location, such as parking fees, road tolls, congestion pricing and similar. Their idea was to allow users to pay without actively using their mobile device but simply through having it, and the mobile device interacting with the merchant’s service.
The user would select the merchants and scenarios where automatic payments can be deducted, and the software would take care of that by tracking their location. They used a combination of multiple technologies to achieve their goal: Ultrasonic mobile device identification, RFID payments, GPS location, and face recognition (Clarifai computer vision platform).
NAVIK realized that current payment solutions demand too much attention from busy consumers, and businesses need to devise a way to improve user payment experience in order to stay competitive. The team created a frictionless and holistic solution that learns consumers’ spending habits and preferences and tailor-makes personalised service offerings. These offerings are, upon user consent, automatically paid in advance and send to the vendor who can prepare the order. Technology-wise, Navik used AWS Rekognition, Angular, and a Raspberry Pi controller with a camera and a servo motor.
The team created a fictional story to demonstrate their plan: Malika wakes up late. She has a meeting with his boss in an hour. She immediately gets a message from Navik through his smartwatch saying: would you like coffee and cinnamon buns as usual? Ariel clicks ok. The order is sent to Starbucks in advance. Malika arrives to pick her order. She goes through the face recognition to confirm her identity, gets her order and in off to go.
Check out our other posts about Junction 2018: