November 18, 2013

New, Smart and Responsive Product Design

Over the last 5 years or so, we have seen a huge increase in products learning our habits and routines to become ‘smart’ and responsive to our habits as users. Our electronic devices, like computers and phones, were the first entry into this brave new world. Largely brought on by their inherent software innovation, our desire for ‘easy to use’ electronics and to complete tasks faster, these kinds of products have became the foundation of the virtual/digital domain in ‘smart’ and responsive technology.

More recently however, we’ve seen this phenomena translate into more physical applications. Primarily, consumer and home automation products have ventured into this territory, as was evident at the Consumer Electronics Show earlier this year. The smart thermostat called ‘Nest‘ is a notable example. By simply using it like you would a manual thermostat over an initial start up period, the device will quickly learn your preferred temperatures and habits. Soon it will self-program to best suit your heating needs. It’s win-win solution: No manual programming for the consumer, temperature control is flexible and personalized, it saves energy, and as an added bonus, it can be adjusted remotely in unexpected circumstances.



Recently on ‘Spark‘ the CBC technology radio show had an interesting interview with James Ellingson national director of sales and marketing of Schindler Elevators.  Schindler have adapted this learning capability to create a smart responsive elevator system called PORT.  Essentially it’s goal is to reduce wait and ride times and in return optimizes the elevators use and reduces the energy required to run an elevator system.
It does all this by learning the habits and routines of users through a kiosk that replaces the traditional call buttons. The user enters their destination floor, then the kiosk directs them to a particular elevator, grouping people who are going to the same or near by floor.  As the system is used the smart algorithm kicks in learning the traffic of the building and tracking users destinations and behaviours, such as when they arrive in the morning or go for lunch.  According to James the PORT system could reduce the time users spend waiting and riding elevators up to 30%.


Smart and responsive products have been successful on a personal or small user group scale.  When considering the large scale it’s incredible that a system like PORT can adapt to what must have hundreds/thousands of variables within a single scenario, that is one sophisticated algorithm.   In this new smart and responsive world the product can only be as good as the algorithm.

Click here to hear the Spark Podcast. You’ll need to fast forward to minute 9:30 for the interview with Schindler Elevators.