Silver Mobile Predictive Behaviour Challenge Banner

identify an algorithm to achieve healthier and happier lifestyle.

A Data Innovation Challenge hosted by Silver Mobile based on different types of sensors data.

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Silverline Mobile Predictive Behaviour Challenge

Silverline provides a suite of apps that are made specifically to meet the needs of seniors and help them lead more connected, productive and healthier lives. The apps are available on both iOS and Android mobile platforms.

The Silverline App fully utilises a smartphone’s advanced functionality in combination with a very user-friendly experience, cheerful designs, high contrast colours and large buttons.

The Companion App is designed to give you piece of mind when you cannot be in the presence of your senior. Share messages/photos and view their well-being stats. Seniors can check in every day and report they are doing ok.

The external sensors project is the next phase of building the senior eco-system. Silverline is extensively testing and prototyping different configurations of sensors to give the most non-intrusive experience whilst collecting the most meaningful data as possible. The sensors are installed in the home of the senior and will begin to track and learn their habits and usage trends to provide accurate prediction data.

Silverline’s apps are designed and continuously improved using feedback from elderly users. You can now be part of the development process by taking part in the Challenge.


Challenge Statement

One of the aims of Silverline is to support effective behavioural change in its users for them to achieve a healthier and happier lifestyle. Therefore, highlight an observation, propose an algorithm, model that helps Silverline achieve this through the use of the applications and data sets shared with you.

Evaluation Metric

Not applicable


Period 41 Days
Start Monday – 27 January 2014
End Saturday – 8 March 2014


Prize pool: SG$ 5,000


about the host

Silverline Mobile

Silverline Mobile

Silverline Mobile, a Singapore based company, is dedicated to creating the world’s first senior mobile eco-system to aid seniors in living more wholesome and healthy lives. With the development of Silverline Mobile apps on powerful smartphones, low energy sensor systems and data analytics, they are working to create an Internet connected system that allows Silverline Mobile to support effective behavioral change in seniors for them to achieve a healthier and happier lifestyle.

data and resources


User Input Data

The User Input data in JSON format. Refer to the README in for more details.

Summary Statistics

The Summary Statistics of App performance (in CSV format) is an aggregated set of data showing user engagement over a timespan of 4 months, capturing no. of Screen Views and Average Time spent on screen etc.

Sensors Data

The Sensors data in CSV format. Refer to the README in for more details.



May I use my own external datasets to build my predictive model?

Yes, you may.

Are there any restrictions to the progamming language and tool I use to build my predictive model?

There are no restrictions to the programming language nor the tool(s) you choose to use when building your predictive model. However, we do require you to submit a short write-up, with your ‘submissions.csv’ file, detailing the methods and resources you use when building your model.


  • Rakuten-Viki Final Presentation Event

    The Rakuten-Viki Global TV Recommender Challenge has finally come to a successful closure on the 16 September 2015. Six Teams (Team Merlion, Team GM, Team Haipt, Team Pritish,Team Gbenedek & Team Lenguyenthedat) were invited to present publicly in front of a pool of audiences and the judges.

  • Rakuten Viki Challenge Results

    Finalist teams are announced! We would like you to join us for the final presentation event where shortlisted teams will present their algorithms and insights to you.


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