Datumize Team Awarded at Intel IoT Hackathon for Smart Public Transportation Solution

Hackathons give a great opportunity to programmers and all other creatives to get together and see how far they can get with mastering a new technology and solving a real world problem in a short amount of time. For Intel, the business partner of Datumize, hackathons are a chance to get greatest talent involved in developing Internet of Things solutions on top of their hardware.

When signing up for hackathon, the objective of Datumize engineers was to get deeper into the world of Internet of Things by tackling a specific issue. Our team, among other 100 participants from all around Europe, had the entire 24 hours in between Sunday and Monday midday to craft the innovative solution. In this article, we give an overview of our project that was awarded with the prestigious second prize.

Commuting - The Great Challenge of Cities

Most of us know the pain of badly organized public transportation. It is proven that stress caused by unpleasant environment and delays of buses, subways or trains hugely impacts our life including the way we work and the way we sleep. Metropoles invest huge money in working out better commuting solutions for their citizens. We wanted to get involved and see what is possible in this domain. As our hackathon project, we decided to prototype an integrated solution that helps decision makers understand better the experience of commuters and make smarter data-driven solutions. We wanted to allow them to see in detail what factors impact experience of public transportation customers and exactly what environment is most friendly to majority of people.

We decided to prototype an integrated solution that helps decision makers understand better the experience of commuters and make smarter data-driven solutions.

Well-being of citizens during commuting is one of the cities’ grand challenges

Our Project in the Making

Sunday morning started with welcoming from organizers and a series of idea pitches of hackers, creatives and technology enthusiasts. Right after, Intel team gave us an opportunity to borrow for all the needed devices and sensors. We followed our idea of solution deployable in buses that consists of a panel for customer feedback (satisfied/unsatisfied buttons) and a set of sensors to capture as many key factors about environment as possible.

The “Thing”

These are the devices that we decided to integrate into the panel that could be deployed in public transportation vehicles:

  • Intel Edison module for connectivity and computation at the edge;
  • Arduino Board;
  • 2 Touch Sensors to capture input from customers;
  • LCD that invites people to give feedback and shows information from the cloud;
  • Temperature Sensor;
  • Sound Sensor to measure various types of noise;
  • 3-Axis Accelerometer to capture sudden motions and shakes in any direction;
  • GPS to capture position that can be correlated with traffic and weather;
  • WLAN Interface to capture number of active devices around;
  • Light Sensor to measure level of light in the bus.

Data has been captured from the sensors using Java API and pre-processed in Java and Python.

Prototype of the panel to be deployed in public transportation vehicles

Integrated Solution and Data Analytics

In the era of Internet of Things computation never happens in one place. Systems always consist of multiple distributed components at the edge (close to data source) and in the cloud. Machine-to-machine communication, previously known only in industrial solutions, now becomes a state-of-the-art in every “smart” solution. Streams of data generated and preprocessed at the edge hit cloud storages that become a base for data scientists who help decision makers take appropriate data-driven solutions.

In our solution, the data and events captured by Edison from inputs and sensors were sent to NodeJS API deployed in the Microsoft Azure cloud. There the streams were post-processed and aggregated to enable experimentations on data correlations. Since we did not have a chance to gather a real dataset during the hackathon, we decided to experiment with the data generated by ourselves.

From the data science perspective, some questions that would be interesting to answer on the captured set of data are: What would be the optimal temperature and light level in the bus? What levels and types of noise start to negatively impact commuters? How much the driver’s behaviour and traffic impact the mood of commuters? Exactly what events cause them to be unsatisfied?

Wealth of captured data enables smarter decisions for the public transportation

Presenting our Solution and the Verdict of Jury

Early in the afternoon of the second day, judges with expertise in the field of Internet of Things visited each of 23 teams and ranked their projects from the point of technical advancement and business applicability. We had 5 minutes to explain our solution and present a live demo and learned after two long hours that our team has been chosen to the final eight. Our second, three-minute pitch has convinced jury to award our team with the prestigious second prize: right after the team that implemented an innovative solution for watering plant roots, and right before the team that proposed a solution for preventing fires of forests.

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written by Pawel Skorupinski