Find out how HackerEarth can boost your tech recruiting

Learn more
piller_image

How these hackathon winners apply Machine Learning to minimize rash driving

Hackathons have become the go-to method for developers and companies to innovate in tech and build great products in a short span of time. With tens of thousands of developers participating in hackathons across the globe every month, it’s a great way to collaborate and work on solving real-life issues using tech.

“Along with being stimulating and productive, hackathons are fun” – says Team Vikings, who won the first prize (a brand new Harley-Davidson bike!) in the recently concluded GO-HACK hackathon. The team built Rashalytics – a comprehensive platform for analysing and minimising rash driving. And now, they have big plans of taking this hack live for the public.

Read on to know more about their amazing idea and how they built the platform.

What is Rashalytics?

Rashalytics is a system that promises to mitigate the problem of rash driving by intelligently incentivising or penalising the driver based on his driving style. It has been designed to reduce the number of accidents that have increased with the hyperlocal on-demand delivery requiring breakneck speeds of the various products.

The system is able to extract the data of rich metrics like sharp acceleration, hard braking, sharp turns, etc. from the driver’s android phone, which is used to train the machine learning models.

Technologies/platforms/languages

  • Nodejs – To create the API server and the mock sensor data generator
  • Kafka – To build the data pipeline
  • Apache Spark – To process the real-time data stream and generate metrics to measure the driving quality
  • ReactJs – To create the dashboard web app
  • Google roads & maps API : To get the traffic and ETA data

Functionality

Machine learning challenge, ML challenge

The system primarily consists of 4 parts:.

  1. The Android app: Simulated by the team, this app aggregates locally and sends the chunks of sensor data to the API server via an HTTP endpoint.
  2. API Server: This matches the data with the schema and if valid, it puts the data in Kafka queue.
  3. Engine: Made with the Apache Spark, this helps sensor data to aggregate and form metrics such as sharp acceleration, hard braking, sharp turns, etc. These metrics, in turn, are used to generate a dynamic driving quality score for the driver. This score forms the basis of a lot of analytics and functionalities that this system provides.
  4. Dashboard: The dashboard provides a beautiful and intuitive interface to take proactive decisions as well as run analytics using the provided APIs. It has been written using ReactJS.

Here’s the flow diagram showing how the whole system works:

 

This system allowed the team to create:

  • A dynamic profile and the dashboard of the rider describing his driving style, which affects his rating.
  • An actionable “real-time” rash driving reporting system which allows the authorities and the hub incharges to react before it’s too late.
  • A dashboard usable by both the fleet managers and traffic police control board to visualise the data such as incident distribution by time, which tells at what time of the day a driver is more likely to drive in an unsafe manner.
  • A modular system in which the new data sources, metrics, and models can be added so that the third-party vendors can be easily on-boarded onto the platform.

 

Challenges

Here are some of the challenges that the team faced while building this application:

  1. Setting up the entire system architecture with different components by developing them in isolation and then combining them together to work seamlessly
  2. Deciding the thresholds for different metrics after which the driving will be considered rash
  3. Creating a linear predictor for the driving quality score vs time with only one data point
  4. Creating a synthetic feature as generating the score itself is challenging enough

What’s Next?

Project creators Shivendra Soni, Rishabh Bhardwaj and Ankit Silaich have great plans in store for their project. Here are some of their ideas:

  1. Create and SDK for easy data collection and integration with different apps and make it possible for third-party vendors to utilise this data
  2. Improve the driving score model to include even more parameters and make it more real-world oriented
  3. Create a social profile which lets the users share their driving score
  4. Enable enterprise grade plug-n-play integration support

 

Hackerearth Subscribe

Get advanced recruiting insights delivered every month

Related reads

Best Interview Questions For Assessing Tech Culture Fit in 2024
Best Interview Questions For Assessing Tech Culture Fit in 2024

Best Interview Questions For Assessing Tech Culture Fit in 2024

Finding the right talent goes beyond technical skills and experience. Culture fit plays a crucial role in building successful teams and fostering long-term…

Best Hiring Platforms in 2024: Guide for All Recruiters
Best Hiring Platforms in 2024: Guide for All Recruiters

Best Hiring Platforms in 2024: Guide for All Recruiters

Looking to onboard a recruiting platform for your hiring needs/ This in-depth guide will teach you how to compare and evaluate hiring platforms…

Best Assessment Software in 2024 for Tech Recruiting
Best Assessment Software in 2024 for Tech Recruiting

Best Assessment Software in 2024 for Tech Recruiting

Assessment software has come a long way from its humble beginnings. In education, these tools are breaking down geographical barriers, enabling remote testing…

Top Video Interview Softwares for Tech and Non-Tech Recruiting in 2024: A Comprehensive Review
Top Video Interview Softwares for Tech and Non-Tech Recruiting in 2024: A Comprehensive Review

Top Video Interview Softwares for Tech and Non-Tech Recruiting in 2024: A Comprehensive Review

With a globalized workforce and the rise of remote work models, video interviews enable efficient and flexible candidate screening and evaluation. Video interviews…

8 Top Tech Skills to Hire For in 2024
8 Top Tech Skills to Hire For in 2024

8 Top Tech Skills to Hire For in 2024

Hiring is hard — no doubt. Identifying the top technical skills that you should hire for is even harder. But we’ve got your…

How HackerEarth and Olibr are Reshaping Tech Talent Discovery
How HackerEarth and Olibr are Reshaping Tech Talent Discovery

How HackerEarth and Olibr are Reshaping Tech Talent Discovery

In the fast-paced tech world, finding the right talent is paramount. For years, HackerEarth has empowered tech recruiters to identify top talent through…

Hackerearth Subscribe

Get advanced recruiting insights delivered every month

View More

Top Products

Hackathons

Engage global developers through innovation

Hackerearth Hackathons Learn more

Assessments

AI-driven advanced coding assessments

Hackerearth Assessments Learn more

FaceCode

Real-time code editor for effective coding interviews

Hackerearth FaceCode Learn more

L & D

Tailored learning paths for continuous assessments

Hackerearth Learning and Development Learn more