SPEEDBOT: MACHINE LEARNING

S . LI

According to the World Health Organisation, 1.35 million people die every year as a result of road traffic crashes, with 181,000 deaths in Britain alone. The biggest causes are inappropriate speeds and distracted driving. 53% of drivers exceed the speed limit on 30mph roads and 81% of drivers exceed the speed limit on 20mph roads. Similarly, up to 49% of drivers admit to using their phones at the wheel, causing 70,000 traffic casualties in the US every year. Yet, using GPS to extract speed limit information can be unreliable and insufficient compared to traffic signs, which can relay a wider variety of traffic information more quickly and clearly. Therefore, I decided to create Speed Bot. Version 4.13 of Speed Bot, available for free on the Google Play Store, is designed to combat traffic casualties by automatically detecting and recognising traffic signs in

your phone’s live camera feed. This is done using machine learning and image manipulation; no Internet access or location permissions are required. In total, Speed Bot can recognise 47 different traffic signs, and when tested in multiple environments with different visibility levels, Speed Bot’s overall detection and recognition accuracies were 97% and 84% respectively, solidifying its ability to save lives. The main concept behind

Speed Bot is neural networks. Neural networks are basically complex functions that mimic the brain. When data is inputted into a basic network, it is fed forwards through different layers. At each layer lie neurons, which take the data, manipulate them with values called weights and biases, and then outputs a certain value. After this, it is repeated thousands of times and we end up with a final output in the output layer. However, if this is done randomly, all we’ll end up with is just a random number. We need to train the network, and this means changing the weights and biases based upon previous performances to make them work for any input image. Essentially, neural networks solve problems using systematic trial and error, but are really good at it.

In these past 17 months, the process of getting Speed Bot out into the world has taught me a lot. It has given me an insight into the (horrifying at times) life of a software engineer, and has given me skills and knowledge that will surely help me into the future. A world where everyone owns a self-driving car, where emotive and sentient robots become our companions, and where artificial intelligence is part of every one of our actions, is not far ahead.

And Speed Bot is just one example of artificial intelligence. A small example - if you are interested in neural networks, or AI in general, I encourage you to research more and consider joining machine learning club, where we’ll be going through

Tensorflow and how to implement neural networks in Python. For me, artificial intelligence is the road works that will bridge the gap between this era and the coming one, and hopefully, it will allow you to detect and recognise that there are no speed limits in the world of Science, Technology, Engineering and Maths. P.S. Speed Bot is currently at 126 downloads. Let’s get it to 1000 by 2021!