How AI Can Help Reduce E-Scooter Crime.

Recently we put out an article about how AI can be used with e-scooters which looked at helping to reduce the number of accidents they seem to generate. We’ll continue to look at AI and e-scooters, but turn our attention to the criminal elements and their liking for this mode of transport.

We mentioned before that one of the reasons why e-scooters are popular is their ease of use. They are light, can get through tight spaces, be picked up and carried, and are able to reach a decent enough speed. Certainly faster than most can run. So it’s little surprise they are also very much liked by thieves. For fast, hit-n’-run crimes such as petty theft or stealing from a shop, they are arguably better than the previously popular moped. So finding a way to make them unusable by thieves would be an excellent move.

That’s not just our line of thought. The Defence, Science and Technology Laboratory are looking precisely at this issue right now to see if there is a way that e-scooters can be immobilised by Police when used by thieves. Here’s our thoughts which expand on their concept slightly to take them out of action before they can be used in a crime.

As an e-scooter is used by its owner it will, over time, be used for repeat journeys across a day. For example, going to a shop, or college, or the office. They will go along usually the same routes and spend the same time in action followed by being idle. If the e-scooter is equipped with embedded IoT tech, that information will be easily recordable and used by an AI platform to tell the user all manner of useful information, such as:

  • When to stay indoors as some rain is coming directly overhead while they are travelling
  • When to take a different route as they are likely to otherwise be late
  • The best time to recharge based on their need for energy the next time they use their e-scooter

Applying AI to beating the criminals

The beauty of course is how the e-scooter will have learned the typical usage patterns over time. Which means the moment it is suddenly taken out of that user behaviour, it will realise something isn’t quite right. And then, as the time, speed and direction of the e-scooter falls more out of line, it can then red-flag the issue as potentially stolen. If it doesn’t get a response from the owner within a set time – say, sixty seconds – the e-scooter is then shut down. Then an auto message is sent to the Police to warn it is suspected to be stolen and the owner is not responding. By giving their last known location details they can be looked out for in case they are injured.

That means for a criminal, they are likely to get little time if any to use their preferred stolen chariot of choice, making it useless for their antics. But it also means the owner gets a better chance of having their e-scooter back faster – and, if they were attacked and had their e-scooter taken, then help can be on the way to them quicker too.

The last benefit of this is in the information sharing with Police. Prevention, as they say, is better than cure. So having a way to immobolise the e-scooter before it is used in a crime will result is of course a move forwards. But the data around the thefts can then be pooled to show when they are most likely to take place and where. This gives the Police valuable intelligence, and lets them deploy officers  to the areas where they are most likely to catch offenders. That’s a good way to get the criminals off the streets before they cause more harm.

So there’s Part 2 of our thoughts of how AI can be used for e-scooters. Next, let’s take a look at how it could be used to keep e-scooters safe and roadworthy.

1 thought on “How AI Can Help Reduce E-Scooter Crime.

  1. Pingback: How Artificial Intelligence Can Help Reduce E-Scooter Accidents | Augmented Insights

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