View from the Edge – when Rasberry and Git got together and made Alexa
March 19, 2017 • Reading time 2 minutes
In what is called the Internet of Things, physical devices are becoming smart. These technologies will drive what is being called the fourth industrial revolutions.
If you have any doubt that this will happen the following video may start to persuade you:
It’s a video demonstrating a voice activated computer that I put together. The other voice in the video is an AI service on Amazon called Alexa that is “always getting smarter”.
Alexa can provide information, such as the weather, and also control various devices, such as light bulbs. The service has only been available for a few months in the UK, so it is still very early days.
But perhaps more incredible is that I, having not done something like this before, set this up in four hours with the help of an on-line tutorial and some bits-and-pieces that I bought from Amazon for less than £40.
Largely this is possible due to the very cost effective components (e.g. Rasberry Pi computer) and open source software, which is free to download. Not only is open source software free, but it is often better quality than its proprietary equivalent as there are huge communities of people that are contributing towards the development – part of the sharing economy.
Aside from me fitting one of these inside my mother’s lampshade to play a practical joke (albeit one that could be hugely helpful), the potential is huge: from self-driving cars (a tutorial too far for my skills), predicted music playlists through to connected devices that could help older people at home . Suddenly it is possible to develop cost effective solutions to problems that haven’t been solved – and no longer do you need to wait for a company to spring up with the solution: do-it-yourself!
This is also exciting on a professional level. We have just started Edge Health a company that is seeking to work the health sector to help make better use of their vast amounts of data. One of our prototypes helped a hospital improve its theatre scheduling by predicting operating times from free-text descriptions using machine learning, which (with some clever maths) can be used to plan super-efficient schedules. Integrating this with voice control, so that a surgeons can dictate notes and instantly get a proposed operating time (for validation) offers a big step forward for the NHS for less than the cost of a hot meal.
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