Everyone is talking about artificial intelligence and data analysis - but many companies lack ideas on how to use the technologies. The digital association Bitkom has therefore compiled twelve concrete application examples for AI and Big Data in the industry in a guide now published, which were presented at Bitkom's Big-Data.AI Summit last year. "The public debate on AI and Big Data is far too often dominated by science fiction scenarios that have little relevance to the day-to-day business of companies," says Dr Nabil Alsabah, Head of Artificial Intelligence and Big-Data.AI Summit at Bitkom. "The guide brings together examples from very different industries that show how these innovative technologies can be used to very concretely improve results or reduce resource consumption."
In twelve chapters, the guide "Concrete Use Cases of AI & Big Data in Industry" presents, among other things, how vehicle data can be used to provide a risk assessment for individual driving behaviour, but also to mark potholes on a map and thus improve road quality. In another use case from mobility, anonymised smartphone data is used to create movement patterns to determine ideal locations for car-sharing stations or e-car charging stations.
Further possible applications for AI arise in medicine. The guide shows how artificial intelligence can be used in orthodontics for so-called cephalometry. This is mandatory before any orthodontic treatment, such as braces. In this process, a lateral X-ray image must be evaluated very schematically, which takes around 10 to 15 minutes. Thanks to AI, the image analysis can be done in less than a second - with about 10 million cephalometries per year worldwide, gigantic efficiency gains are possible. But data analysis and AI can also help in oncology: From early cancer detection, where even the smallest changes are detected on X-rays and CT images, to perfect individualised therapy based on the latest guidelines.
The guide also covers other practical examples such as building a price engine for a car spare parts dealer, predicting passenger flows at railway stations and the use of AI and data analysis in a rather conservative and less technology-savvy sector such as the steel industry.
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