Smart wearables – keep an eye on everything with data glasses
Portable, sensor-equipped AI systems that are worn on the body or integrated into clothing provide useful services. Data glasses, for example, support employees in picking orders by scanning containers, warehouse and article codes. For example, colored markings on the glasses can make it easier to find the right shelf or maintenance instructions can be brought up. This saves time and minimizes the error rate.
Control vehicles from over 4000 kilometers away
Together with the Israeli start-up Ottopia, T-Systems has shown how vehicles can be remote-controlled, transferred, or even used as taxis in a factory yard from over thousands of kilometers away. To ensure that the response time for transmitting the huge amounts of data is not too long, Ottopia uses an AI application that predicts the utilization of the radio cells in good time. This enables uninterrupted services, even over public LTE networks in remote locations.
AI-supported route planning reduces empty runs
One in three trucks drives through Germany empty. AI-supported route planning, which takes into account factors such as weather, events, and customer buying behavior at different times of the year, can reduce the number of empty runs and standing times. The AI system forecasts the market prices for truck routes and determines prices for spare capacities. In this way, supply and demand can be coupled quickly and effectively – and transport journeys made more sustainable.
AI sorts the mail – automated document capture
Letters, e-mails, invoices and other documents can be automatically processed and distributed using the image and object recognition of AI solutions. Since documents often arrive at companies in different formats – especially companies that are active internationally – it is advisable to use a self-learning AI solution that can correctly assign text, numbers and values.
Understanding texts correctly – with text mining
Text mining is an AI-supported reading and comprehension aid that uses methods such as natural language processing and deep learning. It recognizes and processes contextual meaning in structured and unstructured documents. Numerous processes benefit from this: for example, the analysis of customer feedback in e-mails can be used to automatically trigger the right response from customer service. In addition, text mining is very useful when it comes to the analysis of contract texts and other business documents.