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Smart Data Applications
While Big Data is seen as the result of the advances achieved in the digitalization of previous analog data sources as well as the emergence of new digital data sources, e.g., from new sensor technologies, Smart Data refers to the economic and social value added from the rapidly growing mountains of digital data in all areas of life. Beyond a consideration of the technologies required for data management and data analysis, the legal and social framework conditions must also be taken into account.
Although transferring innovative scientific technologies of smart data into the development of marketable high-tech technologies is at the pre-competitive stage, these new technologies are already changing many kinds of application areas of our life, from smart factory to smart city and smart home, by applying to various AI-based smart apps. Here we present the most highlights of four application domains, including smart energy, mobility, eHealth and Industry 4.0.
Smart Meter, Smart Grids, virtual power plants – the energy supplies of the future vary from innovative Smart Home technologies to decentralized energy networks. New information and communication technologies offer potential for more efficient utilization of existing network capacities, as well as relevant data for intelligent network expansion and the integration of renewable energies.
Floating Car Data, Car2X, road sensors and signal systems, cell phone data, routes and timetables, infrastructure data, Twitter – in hardly any other sector are so many data sources available as in transportation. Which new data value-added chains and solutions can be created from them? What meaningful insights can we draw from this real-time data flow?
Biosensors, High-Throughput technologies in life sciences, lifelogging, mobile apps, online registries – the amount of digital, patient-related data is increasing thanks to new possibilities. International research and participative medicine is generating even larger amounts of big data that is constantly stored online. How can this data be used for the improvement of therapies and nursing, for example in telemedicine, without affecting the mutual trust between the doctor and patient?
The Internet of Things is increasingly conquering production halls and supply networks. Due to the complexity of highly automated production, the quality, effectiveness and productivity of the processes can hardly be monitored “manually”. Real-time data stream analyses can not only detect signs of machine wear as soon as they happen, they also provide valuable information for future product and process optimization, improve capacity usage and service development.