IoT use cases:

anomaly detection by Sensative Machine Learning
The project will, with the help pf Machine Learning and AI algorithms, identify common sensor problems for the most interesting sensors in agriculture, including sensors for temperature, humidity, precipitation and wind in weather stations, sensors for soil temperature and humidity, etc. 
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IoT Sensors, interconnected data sources and mobile data form the basis of the real-time smart city. The Smart Public Spaces project is a part of Future by Lund. Here we work with solutions for the future city which are based on real-time information where people, organizations, infrastructure and sensor systems work together to create a sustainable environment with a high quality of life.
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