IoT use cases: Predictive maintenance

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Why predictive maintenance?

Whether trying to predict equipment failure or rising infrastructural challenges, predictive maintenance (PdM) aims at proactively monitoring for signs of upcoming issues so that the user can deal with the basis for these developments before problems arise. Technology is evolving, and responsive maintenance, i.e., to remediate the issues as they appear, is becoming an unattractive way of doing things. Predictive maintenance allows users to save on expenses in many ways, always one step ahead of any real problems like system downtime or equipment damage.

Predictive maintenance with IoT

IoT technology is well-suited for predictive maintenance monitoring in real-time, with strengths such as detailed sensor monitoring and capable data sharing systems. Implementing IoT technology for predictive purposes allows users to make informed decisions, protect their assets from damage, and increase their ROI thanks to the many use cases that open up through installing such devices and systems.

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The goal of the Connected Ship project is to develop and implement a horizontal ship digitalization platform to connect the different digital automation systems and IoT sensor networks across different communication standards on board a ship
The project will, with the help opf 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. 
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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