Axis enables a smarter and safer world by creating network solutions that provide insights for improving security and new ways of doing business. As the industry leader in network video, Axis offers products and services for video surveillance and analytics, access control, and audio systems. Axis has more than 3,000 dedicated employees in over 50 countries and collaborates with partners worldwide to deliver customer solutions.
Category: Computer Science
Scope: 2 students completing 30 credits (20 weeks) each.
The number of IoT devices is growing, resulting in an increased demand for maintenance and an opportunity for continuous and automated device health monitoring. Forecasting the need for maintenance is referred to as predictive maintenance and it is a growing application of machine learning (ML). The forecasts are used to increase the efficiency of maintenance work, as well as to reduce downtime of critical equipment.
Axis has extensive time series (TS) data on connected cameras and several metrics that might be indicative of the maintenance need of a camera individual, such as image quality, process specific memory and CPU consumption, as well as the temperature and power consumption of various components. The data is appropriate for multivariate TS forecasting using ML algorithms and for a comparison of shallow ML algorithms with recurrent neural networks.
The goal of the diploma work is two fold:
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For information or questions regarding technical issues or practical questions, please contact our Master Thesis Coordinator: firstname.lastname@example.org
Supervisors - Professor Kalle Åström (LU) and Professor Bo Bernhardsson (LU)
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