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M1, SIT to develop AI deep learning algorithms for mobile network management

Source: telecompaper.com

Singapore operator M1 and Singapore Institute of Technology (SIT) have signed a research collaboration agreement, to jointly research and develop artificial intelligence (AI) deep learning algorithms and methodology to upgrade the planning, operations and maintenance of large and complex mobile networks. M1 and SIT plan to jointly develop AI services to reduce manual observation and analysis of huge amounts of network key performance indicators (KPIs).
M1 will set up a deep learning environment at SIT, using real-world data from its operational mobile network to provide domain knowledge for data pre-processing, analysis, visualisation and interpretation. SIT will research, model and jointly develop algorithms with M1 for AI machine learning to detect mobile traffic anomalies and predict the volume of mobile traffic.

The project seeks to develop a performance anomaly detection methodology by using deep neural networks (DNN) via semi-supervised or unsupervised learning on multivariate time series data. The two partners will also leverage DNN to model and predict active users in mobile networks, based on historical mobile traffic data.

M1 recently signed a partnership deal with the Nanyang Technological University (NTU) to develop a 5G cellular vehicle-to-everything (C-V2X) research testbed and trials. M1 also signed a research collaboration with the Singapore University of Technology and Design (SUTD) to research the remote operation of tactile robots using 5G tools.

In mid-2019, Singapore’s Infocomm Media Development Authority (IMDA) and the National Research Foundation (NRF) announced plans to invest SGD 40 million to build a 5G Innovation ecosystem. This will support 5G technology trials for enterprise use-cases; the creation of new open testbeds; as well as R&D in 5G, including cybersecurity services. IMDA plans to initially explore clusters such as maritime operations; urban mobility; smart estates; Industry 4.0, consumer applications and government applications.

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