Mobile Data Usage & Signal Strength – Manage, Analyze and predict estimated data usage and signal strength to conduct automatic cause analysis using deep neural network and unsupervised learning techniques

Enterprise mobility management enables to collect various metrics from million of devices. This industrial research project focuses on identifying the key performance indicators and formulas to identify and predict coverage issues and identify data usage problems within a device. Using the key performance indicators, the intern will explore all feasible machine learning approaches. Final goal is to design an AI smart diagnostic system to detect the issue related to data usage and signal strength and conduct automatic cause analysis. This would allow the clients to act proactively by getting deeper insights in their mobile applications. The solutions aim to provide a data usage and signal strength diagnostic solution to help client avoid their business disruption due to issues in mobile devices. This will help the Canadian organization to minimize the maintenance cost while reducing downtime and minimal business disruption.

Faculty Supervisor:

Murat Erdogdu

Student:

Partner:

SOTI Inc

Discipline:

Computer science

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

University of Toronto

Program: