Head of Digital Services, Ericsson Middle East and Africa, Indranil Das has said that in the midst of a global digital transformation, widespread integration of next generation technologies like 5G and Internet of Things (IoT) is just over the horizon to boost large automation.
According to him, “As these technologies become more prevalent, demands of the networks supporting them will grow and evolve in the same stride, necessitating an increase in network complexity and capacity to boot. In order to capitalise on these trends and the new revenue streams they present, and to handle the complexity of diversification at the same time, networks must become scalable, intelligent, and automated.
“Network intelligence and automation are crucial to the evolution of 5G, IoT, and industrial digitalisation on every front. As 5G-enabled technologies develop, operators will need to increase their network capacity – but with additional capacity also comes additional complexity.”
He said to meet these new challenges, operators must introduce engineered solutions that combine machine learning and human intelligence to enable networks to self-learn, self-optimize, and deliver an optimal user experience.
“The complex reality of today’s telecommunications systems will only accelerate further with the introduction of next generation technologies. Machine Intelligence, using machine learning and other AI technologies, is vital to handling this complexity with more efficiency. As such, engineered network intelligence gives operators the ability to scale-up and automate operations in parallel with the growth of their network, resulting in significant performance and efficiency advantages,” Das said.
“In achieving network intelligence, Machine Intelligence must first be implemented from multiple angles. Machine Intelligence, which combines the strengths of Machine Learning and Artificial Intelligence, offers a means of reinventing network operations and redefining the operator product portfolio to create new business opportunities in 5G and IoT,” he added.
Das further explained it would enable algorithms to predict traffic patterns and dynamically put cells into dormant mode without impacting user experience; it would help prevent future malfunctions my providing actionable recommendations and reducing dispatches of service technicians and it would enable detection and optimisation in analytics, drastically reducing customer service calls, among others.