Understanding Autonomous Network Through Current Status

by March 16, 2018

Autonomous Network is a network where human intervention or input is next to zero or minimal. These networks are self-functioning, self-diagnosing and are programmed beforehand to perform in a certain style. It is completely capable of managing itself with all due respect and monitors its own steps as and when required.

Artificial Intelligence, machine learning and other data analytics techniques have encouraged automation to next levels. It is essential and significant to note that here the term network in the ‘ Autonomous Network’ means more than just the sole network. It entails in itself the services, processes and other prerequisites that are necessary for an autonomous device to function uninterrupted. Where Apple’s Siri and Amazon’s Alexa are just a small version of how an autonomous network functions, there has been an advent of driverless, unmanned cars and drones for that matter to substantiate the grand entrance.

Siri and Alexa follow the instructions given by humans. It is a type of autonomous network but still involves a concomitant human instruction chain. When we talk about howDD function, it is a whole new world filled with fascinating technologies at disposal. It is this intriguing experience that has pulled companies apart from those that make cars into the field, for e.g. Google’s Waymo, Tesla, Uber. Apart from these, there are the usual car companies competing against the others like Volkswagen, Ford and General Motors.

All the above companies are striving to build a self-driving software system to be installed which will replace the human drivers thereby refuting any human intervention. This software is based on artificial intelligence, big data analytics, and machine learning algorithms to install sensors which on their own after monitoring and analyzing the outer conditions can decide upon the driving skills.

In the current year, Volkswagen is about to launch Audi A8 with ‘conditional driving automation’. Here, the driving decisions will be made by the computer in the car but a human can take over anytime and has to be ready for the same which is why ‘conditional’. Similarly, General Motors is set to launch Cruise AV in 2019 with no steering wheels or pedals, a car that drives totally on its own.

Tesla, although, is one step ahead of what others are planning, it is building an automation software that can be installed in the previously launched vehicles to provide an option for autonomous and computer-controlled drives. This is an upgrade for the customers.  This is also an example of an adaptive network. An adaptive network adapts or molds itself according to the needs of the business and the market.

The adaptive network has three layers namely- Programmable infrastructure that covers the physical and virtual elements. Analytics and AI are then utilized to analyze the big data thus produced in the process. Then come the software control and automation. Here, the task of monitoring and facilitating the required technology is done in order to eliminate any potential possibility of error due to human intervention.

While it is easy to discuss automation, it is actually a complex and complicated process. At the first step, automation caters to the newly built structure and then at the second step it is also required for it to handle the automation of any upcoming upgrades. In this scenario, the car companies that are going for partial automation are protected from the complexity. But as in the case of those raging to level 1, it is inevitable to build a comprehensive autonomous network with an added functionality of adaptability. Everyone is in search of immediate expertise and fast completion but this strategy is hardly of any use when working with autonomous networks. It is paramount that an autonomous network is built with utmost care and precision to avoid unexpected failures.