Cars are the future smart phones and mobile offices. Very soon our work environment will have people using virtual assistants such as Cortana, Siri, and Google Assistant to make appointments, calls set reminders and ask for direction while on the move.
The growing dependency on our mobile devices result in apps that enable us to shop online, control our home heating system, stream music or listen to a podcast, and surf the internet while in transit. The technological liberties listed above require a good connection,and people expect a seamless one regardless of where they are. Making the network connection flawlessly active on roads and highways is crucial to our modern life.
When you board a train, it is not uncommon to see people on their various mobile devices working or being entertained,and each person requires a good network connection. Mostly, you find people making use of a 4G network and in some cases the on board WIFI. The demand for high-speed data on a train moving at 200km/hr is definitely a challenge for mobile service providers.
Consumers do not care about excuses of the network on 3G, poor hand off or misaligned antennas. All they want is a seamless connected mobility experience. Quality services that won’t interrupt their calls, internet experience and music and video streams.
With the introduction of 5G and the part it would play in making Autonomous Cars possible, there will be more pressure on ways to optimise connected mobility experience. Autonomous cars will require massive bandwidths and cannot afford to have an interruption in network connectivity. Their need to upload and download dozens of terabytes of data to run their processors, sensors and camera, as well as software updates will require quick and responsive data networks. It is said that Autonomous cars have larger software footprint when compared to NASA’s space shuttles.
The common practice when analysing mobile coverage and the quality of the coverage is to extract data based on consumers/users that are often stationary. These users often make or receive calls at a specific location and cannot adequately reflect the situation that pertains to mobile connectivity. Therefore, there is a call to include data from moving subscribers to capture information on mobile connectivity that represents mobility in its entirety. Doing so, will ensure a more accurate mobile experience analytics.
Lastly, questions of how Artificial Intelligence (AI) can be used to improve mobile connectivity experience are raised. The emergence of AI does bring a unique solution to the problem of mobile connectivity. Network operators can make use of AI to track the exact route and path where there might be faults in the network in real-time. With the help of AI, they can easily create dynamic adjustments to the system, to the benefit of both Drivers and Passengers.