The 5G Transportation Revolution

Currently, there are 2 types of big data used for systematic analytics; structured and unstructured data. Obviously, the latter is the complicated one to manage as it mostly comes in the form of lengthy text messages, audio, image or animation (VDO), all of which had unrestricted entry. Requiring too much storage, normalization and extraction effort, although valuable information exists, it was mostly ignored or discarded in the past.

Today, although AI has eliminated such problems, the bigger hurdle has become the instantaneous transfer of vast amounts of data, instead. And the champion to push the edge of the envelope with constant back and forth transmission of massive strings of yottabytes, fast enough to be safe at scale, is the much expected 5G communication technology. It promises a capacity 20 times faster than the preceding model and support of 1 million IoT devices per square kilometer, i.e., tenfold of the previous limitation. Beyond communication, the upgrade also presents a vital stepping stone for self-driving cars. As image analytics from Lidar cameras is needed for VDO driven capacities and split second decision making, the breakthrough in big data transmit-ability marks a crucial stepping stone for the tech. Simply put, auto autonomy wouldn’t be possible without big data level transmission in real-time.

The role of VDO in self-driving safety 

In the pilot stage, VDO cameras were used to capture time, speed, and event images. Eventually, the Advanced Driver Assistance Systems (ADAS) was developed and part of the program was real-time analysis of VDO images that could alert upon the detection of risky behavior on the driver’s part or external treats. Nowadays, with the integration of camera technology that operates like your hundredth pair of watchful eyes embedded in an IoT network of sensory devices and systems with AI as the overarching brain controlling everything, the speed that 5G brings to the table is the last piece of the puzzle required to raise auto safety standards to a viable level.

Within the next 20 years, the number of cars is expected to increase to over 2 billion as a result of highway projects and transportation network expansion into rural areas. Construction and ensuing number of vehicles of which are expected to cause significant environmental issues and traffic congestion. Unsurprisingly, the next decade is set to see significant growth in the number of electric cars and cleaner automobiles. By 2025, EV sales will have a market share of up to 25%. By 2030, there will be over 11 million unmanned vehicles on the streets around the world. Regulatory bodies have been developed and tested, for instance, over 29 states in America and is expected to be enforced in other states in the near future and with similar applications in other nations.

Smart VDO cameras and the transport systems

Safety becomes the central focus of heightened importance when it comes to self-driving cars. As a vital component of the transport infrastructure in the future, smart cameras will play a significant role in detecting and controlling traffic. Such systems have been implemented in selected areas in America and has been proven to reduce a staggering 40% of traffic jam, thus a welcomed improvement on overall traveling time and pollution footprint.

One smart camera equipped vehicle can generate up to 4 terabytes of data per day, or the equivalent of 4,000 gigabytes. The amount of data generated from connecting everything through IoT devices installed in traffic lights, signs, parking lots and pretty much all types of facilities, together, composes unfathomable yottabytes of data. The speed of the 5G network truly holds the key to the safety and success of the self-driving technology and thus the future of transportation for everyone.

References: iotorldtoday.com

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