Our world is undergoing rapid urbanisation. Today, over 55 percent of the world’s population is living in urban areas as per a UN report. As per the same report, India’s urban population is estimated to stand at 675 million in 2035, making it the second highest in the world.
Rapid urbanisation also brings forth many challenges, one of which is inescapable traffic. Millions of people around the world begin and end their day stuck for hours in traffic; the gridlock of tires and tarmac whether it is a daily commute or a weekend escape.
In 2021, Mumbai ranked fifth for having the worst traffic in the world, while Delhi and Bengaluru tied for the number eleven. As a result, Mumbai residents lost over five days in traffic, while Delhi and Bengaluru residents lost four and a half days. In addition, economists estimate that traffic-related accidents are projected to cost the world economy $1.8 trillion between 2015 to 2030.
Thanks to advancements in technology and better network coverage, traffic congestion and potential accidents can be avoided. Technologies such as artificial intelligence (AI), machine learning (ML) and the internet of things (IoT) are helping us reimagine how transportation should be managed. Powered by smart cameras, computer vision, and robust storage solutions, Intelligent Transportation Systems (ITS) around the world are a key part of a smart city movement.
Intelligent Transportation Systems
ITS uses a combination of advanced information and communication technologies to improve the safety, efficiency, and sustainability of the transportation system. The system takes advantage of equipment such as sensors, cameras, and recorders and injects AI algorithms and deep learning (DL) to enhance transportation safety and mobility. ITS encompasses smart metering to intelligently changing traffic patterns so that pedestrians can cross the streets or to alleviate traffic congestion.
Interestingly, these decisions can be automatically taken by AI-infused cameras, without human intervention. However, for AI to differentiate between different objects, for example, for it to be able to recognise a bike as a bike and a human as a human, it needs an immense amount of training. In other words, AI and DL need to analyse hundreds or thousands of hours of video to learn and become more accurate or better.
Data and storage
Data is crucial for an intelligent transportation system. This data must be captured, stored, and processed to gain insight from it and to use those insights to improve the safety and efficiency of the transportation system.
Storage is the foundation of an ITS. A smart camera requires a storage solution that is specially designed for it.
Storage can also be located at the edge in the camera. This helps in case there is a network interruption, and the video footage cannot be shared and recorded at the backend. Today, there are high-capacity cards that are designed specifically for the mainstream security camera market.
While ITS implementations are still nascent, the market could recover 175 million hours of travel a year, prevent 53 million gallons of fossil fuel consumption a year, and reduce CO2 emissions by 10 billion pounds a year. The important point to note is that data will continue to play an important role in putting ‘intelligence’ in an intelligent transportation system and storage will continue to be fundamental to it all.
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Autor(en)/Author(s): Jaganathan Chelliah
Quelle/Source: The Times of India, 20.12.2022
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