Welcome to the Qinsun Instruments Co., LTD! Set to the home page | Collect this site
The service hotline


Related Articles

Product Photo

Contact Us

Qinsun Instruments Co., LTD!
Address:NO.258 Banting Road., Jiuting Town, Songjiang District, Shanghai

Your location: Home > Related Articles > How will intelligent transportation technology once again drive urban development?

How will intelligent transportation technology once again drive urban development?

Author:QINSUN Released in:2024-01 Click:94

Major cities have placed big bets on buses. Cities and suburban centers across the country are investing in new vehicles, routes, and bus lanes to provide safe and reliable public transportation for citizens, stimulate new economic development, and reduce traffic congestion as the pandemic recedes and Americans return to work. Public buses play a crucial role in the goal of reducing carbon emissions in cities, and are also an important component of the Zero Vision project to eliminate pedestrian traffic injuries and deaths.

However, a successful public transportation system requires appropriate implementation. Cities must be able to effectively monitor illegal parking to ensure that bus lanes remain unobstructed for timely transportation and to ensure safer streets. Traditionally, this was done manually with parking law enforcement officers on the streets, which was an inefficient process and difficult to scale up. Some cities have started using fixed cameras to assist law enforcement, but their scope and effectiveness are limited.

In order to adopt more modern law enforcement methods, cities are exploring how intelligent computer vision technology and automatic intelligence can help buses restart. By installing these visual devices on buses, transportation explorers can immediately create a law enforcement network covering every route of the city's public transportation system.

HaydenAI is a technology company that provides intelligent visual solutions for cities. Its CEO and founder, Chris Carson, stated, "Intelligent transportation ecosystems and smart cities are not just about breaking technological boundaries, but also the core concept of addressing social and environmental issues such as accessibility and sustainable development." At a recent online seminar, Carson discussed how appropriate law enforcement can have a broad impact on the traffic goals of cities.

Carson said that intelligent visual technology has improved the safety, sustainability, and fairness of public transportation.

As people return to cities and suburbs to work, transportation officials can use technological tools to prepare for future infrastructure.

Carson said, "I think the approach that transportation agencies must adopt is to embrace technology and see it as an opportunity for growth, an opportunity for innovation." "As we clear more bus lanes, the speed of buses will increase. As the speed of buses increases, more people will ride them."

In order to strengthen and expand law enforcement efforts, cities can not only install artificial intelligence visual devices on buses, but also on school buses, street cleaners, garbage trucks, police cars, and other vehicles. It is possible to aggregate data and share insights among multiple institutions, creating a more comprehensive execution system.

Carson said that the White House has made infrastructure investment a key priority, and technology will play an important role in improving the transportation system.

President Biden is promoting comprehensive reform and upgrading of the country's infrastructure, calling it a transformative effort that can create a resilient and innovative economy around the world. "It's time to embrace technology and create a safer, smarter, and more sustainable transportation ecosystem."

VaibhavGhadiok, co-founder and Vice President of Engineering at HaydenAI, stated that machine learning and computer vision are one of the most important emerging innovations that will drive transformation efforts. He also participated in the online seminar.

Ghadiok said, "Machine learning, especially when applied to computer vision, has made significant strides in the past decade." Through in vehicle devices, "we are building rich (three-dimensional) environmental maps that distinguish between sidewalks, bus lanes, parking timers, fire hydrants, and other components."

The artificial intelligence camera system recognizes vehicles parked on bus lanes through license plate recognition. The system integrates law enforcement dates and times together and can automatically send vehicle information to the violation processor of transportation agencies for further action. This technology can be updated to cope with temporary events such as parades, and parameters can be easily changed as needed.

Strengthening parking law enforcement can significantly improve the efficiency of buses. Ghadiok said that in a pilot device project in New York City, HaydenAI found that bus speeds increased by 50% or more.

"We are improving the punctuality rate of these buses and reducing passengers' waiting time, thereby increasing the number of passengers."

Law enforcement is just a use case of artificial intelligence and computer vision technology. It can also be used to recognize parking timers, so cities can improve parking management. In addition, it can also be used to remind drivers of nearby available parking spaces, alleviating the problem of driving around looking for parking spaces. This technology can even perform traffic pattern analysis to determine how many pedestrians cross intersections at specific times of the day.

In the future, these systems can be used to arrange roadside space, such as allowing delivery trucks to park for 15 minutes in typically restricted areas to drop packages.

All of these uses will help create a more intelligent and unified law enforcement network. As cities invest in new infrastructure technologies, in vehicle computer vision devices driven by artificial intelligence and machine learning will play a crucial role in ensuring safe, efficient, and effective transportation systems in the coming years.