Through the use of high-functioning, high-intake AI data collection, governments, local councils and town planners can make informed decisions regarding traffic flow, congestion and road safety. By implementing video monitoring via CCTV cameras, AI technology can gather a comprehensive amount of data that can be closely analysed and used to carry out positive changes. In this article, Secure Agility discusses how IoT sensors and predictive transport systems work in conjunction with AI technologies to give real-time insights into traffic data, allowing authorities to make informed changes.
How IoT Sensors Gather Information
With AI technology improving daily, the functions and uses for it grow exponentially. AIoT sensors employ AI technologies to gather information about traffic throughout a city. On most intersections, especially ones with traffic lights, there is a camera, this camera uses AI visual monitoring to observe how traffic flows through these intersections. It can be programmed to monitor traffic congestion (how long it takes for cars to make it through the intersection). Furthermore, it can monitor safety standards, such as how many crashes or accidents occur in the area and traffic infringements, such as drivers using their phones while behind the wheel.
According to Ahmed Abdeldayem, IoT Practice Lead, Secure Agility, “our integrated AIoT Transport solution can detect and report on transport infrastructure, and events, visually, and to suit requirements. For example, parking lot companies may want to focus on monitoring occupancy rates during certain times of the day. We can concentrate the data collection around this point of interest, giving your organisation the information it requires.”
Alleviating Congestion
IoT traffic management systems allow authorities to monitor a large area of a city that handles extensive traffic. Observing how city areas handle traffic compared to other areas allows authorities to understand better what types of traffic flow mechanisms work best. For example, roundabouts result in less congestion than an intersection with traffic lights.
Furthermore, it also allows authorities to identify high congestion areas; the data gathered that gives them this insight may lead to roadworks that alleviate this congestion, such as building a bypass, introducing a new lane or changing the speed limit. Overall, IoT traffic observation and monitoring is a great way to collect comprehensive data that can go a long way in transforming the traffic flow and congestion levels of a city.
Improving Road Safety
One of the main roles of IoT traffic management technologies is to improve road safety throughout our towns and cities. By using AI data collection, authorities can identify which areas of the road have the most crashes and driving infringements. Once authorities have this information, they can easily make the right changes to reduce these incidents. For example, if an area of road is seeing a lot of high-impact, high-speed crashes, it could indicate that the speed limit is too high.
Therefore, lowering the speed limit may help reduce these incidents. Furthermore, if AI data shows several crashes in residential areas, such as speed bumps and stop signs have been shown to reduce such accidents effectively. Regarding driver infringements, IoT traffic management systems can pick up on drivers using their phones when behind the wheel, cutting drivers off, not obeying stop/give way signs and much more. Authorities can act on this by putting police cameras in these areas and authorising fines to the individuals.
Find out more about how AI technology can help make Australian roads safer by contacting us online today.
