One of the best things about IoT (Internet of Things) is its ability to solve the most common problems that we have around us and one of them is traffic. I would like to explain the capacity of IoT in optimizing the traffic because of today’s world population and the large number of transports that exist in the world. This issue even rises when most of the world’s population begins to migrate to metropolitan areas. According to research, by the year 2032, nearly 61% of the world population will be in metropolitan areas.
No matter what area you are living in, you will always meet traffic difficulties around the clock. And this problem grows even worse when the city’s population & the vehicles they own increase. Moreover, each country’s transportation method will become worse and also it will be really hard to find out the solution to this problem without taking support from smarter technology.
The use of smart technology like Internet of Things (IoT) is gradually shifting from mobile applications that improve the quality of life to resolving problems that people suffer in their day-to-day lives. Now, let’s understand how IoT resolve the most common difficult problem of today’s world population- Traffic congestion.
The Era of AI and Sensors
Let’s see how the growth of IoT is quickly increasing in our environment. Common virtual assistants like Siri and Alexa for news and data information, cities are changing to smart devices to collect helpful data and insights of different constituents required to effectively serving the needs and wants of civilians. This kind of low-cost sensors allows productive and efficient methods to watch and control traffic using real-time information.
The advanced improvement in machine learning are providing city officials excellent insights regarding the problems that are suffering by metropolitan people and metadata generated by such cutting-edge technologies provide concerned directors to make much more immediate and organized decisions.
Smarter cities are attempting to adapt these smart technologies and combine it in traffic systems where vehicles interact with each other, making the drive from point X to point Y safe. The new improvements in cloud and edge data centers have significantly decreased the cost of data storage, at the same time, making the data immediately available for research and study. Big data revolution is transforming the way how cities run.
Idea behind Smart Traffic
Here, the primary idea is about connecting "Things" together so that the city's traffic can get better and effective. For example, by connecting vehicles GPS with traffic cameras, the city's directors can have a helpful insight and understanding of how to control and handle traffic efficiently. Also, to make it more productive, a message can be sent to vehicles owners to inform them about the traffic jam in the route they are going and help them to take a different route. The result will be a helpful and efficient traffic experience, a notable reduction in the traffic jam and a secure transportation system.
Internet of Things (IoT) performs a crucial part in this scenario by collecting data from various channels like traffic cameras, vehicles GPS, sensors, etc. Such kind of data can be used to analyze and to know the traffic patterns and eventually, we will find innovative ideas to simplify the most often taken roads and transportation systems. Not just that, connected sensors and detectors can recognize serious conditions and assistance will be then sent to act immediately & also can view in real time through websites which is operated by a web development company. Car drivers will also be informed about such conditions to avoid and hence decreasing the number of road accidents for the good safety of other passengers.
Solutions that can be performed to optimize the traffic issue and increase the efficiency of the entire traffic operated transportation systems are:
1. Combine different sources of traffic data
The data sources are managed and developed into a static traffic information model by combining the traffic data that is gathered from different channels like traffic lights, cameras, telematics, and other sources.
2. Analyze traffic data
Analyzing data information to give reliable and real-time insights about traffic issues, performance, conditions, etc. will help in optimizing and ordering the traffic jam. Correlation with old data can be run to offer city directors a useful insight into the traffic condition. This will help them to directly set traffic signals or recommend different routes that can actually help in decreasing traffic jam.
3. Monitor traffic operations
Keeping an eye on traffic operations via a centralized management dashboard which collects information from various places across the city will serve to decrease the traffic jam. This information can be seen on a geospatial map representing the normal traffic flow and heavy traffic areas to support officials and operators to control the traffic and further simplify their response to different conditions
4. Support the data storage and GIS
City’s transportation system must help in the storage and the presentation of Geographic information system, information for robust and stringent graphical displays in the control system to see things such as traffic amount, density, speed, traffic accidents, etc. It can reveal icons for devices which are present over the city like traffic lights, cameras, and other traffic devices to understand the specific data
The Future of IoT in Controlling Traffic Congestion
Internet of Things (IoT) is already helping and making our lives much better in various ways than we demanded. And this is just beginning. The true power of IoT in ensuring safe driving is yet to be revealed as vehicles step towards becoming completely automated and start communicating with things to make choices on their own. This can open new possibilities and chances such as alert drivers from entering into the traffic places or to avoid collisions. There are different other situations where the true potential of IoT to create new possibilities. Yet we still have a very long way to go to achieve this.