In simple terms, the Internet of Things refers to the inter-connectivity of different devices over the internet, so that they may send or receive data without human intervention. This could be the communication between the security system and the appliances of a house, so that they may turn off whenever the house is locked from the outside, or a message sent by your smartphone to your microwave oven to start heating your food when you are a few minutes away from home. When it comes to smart traffic control systems, IoT can be extremely useful in establishing communication channels between the different traffic intersections, over the internet.
Transmission of the current traffic data between neighbouring intersections, over a wireless network, can be utilized to further improve the timing algorithms at each intersection. Now, instead of taking the traffic data at just one intersection into account, the algorithm will also provide some weightage to the traffic conditions at other intersections. For example, if a particular direction of traffic is severely jammed at one intersection, the green time of that lane at the next intersection will also be increased to improve the speed of the flow of traffic in that direction.
Furthermore, the cameras can also be used to detect accidents and roadblocks, the notification for which can then be transmitted to all the neighbouring intersections. This will require additional training using machine learning, so that the controller may correctly identify accident sites and construction zones, based on training images of similar sites fed into the system at the time of implementation. Such information about congestions can then be displayed on digital sign boards to notify the drivers regarding the blockages ahead, so that they may opt for a different route.
The concept of IoT can be further extended to send these traffic notifications to the phones of the users who have installed the corresponding traffic notification app. Similar data can also be sent to the cars in the vicinity so that the car software can provide better directions to reach the destination, based on the current traffic conditions.
What is more, the investment in this technology does not cater solely to the purpose of traffic management but can also be used for reporting hit and run cases and accidents to the local police department, with the help of the detection of collisions in the captured images.
To summarize, the introduction of IoT in traffic systems will lead to the development of well-connected traffic grids that will not only enable smarter traffic control but will also help in accident management and in the optimization of traffic flow in the case of urgent blockage of a particular road.
Although the development of an efficient traffic control algorithm using IoT may seem complicated, with sufficient knowledge of machine learning, image processing, and data handling, it can be designed without much difficulty. Such a design may require initial trial runs to achieve an optimal performance, but the benefits of a smart traffic control grid make it worth the effort and investment.
In the next section, we will try to understand the full potential of such adaptive systems by discussing other applications where this adaptive control model can be reused.