5.) Other Applications of a Smart Traffic Control Module
Although the development of smart traffic controllers seems like a very targeted problem statement, the solution can be utilised for various applications with minor tweaking, provided that the components are designed in a modular fashion. Here are some of the other applications of a smart traffic control module, where the problem at hand is similar to that of adaptive traffic management.
- Smart Elevator Scheduling – Cameras installed on each floor of a building can be used to optimise the performance of an elevator system comprising of multiple elevators. These elevators will have the information regarding the number of people waiting to go up or down on a particular floor and will also be able to communicate with each other, so that they may share the load equally and more efficiently. This is a similar problem statement to that of a traffic control system and the basic infrastructure created using machine learning and IoT can be reused.
- Adaptive Bus Routes – Public transport can be optimised by collecting data at the various bus stations regarding the number of passengers for a particular route at a particular time of day. This can be used to adapt the frequency and the routes of buses, so as to optimise the waiting time of the travellers. Again, this is a problem that can be closely mapped to the traffic control problem at hand.
- Smart Staff Management – In the case of businesses such as restaurants and call centres, the number of employees assigned to a particular shift can be optimised by monitoring the customer traffic at different times of the day. This problem may not require the principles of the Internet of Things but it will definitely benefit from a timing logic as explained in the previous sections. Therefore, creating a modular design where each component works independently of the others can help in reusing some parts of your original design for other applications.
As explained by the above examples, the devices of the future will run on a technology that processes the current data as well as the previously recorded information and interacts with other devices to make smart decisions. This is the combined potential of machine learning and IoT which we have demonstrated today for the more focused problem of traffic management. In the near future, it is possible that our cities are managed using these intelligent systems and devices that can make decisions without human intervention.
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