Efficient Churn Prediction System with Ml-IoT

  • R.Gowthamani, K.Sasi Kala Rani, S.Anandha Swarna, C.Bharathi Priya, M.Akil Vishnu, Malladi Srinivas, Pankaj Dadheech

Abstract

In today’s situation, where time and patience of people are so rare, we mainly focus on the four cross junctions in our project because the traffic gets cleared with less time in comparison with the single road. Although both the situations are hectic, the four cross roads are worse due to waiting for no reason. And so we designed a dynamic system to manage the traffic in an effective way using machine learning and IOT. The thing which works with the connection of internet is called IOT. There are millions and millions of data being processed each minute and normal storage devices are not possible to store these data. These data are processed and stored in the cloud. The cloud is a massive storage where you can access it from anywhere and through any device. The above described concepts are used in this project effectively. We proposed a new technology used for four way roads by using sensors for calculating the distance of the vehicle, and store the vehicle and time count by using sensor. Sensor finds the distance of vehicle and compares it with the big data values. Then the signal is determined using the data sensed from the sensors. When the road is clear till hundred meters, the signal turns red at that road and signal green is diverted to next road which prevents waiting time thus applying the support vector machine algorithm.

Published
2020-04-13
How to Cite
R.Gowthamani, K.Sasi Kala Rani, S.Anandha Swarna, C.Bharathi Priya, M.Akil Vishnu, Malladi Srinivas, Pankaj Dadheech. (2020). Efficient Churn Prediction System with Ml-IoT. International Journal of Advanced Science and Technology, 29(3), 8251 - 8258. Retrieved from https://sersc.org/journals/index.php/IJAST/article/view/9082
Section
Articles