Raspberry PI Based Road Accident Analysis using Data Mining
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Prediction Of The Cause Of Accident And Accident Prone Location On Roads Using Data Mining Techniques
Data mining has been proven as a reliable technique to analyse road accidents and provide productive results. Most of the road accident data analysis use data mining techniques, focusing on identifying factors that affect the severity of an accident. However, any damage resulting from road accidents is always unacceptable in terms of health, property damage and other economic factors. Sometimes, it is found that road accident occurrences are more frequent at certain specific locations. KNN is one of the popular data mining techniques that identify the correlation in various attributes of road accident with the using of pre-defined data sets.
- In the existing system, there is no possibility of the earlier prediction.
- Sensors are only use to detect the roadside problems and accident causes.
- The data mining concepts were not used.
- In our system, here we used the data mining process to predict the accidental causes.
- The location based predictions with using of GPS
- The efficient KNN algorithm will be usedpredict the datamining process.
- Raspberry Pi 3
- Alarming device
- Operating system : Raspbian jessie
- Programming language: Python 2.7
- Data mining algorithm: K-Means Nearest neighbour
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