%0 Journal Article %1 noauthororeditor %A Muralidhar, Dr. B. Srinivasa Rao U. Sri Devi K. Sri Satya Harsha A. Rakesh K. %D 2018 %J International Journal of Trend in Scientific Research and Development %K (Support Abnormal Computers Driving Engineering KNN(k-Nearest Machine) Neighbors) SVM Smart Vector alerts behaviors phone sending sensors %N 3 %P 1384-1387 %T Abnormal Driving Behaviors detection with smart phones %U http://www.ijtsrd.com/engineering/computer-engineering/11339/abnormal-driving-behaviors-detection-with-smart-phones/dr-b-srinivasa-rao %V 2 %X Abnormal driving behaviors detection is a key stone for reducing accidents. There are several existing works for abnormal driving detection which uses high cost sensors to check whether the driver is in normal state or in drunken state. In this paper we would like to introduce a low cost technique for detecting abnormal driving behaviors with the use of some in built Smartphone sensors. With the information collected from the sensors we will employ the machine learning technique (SVM and KNN) to extract the features and for generating a classifier model. We will send the alerts if abnormality is detected. Dr. B. Srinivasa Rao | U. Sri Devi | K. Sri Satya Harsha | A. Rakesh | K. MuralidharÄbnormal Driving Behaviors detection with smart phones" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-3 , April 2018, URL: http://www.ijtsrd.com/papers/ijtsrd11339.pdf http://www.ijtsrd.com/engineering/computer-engineering/11339/abnormal-driving-behaviors-detection-with-smart-phones/dr-b-srinivasa-rao

@article{noauthororeditor, abstract = {Abnormal driving behaviors detection is a key stone for reducing accidents. There are several existing works for abnormal driving detection which uses high cost sensors to check whether the driver is in normal state or in drunken state. In this paper we would like to introduce a low cost technique for detecting abnormal driving behaviors with the use of some in built Smartphone sensors. With the information collected from the sensors we will employ the machine learning technique (SVM and KNN) to extract the features and for generating a classifier model. We will send the alerts if abnormality is detected. Dr. B. Srinivasa Rao | U. Sri Devi | K. Sri Satya Harsha | A. Rakesh | K. Muralidhar"Abnormal Driving Behaviors detection with smart phones" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-3 , April 2018, URL: http://www.ijtsrd.com/papers/ijtsrd11339.pdf http://www.ijtsrd.com/engineering/computer-engineering/11339/abnormal-driving-behaviors-detection-with-smart-phones/dr-b-srinivasa-rao }, added-at = {2018-09-04T14:02:33.000+0200}, author = {Muralidhar, Dr. B. Srinivasa Rao U. Sri Devi K. Sri Satya Harsha A. Rakesh K.}, biburl = {https://www.bibsonomy.org/bibtex/20d9a6dd7ae612d91f1e0a8e08f757e5a/ijtsrd}, interhash = {7a7961dcba623843573395f6e0c1cf9b}, intrahash = {0d9a6dd7ae612d91f1e0a8e08f757e5a}, issn = {2456-6470}, journal = {International Journal of Trend in Scientific Research and Development}, keywords = {(Support Abnormal Computers Driving Engineering KNN(k-Nearest Machine) Neighbors) SVM Smart Vector alerts behaviors phone sending sensors}, language = {English}, month = {April}, number = 3, pages = {1384-1387}, timestamp = {2018-10-02T11:01:27.000+0200}, title = {Abnormal Driving Behaviors detection with smart phones }, url = {http://www.ijtsrd.com/engineering/computer-engineering/11339/abnormal-driving-behaviors-detection-with-smart-phones/dr-b-srinivasa-rao}, volume = 2, year = 2018 }