Analysis Based on SVM for Untrusted Mobile Crowd Sensing

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Ms. Yuga. R. Belkhode , Dr. S. W. Mohod

Abstract

Mobile crowdsensing, which collects environmental information from mobile phone users, is growing in popularity. These data can be used by companies for marketing surveys or decision making. However, collecting sensing data from other users may violate their privacy. Moreover, the data aggregator and/or the participants of crowdsensing may be untrusted entities. Recent studies have proposed randomized response schemes for anonymized data collection. We have Developed vehicle Survey Mobile Application for decision making and predict marketing survey. This kind of data collection can analyze the sensing data of users statistically without precise information about other users� sensing results. In this proposed work, we use SVM classifier for classifying the data can be used by companies for marketing surveys or decision making. In which we worked on Parameter of a city, which will help in analyzing vehicle count as well their availability according to vehicle type, vehicle model etc. The Result analyses will directly affects in predicting the result oriented strategies.

Article Details

How to Cite
, M. Y. R. B. , D. S. W. M. (2018). Analysis Based on SVM for Untrusted Mobile Crowd Sensing. International Journal on Future Revolution in Computer Science &Amp; Communication Engineering, 4(4), 388–392. Retrieved from http://ijfrcsce.org/index.php/ijfrcsce/article/view/1534
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