PROJECT TITLE :

Automatic Identification of Driver’s Smartphone Exploiting Common Vehicle-Riding Actions - 2018

ABSTRACT:

Texting or browsing the net on a smartphone while driving, referred to as distracted driving, considerably increases the chance of automotive accidents. There have been a number of proposals for the prevention of distracted driving, but none of them has addressed its necessary challenges utterly and effectively. To remedy this deficiency, we gift an occurrence-driven solution, called Automatic Identification of Driver's Smartphone (AIDS), which identifies a driver's smartphone by analyzing and fusing the phone's sensory info connected to common vehicle-riding activities, like walking toward the vehicle, standing close to the vehicle whereas gap a vehicle door, coming into the vehicle, closing the door, and starting the engine. AIDS extracts options helpful for identification of the driver's phone from numerous sensors obtainable in commodity smartphones. It identifies the driver's phone before the vehicle leaves its parked spot, and differentiates seated (front or rear) rows in a very vehicle by analyzing the subtle electromagnetic field spikes caused by the beginning of the engine. To evaluate the feasibility and adaptableness of AIDS, we tend to have conducted in depth experiments: a prototype of AIDS was distributed to 12 participants, each men and women in their 20 and 30s, who have driven seven completely different vehicles for three days in real-world environments. Our evaluation results show that AIDS identified the driving force's phone with an 83.3-ninety three.3 percent true positive rate while achieving a ninety.1-ninety one.a pair of % true negative rate at a marginal increase of the phone's energy consumption.


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