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SMinder: Detect a Left-behind Phone using Sensor-based Context Awareness

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Abstract

Forget your smartphone in the car again? This happens often in our daily lives, sometimes even makes troubles. In this paper, we present SMinder, an effective, low power approach to remind user take the phone when getting off the car. Based on the context awareness techniques in mobile sensing, we detect the situation of forgetting to take the phone when getting off the car. SMinder requires neither any infrastructure nor any human intervention. It only uses low power smartphone sensors. Namely, the smartphone detects by itself whether it is left behind and remind the user before he leaves the car. SMinder reminds the user with high accuracy and minimum energy consumption, making it realistic for real-world use. Compared to the existing approaches, SMinder is cheaper and easier to use. Our experiments with the prototype system demonstrate the performance, scalability, and robustness of SMinder.

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Notes

  1. The temperature in car can reach 60 °C or more under the sun in summer.

  2. Uber help service: https://help.uber.com.

  3. Accelerometer is used when the smartphone do not have a barometer sensor.

  4. China has the largest smartphone industry in the world since 2009

  5. Didi is the China’s leading taxi-hailing application.

  6. The default value of n is 5 seconds, and can be optimized based on user habits.

  7. iOS: Understanding iBeacon. Apple Inc. February 2015.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China under Grant No.61702261, the China Postdoctoral Science Foundation under Grant No.2017M621742, and the Foundation of State Key Laboratory of Novel Software Technology under Grant No.KFKT2017B15.

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Authors and Affiliations

  1. College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, People’s Republic of China

    Haibo Ye & Zhiqiu Huang

  2. School of Computer Science and Engineering, Southeast University, Nanjing, 211189, People’s Republic of China

    Kai Dong

  3. School of Computer Science and IT, RMIT University, Melbourne, Australia

    Tao Gu

Authors
  1. Haibo Ye
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  2. Kai Dong
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  3. Tao Gu
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  4. Zhiqiu Huang
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Correspondence to Haibo Ye.

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Ye, H., Dong, K., Gu, T. et al. SMinder: Detect a Left-behind Phone using Sensor-based Context Awareness. Mobile Netw Appl 24, 171–183 (2019). https://doi.org/10.1007/s11036-017-0987-6

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  • DOI: https://doi.org/10.1007/s11036-017-0987-6

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