Phone Call Detection Based on Smartphone Sensor Data

Smartphones are now equipped with as many as 30 embedded sensors, which have been widely used in human activity recognition, context monitoring, and localization. In this paper, we propose a phone call detection scheme using smartphone sensor data. We design Android applications to record, upload and display smartphone sensor data. We show how proximity and orientation sensors together can be used to accurately predict phone calls. Furthermore, the activity state during a phone call can be classified into three categories: sitting/standing, lying down, and walking. Features are extracted from proximity and orientation sensors to determine the range of values satisfying each state. Our system achieves an overall accuracy of 85 %.

[1]  Xingming Sun,et al.  Enabling Personalized Search over Encrypted Outsourced Data with Efficiency Improvement , 2016, IEEE Transactions on Parallel and Distributed Systems.

[2]  Toshiyo Tamura,et al.  A Wearable Airbag to Prevent Fall Injuries , 2009, IEEE Transactions on Information Technology in Biomedicine.

[3]  Tobi Delbrück,et al.  Proximity Sensing Based on a Dynamic Vision Sensor for Mobile Devices , 2015, IEEE Transactions on Industrial Electronics.

[4]  Dong Xuan,et al.  Mobile phone based drunk driving detection , 2010, 2010 4th International Conference on Pervasive Computing Technologies for Healthcare.

[5]  Gary M. Weiss,et al.  Activity recognition using cell phone accelerometers , 2011, SKDD.

[6]  Hiroyuki Oneyama,et al.  Formulation of a simple model to estimate road surface roughness condition from Android smartphone sensors , 2014, 2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP).

[7]  Alar Kuusik,et al.  Acceleration data acquisition and processing system for structural health monitoring , 2014, 2014 IEEE Metrology for Aerospace (MetroAeroSpace).

[8]  Naixue Xiong,et al.  Steganalysis of LSB matching using differences between nonadjacent pixels , 2016, Multimedia Tools and Applications.

[9]  Gang Chen,et al.  Color Image Analysis by Quaternion-Type Moments , 2014, Journal of Mathematical Imaging and Vision.

[10]  Luciano Bononi,et al.  By train or by car? Detecting the user's motion type through smartphone sensors data , 2012, 2012 IFIP Wireless Days.

[11]  Ke Lu,et al.  $p$-Laplacian Regularized Sparse Coding for Human Activity Recognition , 2016, IEEE Transactions on Industrial Electronics.

[12]  Xingming Sun,et al.  Segmentation-Based Image Copy-Move Forgery Detection Scheme , 2015, IEEE Transactions on Information Forensics and Security.

[13]  Min Chen,et al.  Energy-Efficient and Context-Aware Smartphone Sensor Employment , 2015, IEEE Transactions on Vehicular Technology.

[14]  Jia Li,et al.  WiFi based indoor localization with adaptive motion model using smartphone motion sensors , 2014, 2014 International Conference on Connected Vehicles and Expo (ICCVE).

[15]  Zhihua Xia,et al.  Steganalysis of least significant bit matching using multi-order differences , 2014, Secur. Commun. Networks.

[16]  Bin Li,et al.  Detection of in-progress phone calls using smartphone proximity and orientation sensors , 2017, Int. J. Sens. Networks.

[17]  Filip De Turck,et al.  User-driven design of a context-aware application: An ambient-intelligent nurse call system , 2012, 2012 6th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth) and Workshops.

[18]  Huiyu Sun,et al.  Big Data Mobile Services for New York City Taxi Riders and Drivers , 2016, 2016 IEEE International Conference on Mobile Services (MS).

[19]  Ozgur Yurur,et al.  Adaptive and Energy Efficient Context Representation Framework in Mobile Sensing , 2014, IEEE Transactions on Mobile Computing.

[20]  Xingming Sun,et al.  Achieving Efficient Cloud Search Services: Multi-Keyword Ranked Search over Encrypted Cloud Data Supporting Parallel Computing , 2015, IEICE Trans. Commun..

[21]  Moe Z. Win,et al.  A smartphone localization algorithm using RSSI and inertial sensor measurement fusion , 2013, 2013 IEEE Global Communications Conference (GLOBECOM).

[22]  Ahmed Ghoneim,et al.  A Triaxial Accelerometer-Based Human Activity Recognition via EEMD-Based Features and Game-Theory-Based Feature Selection , 2016, IEEE Sensors Journal.

[23]  Hongbo Jiang,et al.  SensTrack: Energy-Efficient Location Tracking With Smartphone Sensors , 2013, IEEE Sensors Journal.

[24]  Shaharyar Kamal,et al.  Real-time life logging via a depth silhouette-based human activity recognition system for smart home services , 2014, 2014 11th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS).

[25]  Kalaiarasi Sonai Muthu,et al.  Classification Algorithms in Human Activity Recognition using Smartphones , 2012 .

[26]  Ralph Grishman,et al.  Active learning based named entity recognition and its application in natural language coverless information hiding , 2017 .

[27]  Gary M. Weiss,et al.  Actitracker: A Smartphone-Based Activity Recognition System for Improving Health and Well-Being , 2016, 2016 IEEE International Conference on Data Science and Advanced Analytics (DSAA).

[28]  May El Barachi,et al.  Mobile Phone Sensing as a Service: Business Model and Use Cases , 2013, 2013 Seventh International Conference on Next Generation Mobile Apps, Services and Technologies.

[29]  Niwat Thepvilojanapong,et al.  WINFO+: Identification of Environment Condition Using Walking Signals , 2009, 2009 Tenth International Conference on Mobile Data Management: Systems, Services and Middleware.

[30]  Li-Chun Wang,et al.  A Proximity Sensor Based No-Touch Mechanism for Mobile Applications on Smart Phones , 2012, 2012 IEEE Vehicular Technology Conference (VTC Fall).

[31]  Paul J. M. Havinga,et al.  Towards Physical Activity Recognition Using Smartphone Sensors , 2013, 2013 IEEE 10th International Conference on Ubiquitous Intelligence and Computing and 2013 IEEE 10th International Conference on Autonomic and Trusted Computing.

[32]  Zhihua Xia,et al.  A Secure and Dynamic Multi-Keyword Ranked Search Scheme over Encrypted Cloud Data , 2016, IEEE Transactions on Parallel and Distributed Systems.

[33]  Xingming Sun,et al.  Structural Minimax Probability Machine , 2017, IEEE Transactions on Neural Networks and Learning Systems.

[34]  Emanuele Lindo Secco,et al.  A Real-Time and Self-Calibrating Algorithm Based on Triaxial Accelerometer Signals for the Detection of Human Posture and Activity , 2010, IEEE Transactions on Information Technology in Biomedicine.

[35]  Calvin C. Newport,et al.  Aggregation in Smartphone Sensor Networks , 2014, 2014 IEEE International Conference on Distributed Computing in Sensor Systems.

[36]  Jie Zhang,et al.  Indoor localization using smartphone inertial sensors , 2014, 2014 11th Workshop on Positioning, Navigation and Communication (WPNC).

[37]  Debopam Acharya,et al.  Contextual sensitivity of the ambient temperature sensor in Smartphones , 2015, 2015 7th International Conference on Communication Systems and Networks (COMSNETS).