SignalSense - Towards Quality Service

Book chapter

Islam, S., Sharif, M., Naeem, U. and Geehan, James 2017. SignalSense - Towards Quality Service. in: Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers ACM. pp. 627-630
AuthorsIslam, S., Sharif, M., Naeem, U. and Geehan, James
Abstract

The craving to remain “connected” has exploded since mobile
phones became popular a few decades ago and are now
fully entrenched in our lives as we become more and more
dependent on connected services for professional, daily and
social needs. Despite the significant demand from consumers
and the push towards improved mobile technologies, many
services delivered to the average consumer exhibit poor performance
and quality.
In this paper, we propose SignalSense, a highly interactive and
novel mobile application that senses and records real-time
mobile and wifi signal strength and quality for indoor/outdoor
mapping. The application also uses mobile sensing to crowdsource
signal information and intelligently combines them with
geo-location data to make recommendations to users, leading
to improved user experience. Initial evaluation demonstrates
the need for such an application.

Book titleProceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers
Page range627-630
Year2017
PublisherACM
Publication dates
Print11 Sep 2017
Publication process dates
Deposited11 Sep 2017
EventUbiComp/ISWC'17 Adjunct SmartGuidance Conference, 2017
ISBN978-1-4503-5190-4
Digital Object Identifier (DOI)https://doi.org/10.1145/3123024.3124421
Accepted author manuscript
License
CC BY
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Binkley, David, Harman, Mark, Hassoun, Youssef, Islam, S. and Li, Zheng 2009. Assessing the impact of global variables on program dependence and dependence clusters. Journal of Systems and Software. 83 (1), pp. 96-107. https://doi.org/10.1016/j.jss.2009.03.038
Requirements for the formal representation of pathophysiology mechanisms by clinicians
de Bono, B., Helvensteijn, M., Kokash, N., Martorelli, I., Sarwar, D., Islam, S., Grenon, P. and Hunter, P. 2016. Requirements for the formal representation of pathophysiology mechanisms by clinicians. Interface Focus. 6 (2), p. 20150075. https://doi.org/10.1098/rsfs.2015.0099
An empirical study on dependence clusters for effort-aware fault-proneness prediction
Yang, Yibiao, Harman, Mark, Krinke, Jens, Islam, S., Binkley, David, Zhou, Yuming and Xu, Baowen 2016. An empirical study on dependence clusters for effort-aware fault-proneness prediction. in: Lo, David, Apel, Sven and Khurshid, Sarfraz (ed.) ASE’16 Proceedings of the 31st IEEE/ACM International Conference on Automated Software Engineering IEEE/ACM. pp. 296-307
Towards Cloud Security Monitoring: A Case Study
Ismail, Umar Mukhtar, Islam, S. and Islam, S. 2016. Towards Cloud Security Monitoring: A Case Study. in: 2016 Cybersecurity and Cyberforensics Conference (CCC) IEEE.
High-Frequency Intermuscular Coherence between Arm Muscles during Robot-Mediated Motor Adaptation
Pizzamiglio, Sara, De Lillo, Martina, Naeem, U., Abdalla, Hassan and Turner, D. 2017. High-Frequency Intermuscular Coherence between Arm Muscles during Robot-Mediated Motor Adaptation. Frontiers in Physiology. 7 (668), pp. 1-14. https://doi.org/10.3389/fphys.2016.00668
gUML: Reasoning about Energy at Design Time by Extending UML Deployment Diagrams with Data Centre Contextual Information
Jebraeil, Nigar, Noureddine, A., Doyle, J., Islam, S. and Bashroush, R. 2017. gUML: Reasoning about Energy at Design Time by Extending UML Deployment Diagrams with Data Centre Contextual Information. in: 2017 IEEE World Congress on Services (SERVICES) IEEE. pp. In Press
Cloud Strife: Expanding the Horizons of Cloud Gaming Services
Doyle, J., Islam, S., Bashroush, R. and O'Mahony, Donal 2017. Cloud Strife: Expanding the Horizons of Cloud Gaming Services. in: 2017 IEEE World Congress on Services (SERVICES) IEEE.
A Mutlimodal Approach to Measure the Levels Distraction of Pedestrians using Mobile Sensing
Pizzamiglio, S., Naeem, U., ur Réhman, Shafiq, Sharif, M., Abdalla, H. and Turner, D. 2017. A Mutlimodal Approach to Measure the Levels Distraction of Pedestrians using Mobile Sensing. Procedia Computer Science. 113, pp. 89-96. https://doi.org/10.1016/j.procs.2017.08.297
Recognition of Activities of Daily Living from Topic Model
Ihianle, I., Naeem, U. and Tawil, A. 2016. Recognition of Activities of Daily Living from Topic Model. Procedia Computer Science. 98, pp. 24-31. https://doi.org/10.1016/j.procs.2016.09.007
Measuring energy footprint of software features
Islam, S., Noureddine, A. and Bashroush, Rabih 2016. Measuring energy footprint of software features. in: 2016 IEEE 24th International Conference on Program Comprehension (ICPC) IEEE.
PORBS: A parallel observation-based slicer
Islam, S. and Binkley, David 2016. PORBS: A parallel observation-based slicer. in: 2016 IEEE 24th International Conference on Program Comprehension (ICPC) IEEE.
Efficient Identification of Linchpin Vertices in Dependence Clusters
Binkley, David, Gold, Nicolas, Harman, Mark, Islam, S., Krinke, Jens and Li, Zheng 2013. Efficient Identification of Linchpin Vertices in Dependence Clusters. ACM Transactions on Programming Languages and Systems. 35 (2), pp. 1-35.
ORBS and the limits of static slicing
Binkley, David, Gold, Nicolas, Harman, Mark, Islam, S., Krinke, Jens and Yoo, Shin 2015. ORBS and the limits of static slicing. in: 2015 IEEE 15th International Working Conference on Source Code Analysis and Manipulation (SCAM) IEEE. pp. 1-10
Recognition Framework for Inferring Activities of Daily Living Based on Pattern Mining
Nasreen, Shamila, Azam, Muhammad Awais, Naeem, U., Ghazanfar, Mustansar Ali and Khalid, Asra 2016. Recognition Framework for Inferring Activities of Daily Living Based on Pattern Mining. Arabian Journal for Science and Engineering. 41 (8), pp. 3113-3126. https://doi.org/10.1007/s13369-016-2091-9
Coherent clusters in source code
Islam, S., Krinke, Jens, Binkley, David and Harman, Mark 2013. Coherent clusters in source code. Journal of Systems and Software. 88, pp. 1-24.
Uncovering Dependence Clusters and Linchpin Functions
Binkley, David, Beszédes, Árpád, Islam, S., Jász, Judit and Vancsics, Béla 2015. Uncovering Dependence Clusters and Linchpin Functions. in: 2015 IEEE 31st International Conference on Software Maintenance and Evolution (ICSME) IEEE. pp. 141-150
Activities of daily life recognition using process representation modelling to support intention analysis
Naeem, U., Bashroush, R., Anthony, Richard, Azam, Muhammad Awais, Tawil, Abdel Rahman, Lee, S. and Mou-Ling, Dennis 2015. Activities of daily life recognition using process representation modelling to support intention analysis. International Journal of Pervasive Computing and Communications. 11 (3), pp. 347-371. https://doi.org/10.1108/IJPCC-01-2015-0002
Novel centroid selection approaches for KMeans-clustering based recommender systems
Zahra, Sobia, Ghazanfar, Mustansar Ali, Khalid, Asra, Azam, Muhammad Awais, Naeem, U. and Prugel-Bennett, Adam 2015. Novel centroid selection approaches for KMeans-clustering based recommender systems. Information Sciences. 320, pp. 156-189.
Semantic Process Mining Towards Discovery and Enhancement of Learning Model Analysis
Okoye, Kingsley, Tawil, Abdel Rahman H., Naeem, U. and Lamine, Elyes 2015. Semantic Process Mining Towards Discovery and Enhancement of Learning Model Analysis. in: 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security, and 2015 IEEE 12th International Conference on Embedded Software and Systems IEEE. pp. 363-370
A Semantic Rule-based Approach Supported by Process Mining for Personalised Adaptive Learning
Okoye, Kingsley, Tawil, A., Naeem, U., Bashroush, Rabih and Lamine, Elyes 2014. A Semantic Rule-based Approach Supported by Process Mining for Personalised Adaptive Learning. Procedia Computer Science. 37, pp. 203-210.
Frequent Pattern Mining Algorithms for Finding Associated Frequent Patterns for Data Streams: A Survey
Nasreen, Shamila, Azam, Muhammad Awais, Shehzad, Khurram, Naeem, U. and Ghazanfar, Mustansar Ali 2014. Frequent Pattern Mining Algorithms for Finding Associated Frequent Patterns for Data Streams: A Survey. Procedia Computer Science. 37, pp. 109-116.
Statistical Sampling Approach to Investigate Child Pornography Cases
Sarantinos, N., Al-Nemrat, A. and Naeem, U. 2013. Statistical Sampling Approach to Investigate Child Pornography Cases. 2013 Fourth Cybercrime and Trustworthy Computing Workshop (CTC). Sydney NSW, Australia 21 - 22 Nov 2013 IEEE. https://doi.org/10.1109/CTC.2013.14
A Framework to Recognise Daily Life Activities with Wireless Proximity and Object Usage Data
Azam, M.A., Loo, J., Naeem, U., Khan, S.K.A., Lasebae, A. and Gemikonakli, O. 2012. A Framework to Recognise Daily Life Activities with Wireless Proximity and Object Usage Data. in: Proceedings of 23rd IEEE International Symposium on Personal, Indoor and Mobile Radio Communication 2012 IEEE. pp. 590-595
Behavioural Patterns Analysis of Low Entropy People Using Proximity Data
Azam, M.A., Loo, J., Khan, S.K.A., Naeem, U., Adeel, M. and Ejaz, Waleed 2012. Behavioural Patterns Analysis of Low Entropy People Using Proximity Data. Innovative Information Science & Technology Research Group.
A Comparison of Two Hidden Markov Approaches to Task Identification in the Home Environment
Naeem, U. and Bigham, John 2007. A Comparison of Two Hidden Markov Approaches to Task Identification in the Home Environment. Proceedings of the 2nd International Conference on Pervasive Computing and Applications, Birmingham, UK, 2007, pp. 383-388
Recognising Activities of Daily Life Using Hierarchical Plans
Naeem, U., Bigham, John and Wang, Jinfu 2007. Recognising Activities of Daily Life Using Hierarchical Plans. Proceedings of the 2nd European Conference on Smart Sensing and Context, LNCS 4793, Lake District, UK, 2007, pp. 175-189
A Hierarchal Approach to Activity Recognition in the Home Environment based on Object Usage
Naeem, U. and Bigham, John 2008. A Hierarchal Approach to Activity Recognition in the Home Environment based on Object Usage. Proceedings of the 2008 Networking and Electronic Commerce Research Conference (NAEC 2008), Lake Garda, Italy, 2008, pp. 48-54
Recognising Activities of Daily Life through the Usage of Everyday Objects around the Home
Naeem, U. and Bigham, John 2009. Recognising Activities of Daily Life through the Usage of Everyday Objects around the Home. Proceedings of the 3rd International Conference on Pervasive Computing Technologies for Healthcare. Technologies to Counter Cognitive Decline Workshop London
Activity Recognition using a Hierarchical Framework
Naeem, U. and Bigham, John 2008. Activity Recognition using a Hierarchical Framework. Proceedings of the 2nd International Conference on Pervasive Computing Technologies for Healthcare, Ambient Technologies for Diagnosing and Monitoring Chronic Patients Workshop, Tampere, Finland, 2008, IEEE pp. 24-27