Trends in Mobile Data Analytics Satnam Singh, PhD Senior Chief Engineer, Samsung India Software Operations, Bangalore[Thanks – Ravindra Guntur, Jithendra Vepa, Balvinder Singh and other researchers mentioned in References]
Motivation: Context-Aware Intelligent Devices Image/Music Video Speech LocationGesture Text Acceleration Transform mobile devices into intelligent context-aware systems Learn from user’s context, history of interactions, and state of the physical environment 2
Speech Analytics: Trends • Current Virtual Assistants (VAs):S-Voice [Samsung] Siri [Apple] – Local Search and maps – Weather – Voice dialing, SMS and email, etc. • Future VAs - knowledge- centric Google Voice & Vlingo [Nuance] Google Now • Understand user’s intent [Google] [Beyond Siri] 3
Virtual Assistants Technology Text Text• Future VAs need to perform well in noisy environment 4
Text Analytics: Trends[SGI]- Twitters heartbeat • B2B Applications: Brand building and Social Marketing • Social network-driven Recommendation Engines[Socialbakers] 5
Text Analytics: TechnologyUnstructured Lexiconsor Lexicon orText Corpus Dictionaries or taxonomy or Ontology Ontologies Text Term Representation Clustering and Classification • Beyond “searching” • Enables What-If Analysis, Information Retrieval and Detection 6
Video Analytics: Trends and TechnologyVideo Motion Detection • B2B Applications in Surveillance and Remote Monitoring • Video EnhancementsIntrusion Detection • Technology: Image and Object Recognition, Machine Learning Video Panorama [IntelliVision] 9
Gesture Analytics: Trends• Navigate a smart TV with hand gestures [Tarsier]• Hand gesture-based start and stop music [Flutter] Fluttter• Goodbye to your Mouse and Keyboard [Leap Motion]• Various Users: Surgeons, Gamers, Artists, Engineers 10
Gesture Analytics: Technology • Computer Vision - Template Matching use Semaphores – sign language, Tracking and morphingFeature Extractionand hand detection Pattern Matching with Existing Templates Gesture- (Hidden Markov Driven Models) Control/Action 11
Multi-Model Analytics: Trends • Indoor Maps – airports, hospitals, etc. • 3D Maps- Cool 3D Maps [eeGeo] • Activity Recognition: Detect walking, driving, biking, climbing stairs, standing, etc. [Alohar mobile, ActiServ] 12
Multi-Model Analytics: Technology• Indoor Map Technology- Wi-Fi fingerprinting: Cisco Systems, Qualcomm and indoor map developer Meridian• Indoor Map Startups – [Aisle411,Wifarer, Micello, Meridian, Point Inside and MapEverywhere]• Activity Recognition Technology : A combination of Accelerometer/GPS, timing and wifi data [ActiServ] 13
Summary• Mobile data analytics is still in infancy stage• Mobile Data Analytics: – Would bring innovative features in next generation smartphones (B2C Opportunities) – Transform the businesses through their deep integration in B2B solutions• Future mobile devices would be build on analytics platform and deliver intelligent, personalized, context-aware features and services 14
References• Beyond Siri, http://www.visionmobile.com/blog/2012/06/infographic-beyond-siri-the-next- frontier-in-user-interfaces/• Nuance Communications,• https://www.recognize.im/site/showcaseApps• B. Girod, “Mobile Visual Search,” IEEE Signal Processing Magazine, July 2011.• http://www.usatoday.com/story/tech/2012/11/26/indoor-map-technology-poses-challenges- and-opportunities/1698739/• Tarsier Inc. http://www.moveeye.info/• LeapMotion, https://leapmotion.com/• SGI -Global Twitter Heartbeat, http://www.sgi.com/go/twitter/• Flutter, https://flutterapp.com/• A. Stefan, V. Athitsos, J. Alon, and S. Sclaroff, “Translation and scale-invariant gesture recognition in complex scenes,” ACM PETRA 08• 3D Maps, http://www.mapply.com/ , http://recce.at/• IntelliVision, http://www.intelli-vision.com/products/intelligent-video-analytics/intelligent-video- motion-detector• ActiServ: Activity Recognition Service for Mobile Phones, www.teco.kit.edu/~gordon/publications/ISWC10_berch.pdf 15
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