Upload
arpan-pal
View
24
Download
0
Tags:
Embed Size (px)
Citation preview
1 Copyright © 2014 Tata Consultancy Services Limited
Analytics as a Service for IoTDr. Arpan PalPrincipal Scientist, Innovation LabTata Consultancy Services Ltd.India
April 15, 2023
2
The Internet of Everything
Humans
Physical Objects and Infrastructu
re
Computing Infrastructu
re
Peo
ple
Con
text
Dis
cove
ry
PhysicalContext Discovery
INTERNET OF EVERYTHING
Physical Context
DiscoveryWhat is happening,
where and when
People Context Discovery
Who is doing what, where and when, who is
thinking what
Internet of
Digital
Internet of
Things
Internet of
Humans
ABI Research. May 7, 2014
3
Understanding the Physical Context
New Business / Pricing Models, Always On–Anytime–Anywhere, Secure, Context-aware - need to guarantee ROI for sustainability
Enables real-time monitoring to reduce downtime, reduce cost of maintenance and improve personnel safety, predicts wind-speed to improve productivity
Enables crop scouting and mapping of farmland to improve productivity of the farmers
4
Understanding the People Context
Non-intrusive, un-obtrusive sensing
Identity, Location, Activity, Physiology
Understand Behavior – Individuals / Groups
Quantified Self
Customer becomes the focus, not the product or service – key is understanding the Customer, Extend B2B to B2B2C
5
Platform Requirements for IoT
TCS Connected Universe Platform (TCUP)A horizontal platform for addressing the IoT Software and Services market
Applications need support for
VisibilityCapture & store data from sensors
InsightsPatterns, relationships and models
Control Optimize and actuate
TCUP Platform
Analytics is the Key
6
IoT Analytics – what does it really mean?
http://www.ciandt.com/card/four-types-of-analytics-and-cognition
7
Challenges for IoT Analytics
Scalability – Distributed Computing
Affordability – Reusability
Fusion – Sensor Data and Error Modeling
Ease-of-Development – Address Complexity
S
A
E
F
A sensor techie An embedded programmer A cloud programmer An algorithm expert A domain specialist An infrastructure expert
The App Developer needs to be
8
Analytics-as-a-Service
Distributed Computing Infrastructure for IoT (Fog Computing)
Analytics Algorithm Repository for IoT (Algopedia)
Planning Prognostics
Causal Analytics
Behavior Sensing Measurement Anomaly
Detection
Algorithm Recommendati
on: Ease-of-Development and Fusion
Analytics Libraries: Affordability via Reuse
Base TCUP Platform (Sensor Data Transport, Storage and Analysis)
Compute Scalability: Utilize Edge
Devices
Prescriptive DescriptiveDescriptiveDescriptivePredictive Diagnostic
9
Model-driven-development for IoT – Separation of Concerns through Knowledge Modeling
• Knowledge models include rules, ontologies, Information flow graphs, physical models
• Ratified / Augmented by experts (domain, sensor, algorithm and infrastructure)
10
Sensor-agnostic Anomaly Detection – Remote Health Monitoring
Sensed data – PPG, ECG, HR,
BP, Heart Sound, Smart-
Meter …..
Outlier Detection
Information Measure
Generate Alerts
based on critical
information
Preventive Healthcare
Promote WellnessSensor agnostic outlier analysis
library
Refer to Doctors
Being Tested on ECG, PPG and EEG Data• Anomaly within same source, same
time• Anomaly within same source,
different time• Anomaly between different sources• Can also be used for Adaptive
Compression
11
Behavior Sensing – Crowd sourcing of people context using mobile phones
Indoor Localization – Bldg, Mall
• Entry-Exit and Zoning• Fine-grained positioning
Activity Detection - Wellness• Walking / Brisk Walking / Jogging /
Running• Calorie Burnt
Traffic Sensing – City Authority• Congestion Modeling• Honk Detection• Road Condition Monitoring
Driving Behavior - Insurance• Hard Cornering / Breaking
Magnetometer – Entry/Exit
WiFi -Zoning Bluetooth -Proximity
RFID Fusion
98% 97% 96% 99.7%
(Accuracy ~2m)
(Accuracy ~ 98%)
Mobile phone sensors – Magnetometer, Wi-Fi, Bluetooth, Accelerometer, Microphone, GPSKnowledge – Sensor Noise Models
12
Vision: Democratizing IoT App Development
I only know the business logic, I do not know how to code, nor
do I understand analytics algorithms…
I know how to code, but I do not know algorithms, nor do I know about the
business logic…
Oh, I know algorithms, but I can’t code for
your mobile devices…
I have all these cloud and edge nodes which you can use to deploy
the app…
Need of the Day - Knowledge-driven Framework for IoT App Development
13
Publication List
Anomaly Detection and Compression1. A Ukil, et. al., “Adaptive sensor data compression in IoT systems: sensor data analytics based Approach”,
ICASSP 20152. One more
Crowd-sensing via Mobile Phones3. Nasimuddim Ahmed et. al., ""SmartEvacTrak: A People Counting and Coarse-Level Localization Solution for
Efficient Evacuation of Large Buildings“, CASPER'15 workshop of IEEE Percom 20134. Sourjya Sarkar et. al. “Improving the Error Drift of Inertial Navigation based Indoor Location Tracking” , IPSN
20155. Vivek Chandel et.al., "AcTrak - Unobtrusive Activity Detection and Step Counting using Smartphones“,
Mobiquitous 20136. Ghose, Avik et. al., "Road condition monitoring and alert application: Using in-vehicle smartphone as internet-
connected sensor.“, Percom Workshops 2012.7. Tapas Chakravarthy et. al., “MobiDriveScore — A system for mobile sensor based driving analysis: A risk
assessment model for improving one's driving”, ICST 20138. Maiti, Santa, et al. "Historical data based real time prediction of vehicle arrival time." ITSC 2014
3D Vision based Measurements9. Saha, Arindam et. al.,"A System for Near Real-Time 3D Reconstruction from Multi-view Using 4G Enabled
Mobile." IEEE Mobile Services (MS), 201410.Brojeshwar Bhowmick et. al., “Mobiscan3D: A low cost framework for real time dense 3D reconstruction on
mobile devices”, IEEE UIC 2014
Model-driven Development11.A. Pal et al., “Model-Driven Development for Internet of Things: Towards Easing the Concerns of Application
Developers,” IoT as a Service (IoTaaS), 201412.S. Dey et al., “Challenges of Using Edge Devices in IoT Computation Grids,” ICPADS 2013
IoT Platform13.P. Balamuralidhara et al., “Software Platforms for Internet of Things and M2M,” Journal of. Indian Inst. of
Science 14.www.tcs.com/about/research/Pages/TCS-Connected-Universe-Platform.aspx
14
TCS at a Glance
Bangalore, India1
Chennai, India2
Cincinnati, USA3
Delhi, India4
Hyderabad, India5
Kolkata, India6
Mumbai, India7
Peterborough, UK8
Pune, India9
2000+
Associates in Research, Development and Asset Creation
1 2
3
4
597
6
8
10
Singapore10
iCity Lab - Collaboration with Singapore Management University – Elderly Care, Mobile Sensing
46+
13.44
Billion US$ in Q1-FY15 revenues *
305,431
119
55+ Countries where TCS has presence
Employees*
Nationalities
Source: Figures from TCS Analyst Report FY Q1-15 Employee count includes that of TCS subsidiaries
Years in Business
3.694
Billion US$ in FY14 revenues
Innovation @ TCS
15
Thank [email protected]