Convergence of Engineering and ICT will grow IoT

Tan Guan Hong

Senior Director, Smart Nation Systems and Solutions

Government Technology Agency of Singapore

The Convergence of Engineering and ICT will

grow the IoT sector

ST Electronics Technology Seminar 2017Engineering with Passion - Smart, Secure, Connected

24 May 2017

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IoT Vertical Stacks

Sensors

Communication

Data Centre

Visualization & Support

Video Analytics

Data Science

Define the IoT Eco-SystemS

yste

m E

ng

ineeri

ng

Cyb

er

Sec

uri

ty


Consumer IoTIIoT or Industrie 4.0

Structured Work Process with SOPs

Paid to provide Service

Unstructured Process as dealing with individuals

Pays for Service

Focus on Efficient and Outcomes Conflicting individual goals for self interest & benefit

Highly fragmented, flexible and change over

time fast

Inflexible and Large Organisations,

no single individual ownership

IoT

Influence by stake holders and KPIs Influenced by individuals, social behaviour

and friends

Consumer facingProcess Driven

B2B IoT , Enterprise IIoT or Industrie 4.0

(Reliable Focus)

B2C IoT , Consumer IoT (Cost Focus)


The need for both ICT and Engineering domains to collaborate to grow the IoT sector together

The ICT is growing rapidly with many new technologies, while the Engineering provides

insights to the Physical World inwhere humans interact with


Hydrostatic

Water Level

Thermometer

Accelerometer

CCTV

Signal/Video

Processing

into

Engineering

Data

EngineeringDomain

Numeric

representation of

sensor output

e.g. 3.27

Unit to know the

Physical

representation

e.g. psi, oC , G

SQL

IoT

Applications

Mobile Apps

ICT Domain

Decision making using Apps

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High Repeatability

High Accuracy

High Repeatability

Low Accuracy

Low Repeatability

High Accuracy

Low Repeatability

Low Accuracy

Sensor

7

Output of

every

physical

sensor has

Statistical

uncertainties

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Understanding the Data Flow from Physical Parameters pick up by Sensors, Data Quality from Sensors and Data Risk AcceptanceNOT just Availability of Data alone

Sensor

You could also be Sensing unwanted Noise!

SQL

Physical Sensor output can be affected by

Data corruption from

EMI Noise, Humidity, Temperature, Pressure,

Vibration (Lose connections)

Output of data is taken

from a Database and

usually many trust this

data !

When retrieved from SQL dB, the data is Highly

Repeatable and Accurate !

System is Auditable and Computers don’t lie ! ☺

ICTEngineering


Two-dimensional (2D) camera: These sensors capture data over time frames. Using various video

analytics algorithms, these 2D camera sensors can provide different information. For example, within

the same image, the algorithms can extract information such as (i) people count, (ii) number and color

of cars (iii) lighting condition, etc. Over time, processed metadata can yield further insights such as

tracking of (iv) people’s movement, (v) dwell time, etc.

Sensor

IoT Sensor Devices:-

Slow Sensor Data: Temperature, Humidity, Hydrostatic pressure, Strain Gauge, Tilt and Infra-red

sensors acquire data in minutes or hours. These are Quasi-static sensors.

Dynamic (Fast) Sensor Data: Accelerometer provides G m/s2 in milliseconds or faster. Acoustic

sound sensor provides voltage signals over time. When these sensor data are processed in the

Frequency Domain using Fast Fourier Transform, the data can provide Peak Vibration Level at various

Frequencies.


Sensor Measurement Error due to aliasing

Sensor

9


Understanding Measurement Principle is important !

Actual

Temperature

Sampled

Temperature

Displayed

Temperature

Nyquist

Frequency:-

Sample at

least Twice

the Highest

frequency

Temperature don’t

change at all !

If sample too slow

Temperature is

actually

fluctuating

Sensor

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Accuracy of Information depends :-

Accuracy of SensorMaintenance & Calibration of Sensor (Function of Time, Drift, Deterioration )

Video Analytics is Processing of Image Data into Structured Information

Accuracy and Repeatability only in controlled environment

Installation of SensorUse of Sensor in its context (monitoring & control function)

Expected functional accuracy for decision making

ICT’s view is sensor data is stable, repeatable and maintenance free !

While an Engineering view is always drift, accuracy and noise

ICT is in Cyber World while Engineering view is deployment into

physical environment which Mother Nature controls)

Sensor

11


Accuracy of SensorsAverage Water Depth of 10 m

Water Depth variation of +/- 0.5 m @ 0.1 Hz

in flowing canals+ 0.5 m

- 0.5 m

Acceptable Accuracy is then +/- 0.25 m

Expected Physical Accuracy to measure

Sensor accuracy needs to be x 2 better to be

cost effective

10 m

Sensor when used outdoor deteriorates over time

Regular Cleaning maintenance, validation and re-calibration

Sensor diaphragm membrane is stiffened by barnacles,

hence affect the readings

Sensor


Accelerometer

Sensor on

Railway Track

Digitizer

Electro Magnetic Interference from

Motors, Welding Equipment, etc

Digital DataAnalogue Signals

Use of a Spectrum

Analyzer to check the

Signal to Noise Ratio to

verify Quality of Signal

presented to the Digitizer

Wanted Sensor Signal

EMI Noise

1.0 G = 0.9 G + 0.1 G

= 0.8 G + 0.2 G

Real Data Noise

Sensor

When train passes over the Railway track, it

generates 1.0 KHz vibration levels

What G number are you

actually measuring ?

Signal to Noise Ratio

13

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Work stoppages due Drop in Sensor readings due to

Electro-Magnetic Interference

Sensor

LTA Real Time

Temporary

Strut Force

Readings

Load (

kN

)

Lunch Lunch

200 kN

Fluctuating

reduction in

Load = Weight of

15 Merc E200

Can also mean that site

diaphragm wall is collapsing


Using Camera as a Sensor

• Accurate & Reliable Data

• Outdoor Operating Conditions are

huge challenges

• One Camera gives many Metadata

and is a Contactless Sensor

Camera as a Sensor


Video

Analytics

Image Processing, Video and Data Analytics

Y

X

Within one Image Frame (Array of many

colour pixels) , Image Processing extracts

Motorcycle & Rider, Number & Colour of

Cars, Ambient light, Angle of sun wrt camera,

Number of People in zebra crossing

Cam#5 @

Location C

Video

Analytics

Cam#1 @

Location A

By tracking Motorcycle & Rider, Cars, People

in Zebra crossing over time frames, the speed

and dwell time of each object can be

determined

With these processed structured data with

other data sets from different cameras, Data

Analytics can be used to track any object

over time & space (Geo Location)

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Camera as a Sensor


Camera as a SensorHigh Value Real Time Analytics rather than Forensic

People & Object DetectionDetection of Road

Surface Flood But Not like this

Deployment !

Road Surface Flood

CCTV can be used for:-

Counting Cars, Bicycles

and Humans

Lighting

People Crossing @

Junction

Debris on Roads and

Pavements

Visible Water Pollution

Water level, Water flow

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http://www.pbs.org/wgbh/nova/next/tech/the-limits-of-facial-recognition/

The Real Truth about using Video

Analytics to trace the Boston Bombing !

Camera as a Sensor


System Engineering Approach

Sensors Comms Video Analytics

For a system to work, all 3 sub-blocks must work

Up time++

Each sub-block has 2 states, “0” Not-working Logic

and “1” Working Logic

This system has 2 x 2 x 2 possible combinations (23= 8)

System Engineering


The system has 3 functional sub-blocks

0 0 00 0 10 1 10 1 01 0 01 1 01 0 11 1 1

For system to work, the probability is

1/8 = 12%

The possibility of system not working

is 7/8= 88% !

When getting it to work, can you

assume that the person has the skills

to troubleshoot any of the 7/8 ?

UnlikelyIoT Stack

Sensors

Communication

Data Centre

Visualization & Support

Video Analytics

Data Science

is 26 = 64

1/64=1.5%

System Engineering


We are trained on how it works

but we are NOT trained to get a

non-working to work…

Troubleshooting demands a

wider range of skills and

innovations

System Engineering


Priority of System

Specification

1.Functionality

2.Performance

3.Reliability

4.Convenience

5.Price

System Engineering


Commissioning

at functionality

level only

After 6~12 months for

outdoor systems if design

without reliability built-into

the system

Reliability

Thank you!

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Convergence of Engineering and ICT will grow IoT

Data & Analytics

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