IoT: Real-Time Information from the Real-World Karthik Kumar Viswanathan

Introduction

The first IoT Device, possibly known

• Coca-Cola Machine ca. Late 70s.

• This was the Data you could see:

• Those two lower buttons could give you a Cold Drink. Two on the right had beverages that were loaded an hour ago. The Other two were empty.

Agenda

• What is IoT?

• What makes up IoT?

• IoT Data

• What can you do with the Data?

• A word on Sustainability

• Questions?

What is IoT?

• The Internet of Things = Things connected to the Internet

• They usually send valuable data acquired from sensors to the manufacturer or the operator

• Each Thing has a Unique ID

• You can act upon it immediately, or ….

• You can aggregate it over a period of time.

What makes up IoT?

• Unique IDs

• Sensors

• Processors

• Communication

• Responses

Unique IDs

• Identifier Grid

• NFC/RFID

• Barcodes/QR Codes

• Digital Watermarking

• BD-ROM Mark

• IP Addresses

• Any number

Unique IDs

• IDs are mapped to Static Data and Dynamic Data

• What creates an ID?

• Let’s take an example: There are 2^46 physical devices which could each have a Mac Address. Out of these, 24 bits are for your device. 22 bits are for the manufacturer. 2 bits tell you if the device is unicast, and another bit tells you if it is OUI enforced/locally enforced.

• Shared by Ethernet/WiFi and Bluetooth. All are EUI-48s.

Unique IDs

• So much skew in network manufacturers

• Cisco owns 1074 out of the 2^22

• Apple itself has 284 of them. Thanks to an error. And a lot of $$$$$$$

• Intel has 266

• Broadcom has 50

• Realtek has 6

Unique IDs

• What creates an ID? IP addresses are just going to take the path that Mac addresses did. Essentially, usage drives ID adoption.

• “2^32 addresses ought to be enough for everybody.”

• Or IPv6. If everyone agrees well -> Every Mac address has its own IPv6 address.

• IPv6 has 4.2*10^37 devices. But the question is - Will it Blend?

Unique IDs

• You can also adopt a different scheme…

• Zigbees have 2^16 networks, 2^64 devices per network.

• (2^16) more like private network devices.

• If you had devices with all of these IDs, would it make sense to keep them identifier with a URI?

• Conclusion: Unique IDs are there to stay, and if you have your own, you use them. Map them to static or dynamic data!

Sensors

• Allow us to measure something

• Measurement curves are linear or non-linear

• Some measurements involve chemical reactions, and their read-values are change over a period of time. After a certain time, these sensors will have to be serviced.

• Sampling rate is also critical to accuracy.

• So a value is derived by a combination of voltage readings, curve and time.

Sensors

• Distance: Infrared

• ElectroMagnetic: Infrared, Light, UV, Spectrometry

• Chemical: Catalytic, Electrochemical, Pellistor

• Pressure/Vibration: Piezoelectric

• Temperature: Resistance

• Dielectricity: Oscillation (Capacitance/Inductance)

Sensors

• Temperature Sensor

• Conductivity Sensor

• Dissolved Oxygen Sensor

• pH Sensor

• Flow Sensor

• Oxidation Reduction Potential Sensor

Sensors

• Dissolved Ions Sensor

• Leakage Sensor

• Turbidity Sensor

• Atmospheric Pressure

• Leaf Wetness

• Humidity

Sensors

• Luminosity Sensor

• Soil Temperature

• Soil Humidity

• Dendrometer

• Solar Radiation

• UV

Sensors

• Wind Direction

• Magnetic Field Sensor

• Current Flow

• Liquid Flow

• Load Cell AMS

• Foil Displacement Sensor

Sensors

• Linear Displacement Sensor

• Dust Sensor

• Noise Sensor

• Ultrasonic Sensor

• Luminosity Sensor

• Geiger Counter

Sensors

• Most sensors are available ready to use in the market.

• Having detachable Sensors can lead to better serviceability than soldered.

• Require QA and Basic Calibration ahead of deployment.

• Post-Deployment Calibration can always be done on the app/cloud.

• Some sensors need a deploy-time measurement to track service times.

Processors

• Various sizes and costs

• ADCs, MicroControllers, CPUs, Cloud Computing

• Each does a designated function at a designated price point and power

• What usually increases cost/complexity is combining/communication

Evaluate Price(P1+P2+Combination) vs Price(P1)

Processors

• ADCs: Separate or Bundled

• Microcontrollers: Atmel, PIC

• CPUs/SoCs: ARM, MIPS, x86

• Cloud: Private and Public: Softlayer, Rackspace, AWS and a lot of options!

• The amount of data increases into each of these levels

• A good optimisation of the four are necessary for production

Communication

• UART / Serial: TTL / RS232 / GPIO

• USB

• Onewire

• I2C

• SPI

• Ethernet

Communication

• WiFi

• GSM (and *G)

• Bluetooth

• Zigbee

• Radio and other EM waves

• SD Cards, Disk Drives and anything offline

Responses

• Response to data makes a huge difference in the product

• Online responses include alerts, audible alarms, activating relays, motors and other knee jerk reactions

• Offline responses include tweeting, mobile notifications, emails, and essentially anything not as critical.

• Aggregated responses for presenting alerts over an accumulated amount of data. Today’s run: 13km

IoT Data

• Are you able to send data within a few ms? The human brain responds in 255ms. So if you and the human can communicate within that time, you’ve been able to make it appear real-time to them.

• What if you have a lot of data but you can’t send data as fast as you produce? You’ll have to aggregate it while preserving the semantics as much as possible.

• Idea is to optimise communication, not the accuracy of data.

IoT Data

IoT Data

• If the variables do not fluctuate within a time interval, they can be replaced with aggregates during the interval.

• But when variance is observed, preserve the original data.

• This yields into a thorough and pragmatic analytical capability for data

• The more data you need to transmit, the better your pipe should be.

IoT Data

• How quickly do you send the data?

• Data not sent is the fastest data!

• Use the entropy, Luke!

• The smaller is the entropy, the quicker you can send it. Or conversely, the smaller the entropy is, the less often you need to send it.

IoT Data

• How long do you store the data?

• Depending on the data, sometimes months or years of data could be stored.

• The variance needs to be calculated over larger intervals as well to retain the data semantics.

• Hence values over smaller intervals are really critical to understand the meaning of your data - not just aggregates.

What can you do with the Data?

• Alerts

• Respond to Crisis Situations Faster

• Reports

• Data Analytics

• Business Intelligence

What can you do with the Data?

• Analytics has changed a lot over the years:

• Visualization

• Patterns

• Prediction

• Optimization

• Course Correction/Action

A word on Sustainability

• How are IoT devices going to be powered? How does the power source harm the environment?

• How repairable and reusable are IoT components going to be?

Env Impact(Device+Existing) < Env Impact(Existing)

• Avoiding wastage is key to sustainable IoT implementation.

Questions?

Thank You!

• If you have any further questions

• If you want me to give a talk on something

• If you have suggestions for me

@kvisw