CuTech Talks- Art of Building IoT Products event held on 9th January 2016 at Cumulations Technologies. This PPT covers the topic "On Problems, Products and IoT" presented by Tej. It addressed the importance of implementing right technology at right time.

1. On Problems, Products and
IoT
Dr. Tej Pochiraju, 9th January 2016
micrograce

2. Brief Bio
● Wireless hardware + applications since 2004
● >150 SMEs + some LEs (Cadbury, Texon, Rockwool)
● ~40 product developments
○ Some successes, many failures
○ Livestock RFID (Scotland/France)
○ Wave energy sensor network (currently off coast of NY)
○ Passive RFID Pressure Sensor (England)
○ Wireless Smart Grid Sensors (Italy)
○ Wireless Tyre Pressure Sensor (Northern Ireland)
○ Trailer Monitoring (sold to Ministry of Defence, UK)
○ Very, very keen to work on environmental challenges in India

3. Ignore your idea
Definitely ignore your technology
Focus on the problem

4. Problem Driven Approach to Product Development
● What is the problem?
● Who is affected by this problem?
● Why is this problem worth solving? aka Return on
Investment
● When is the problem worth solving?
● When will the solution be commoditised? Can you wait?
● Who is willing to pay for the solution?
● Is it a product?

5. Remote Monitoring of Wave Energy Generators

6. Remote Monitoring of Wave Energy Generators
● NEED: Generator can be damaged if not shut down during strong waves
resulting in loss of ~$1M to equipment owner
● Idea: Remotely monitor waves and automatically shut generator down
during ‘events’
● Technology: Wave sensors in wireless mesh network for remote
monitoring from up to 12 km
● ROI: Sensor Deployment costs about $300,000 and lasts 10+ years [Think
Insurance]

7. Remote Monitoring of Electric Grid: Similar Story

8. Livestock RFID: Before

9. Livestock RFID: After

10. Microwave Wood Drying!

11. Touchscreen Sphygmomanometer in 2007!

12. What is IoT?
● Really old concept
● Overused phrase
● Lots of data but NOT Big Data
○ Most processes being measured are well understood physically or need relatively simple
statistical models
○ Big Data Analytics are great at understanding stochastic/random processes
● Quite useful, in the right context

13. What is IoT good for?
● Consumer goods - extremely difficult to predict (+ no personal experience)
● Industrial:
○ Where cost of failure is high
■ Asset tracking, predictive maintenance
○ Where process is not completely understood or influenced by uncontrolled parameters
■ Agriculture
■ Chocolate/Alcohol making (haven’t changed for 100+ years!)
■ But beware questions on ROI and who pays!
○ Where there is an advantage to aggregating data from multiple installations
■ Aircrafts (practising data sharing for 60+ years)
■ Traffic monitoring

14. What I have learnt
● The best technology is one that solves the problem effectively and will solve it
for the lifetime of deployment
● Lifetime determined by first component to fail expensively:
○ Sensor
○ Data logger
○ Communications network (what if 2G disappears?)
● The best way to develop hardware is by eliminating as much hardware as
possible
● If you can implement something in software (and cloud), DO IT!
○ Total Harmonic Distortion calculation on cloud vs in hardware

15. Common Startup Failures
● Not understanding/picking the right problem
○ Secondary research is not good enough. Get out there and research the problem
● Solving everything
○ Solve one problem really well
■ Kickass cloud db+viz+analytics >> ‘Full-stack’ data logger+cloud :-(
● Lack of Focus
○ Pick a problem that is worth solving, solve it, sell it
○ Do nothing else until 1st sale then whore yourself to investors to scale
○ Set a time limit on when to stop (12-18 months)
● Reinventing the wheel
○ Use open source, use proprietary, use what exists if it meets your needs
○ Replace when worth replacing (almost never will be)

16. Ignore your idea
Definitely ignore your technology
Focus on the problem