In today’s world, homes are becoming ever smarter. Majority of you already equipped your home with smart device (excluding smartphones and computers even if they can account to that list as well) without knowing. Smart fridge, washing machine, TV, heating/cooling, climate control, lights, blinds, etc. are part of our day to day life. Some of them are already connected to network and communicate with manufacturer to predict maintenance periods, outages and similar odd behavior. By tapping into that communication and implementing/empowering central collection and analytic solution we can start building models which can help us save money, health, relief stress levels and even save/protect our lives and property by tracking and predicting potential problematic situations (fire, smoke, CO and other gas related fumes, intruders) even if we do not have appropriate sensors in place. Correlating different sensor measurements and establishing appropriate and proven causality, we can start making our home even smarter and cost effective. Should we dynamically close shutters to preserve heat/cold within our house, should we change temperature on our smart fridge so we do not waste energy based on how much “stuff” (and which “stuff”) do we have inside fridge are some of questions which can be answered by this lecture where we will talk about implementation of Smart+ Home analytics based on user behavior, patterns but also extended into protection area by preventive alerting for fires/gas leaks, potential wiring issues (problems hidden in house walls), etc.

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8. 1984 – BIG BROTHER
IS WATCHING YOU
…AND HELPING WITH SAVINGS

9. Agenda
• Am I relevant?
• IoT
• What is an Intelligent
Building?
• Reality
• Issues (Man in a middle)
• DIY approach
• Use-cases
• Q&A

10. Am I relevant ?
197x
DoB
1985
1991
1987 1997
1998
1999
2005
2015
2018
1984
1985 1990
1996*
1997
1998 2011
1987 1991
2015

11. Am I relevant ?
198
4

12. Why is home automation such a big
industry?
• Convenience
• Accessibility from anywhere with internet connection
• Laziness factor
• Nikola Tesla – first patented remote control (1898)
• Control
• Manage anything that is hooked up – alarms, etc.
• Efficient use of systems – radiant heat example
• Cool
• Pride factor

13. Agenda
• Am I relevant?
• IoT
• What is an Intelligent
Building?
• Reality
• Issues (Man in a middle)
• DIY approach
• Use-cases
• Q&A

14. What is the Internet of Things
(IoT)
• Internet connected objects (things) working together to solve a
business problem
• Has been around for quite a while, but only recently has become
affordable for personal use

15. IoT Application Segments

16. Agenda
• Am I relevant?
• IoT
• What is an Intelligent
Building?
• Reality
• Issues (Man in a middle)
• DIY approach
• Use-cases
• Q&A

17. What is Smart Home?
A home equipped with lighting, heating,
electronic devices that can be controlled
remotely by pc or phone.

18. What is an Intelligent
Building? • Building Automation Equipment
• Building Automation Systems
Integration
• Building Analytics
• Building Remote Monitoring Services
• Consumer Health Monitoring &
Telehealth
• Digital Signage
• Industrial Automation
• Fire Detection and Suppression
Equipment
• Office Lighting Applications Report
• Smart Lighting and Connected Lighting
• Metering
• IoT Connectivity & Devices
• IoT Software and Services
• Physical Security Equipment
• Photovoltaic and Renewable Energy
• Security Services and Systems
Integration
• Smart Building Systems
• Smart Grid

19. Intelligent Building - Why?
• Building Automation System deliver benefits
beyond energy efficiency.
• Cyber security is a key differentiator between
intelligent building solutions.
• Smart cities drive the development of
intelligent buildings.
• Intelligent buildings optimize the occupant
experience.
• Climate change policy mandate efficiency in
buildings.

20. Green energy

21. Agenda
• Am I relevant?
• IoT
• What is an Intelligent
Building?
• Reality
• Issues (Man in a middle)
• DIY approach
• Use-cases
• Q&A

22. Internet of Things Evolution
Internet of Everything (IoE): represents the open access to
data from one or more monitoring and control systems by third-party
applications to provide unique, additional value to stakeholders
Where we are today
(security is key
challenge)
Ideal goal of
connected society

23. Learning Thermostat

24. Automated lighting system

25. Smart Appliences

26. Smart alarming

27. Energy usage

28. Water consumption

29. Confusion over What Smart Home
Really Is
• A Nest thermostat is an obvious example of a
self-learning connected home solution
• …but, it is just an autonomous Wi-Fi-enabled
gadget which uses temperature, motion, humidity
and light sensor data to create custom
temperature schedules, thus saving users energy
and keeping them comfortable.
• A truly intelligent Smart Home is a multi-layer
system which requires little to no management on
a user’s part and is capable of making decisions
based on historical and real-time data

30. Smart home communication environment
Smoke
detecto
r
Connected
light
bulbs
Connected
camera
Connected TV
Cloud
Smart
device
Gateway

31. Pros
• Money savings
• (energy savings, water
consumption savings)
• Convenience
• Customization

32. Cons
• Hackers
• Learning
curve

33. Agenda
• Am I relevant?
• IoT
• What is an Intelligent
Building?
• Reality
• Issues (Man in a middle)
• DIY approach
• Use-cases
• Q&A

34. DIY requires technical skills

35. Choose approach – Wire /
WireLESS

36. Smart objects – our goal
Make things that weren’t meant to talk to each other interact smartly
• Phone → Location detection, presence detection →
Thermostat
• Doorbell activation → CCTV takes picture → Email +
SMS + Tweet
• Fire Alarm → Email + SMS
• Security System → CCTV → Email + SMS
• Climate control → presence @ home & weather
forecast
• Hot water tank → our presence, weather forecast
• Dog → CCTV + Email
• Weather notifications → email

37. (Deep) Learning for Home
Automation
• Smart homes are artificially intelligent systems
that need to adapt themselves based on user
actions and surroundings.
• These systems need to carefully analyze the user
needs and the conditions of the surroundings in
order to predict future actions and also
minimizes user interaction.
• A single day in a person’s life consists of a
set of actions.
• These actions, over a period of time can be
learned by an intelligent system and prove
useful to predict future actions

38. Become man-in-a-middle

39. Data Collection … . .. … ..
….
Input Output
• Further filtering
unnecessary
events via A:B
testing
• Collect all
sensor events
• Verify against
sliding window

40. Continuously Learning (AI) Smart home
Generate sensoring
data
Collect all
sensoring data
Process to make
better decisions
• Automation
• Online Learning
01
02
03

41. DIKW model
• Information is inferred from data, in the
process of answering interrogative questions
(e.g., "who", "what", "where", "how many",
"when"), thereby making the data useful for
"decisions and/or action".
• Knowledge as
"synthesis of
multiple sources of
information over
time"

42. DIKW in a nicer picture 

43. Interaction is a key
• By focusing on single
interaction channel
we are introducing
SPOF’s in our system
• Voice
• Touch
• Gesture

44. Agenda
• Am I relevant?
• IoT
• What is an Intelligent
Building?
• Reality
• Issues (Man in a middle)
• DIY approach
• Use-cases
• Q&A

45. Basic use-cases
• Control lighting throughout your home
• Control your TV and tuner
• Control your Audio device
• Set your home temperature
• Control sunscreens and blinds
• Secure your home - by combining door/window
sensors with motion sensors, Smart Home knows
exactly what is going on, and can warn you if
something is out of place
• Daily tasks, Wellness, Connectivity, etc.

46. Let’s mix them together
• Wake up comfortably
• Pretend you're home - simulate your presence to
pretend you are home based on your „normal”
activity
• Energy saving by utilizing your behavior and
comfort requirements
• Control in-house doors and AC elements to keep
need for heating/cooling to minimum while
preserving comfort level
• Auto-lock/un-lock based on connected devices

47. Correlation use-cases
• Smart Home equipment predictive maintenance
• Fire & Safety - Fire propagation is faster, and
time to flash over, escape times and collapse
times are all shorter
• Energy saving by utilizing your behavior and
comfort requirements
• Audio vs other sensor correlation for intrusion
detection
• Eliminate false-positives through multi-
verification process:
• a large number of smoke alarms were going off because
regional parrot’s squawk matched a manufacturer’s
alarm sound closely enough that it was fooling the
sensors

48. Health …
• Telehealth - connecting a citizen’s health
monitoring to the smart home and start with
real-time checking of health and wellness
signals
• Automated Activity and Fall Detection Systems
• Reminding Systems
• Mold detection and prevention

49. Scary use-case
• Detect depression in conversations (speech,
social media, etc.):
• From the way you move and sleep, to how you interact
with people around you, depression changes just
about everything.
• It is even noticeable in the way you speak and
express yourself in writing
• Your mental health is reflected in the images you
choose to post on social media
• Intuitively, we tend to link darker, grayer colors
with negative moods and brighter, lighter colors
with positive ones
• React & prevent – play soothing music, alert …

52. www.atmc.ai
info@atmc.ai