Quby is a leading company offering data driven home services technology across European markets, known for creating the in-home display and smart thermostat Toon. We enable our partners to take on a leading role in the home services domain, by offering data driven home services. Our services enable users to control and monitor their homes using both an in-home display and app.
As a data driven company, we use AI and machine learning, backed by Apache Spark, to generate actionable insights for all our end users. Via our IoT devices we have access to Europe’s largest energy dataset, petabytes in scale and growing exponentially. This unique dataset enables us to introduce new data driven services, with a particular focus on homes with smart meter installations.
In this talk, Ellissa will describe how machine learning is implemented on the Quby platform and will show multiple use cases backed by high-resolution IoT data. We’ll take a look at super resolution techniques for time series data, where using detailed high-resolution energy data is used to show personalized energy insights for users where only limited low-resolution energy data is available. We’ll show how ML algorithms offer the possibility for non-intrusive monitoring of elderly patients.
Ellissa will share the experiences from the Data Science and Data Engineering teams at Quby with bringing these data science algorithms from R&D to production using Databricks and the lessons learned in offering these services to hundreds of thousands of users on a daily basis.
2. Ellissa Verseput, Quby
Making Homes Efficient and Comfortable
Using AI and IoT Data
#UnifiedDataAnalytics #SparkAISummit
3. Outline
• Why, What, How Quby
• 2 Example Use Cases
– Bill Breakdown (Efficient)
– Thermostat Program Advice (Comfortable)
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4. 4
We believe the future can be better.
Easier, more comfortable, and more sustainable.
We help businesses and their customers to make this change
without compromising on the important things in life.
6. Z-Wave
Meter adaptors
Boiler
adapters
Gas sensor
Philips Hue
Z-Wave
Central heating
system
Solar panels and power
storage
Smart plugs & smoke detectors
Electricity sensor
Gas
Water
Water sensor
Electricity
Athom Homey Amazon Alexa Google HomeDrebbleOlisto
8. Outline
ü Why, What, How Quby
• 2 Example Use Cases
– Bill Breakdown (Efficient)
– Thermostat Program Advice (Comfortable)
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9. Energy insights gas & electricity
(high frequency)
Waste checker (~7 use cases)
Water insights & saving tips
Solar generation integration
Smart thermostat functionality
Smart home integration
Air quality measurement & insights
Monitoring the home
Smart security solution
Assisted living
Energy insights with low frequency
Dedicated app development for utilities with superior user experience & personal relevance
Home services
Efficient home Comfortable home Trusted home
Current Quby Portfolio
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10. Use Case #1
Bill Breakdown
10
Show how different appliances and
activities in the home contribute to the
energy bills
17. 17
Utilizing our large database of high-resolution data, we apply advanced techniques to offer a more
personalized, more dynamic and more accurate bill breakdown service.
Low resolution data
Bill breakdownEnhancement
Most similar
users with high
resolution data
Appliance
detections
High resolution data
User
Similar users
20. Outline
ü Why, What, How Quby
Ø 2 Example Use Cases
• Bill Breakdown (Efficient)
• Thermostat Program Advice (Comfortable)
20
21. Outline
ü Why, What, How Quby
Ø 2 Example Use Cases
🤯 Bill Breakdown (Efficient)
• Thermostat Program Advice (Comfortable)
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22. Use Case #2
Thermostat Program Advice
22
Suggest updates to the Toon users’
thermostat program, such that the program
better reflects their behavioural patterns
23. Thermostat Program Advice Key Technology
23
Cooling down and
warming up rate
Humidity sensor
Somebody home?
Presence Detection
24. Non-intrusive Monitoring
24
Proof of Life – Toon can detect when a person is present
Safety – Toon can indicate an active/inactive (elderly) resident
Heating/Lighting – Toon can detect people are active to optimize heating
25. Training a Machine Learning Model
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Hour Mon Tues Wed
08:00 Home Away Home
09:00 Away Away Home
10:00 Away Away Home
Hour Mon Tues Wed
08:00 Home Home Home
09:00 Home Away Away
10:00 Away Away Away
Cooling down and
warming up rate
Humidity sensor
26. We want to track model improvements and reproduce models
Challenge
32. Thermostat Program Advice Architecture
32
Toon data
collector
Presence
Labels
API
Survey
Program Advice
33. What’s next?
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8:00
Good to see that mom has
woken up. I was worried
since she complained she
had breathing issues.
16:00
Guess the first thing he
turned on was the game
console. At least, I know
he is back home from
school
12:00
I left for work early
morning, there
shouldn’t be any
recent activity.
Perhaps I should have
the neighbors check
34. Assisted Living
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8:00
Good to see that mom has
woken up. I was worried
since she complained she
had breathing issues.
16:00
Guess the first thing he
turned on was the game
console. At least, I know
he is back home from
school
12:00
I left for work early
morning, there
shouldn’t be any
recent activity.
Perhaps I should have
the neighbors check
We can monitor the home to help
people care for their loved ones and
keep their homes safe & warm.
35. Summary
ü Why, What, How Quby
ü 2 Example Use Cases
ü Bill Breakdown (Efficient)
ü Thermostat Program Advice (Comfortable)
35