SOLUTION
Real-time offline spatial big data collection solution based on AIoT convergence technology
1
Comply with privacy laws2
Quasi-personapzation3
NEXT (Auto-ML-Ops related...)Offline Spatial Big Data, What can I collect and analyse?
Comply with privacy laws
Unsettling issues
Risk of privacy breaches
Total personal data leaked in the last three years
65,052,232cases*
*According to the national audit data received from the Personal Information Protection Commission (Personal Information Protection Commission) by Kim Jong-min of the Democratic Party of Korea (2023)Top two privacy concerns(2)*
Hacked from the outside (81%)
Breaches due to administrative mistakes (77.9%)
Intentional breaches by insiders (30.9)
Breach by an outsourcer (7.3)
*Ministry of Science and ICT, Korea Information Protection Industry Association Information Protection Survey (2019)
Hacks, operational mistakes, deliberate leaks, and more... Should you take the risk?
Don't store footage that could be compromised.
Hacks, operational mistakes, deliberate leaks, and more... Should you take the risk?
Filming stage anonymisation and AI analytics
SUMMARY
Store analytics dataTable occupancy
88%
Average dwell time
63mins
Order menu percentages
54%
(Iced Americano)
Percentage of males
43%
Percentage of females
57%
*The photo above is an example image.
Quasi-personalization
No matter how many days pass, no matter how many times it appears in different spaces, the
What if you recognise the same person?
Business cards that may violate privacy laws when passed on to third parties
Fingerprint/DNA to determine identity
DNA, why is it used in court?
DNA from suspect collected in Case A
compare
DNA from suspect collected in Case B
If the same DNA is detected in different cases, you know it's the same person, even if you don't know who it is.
What if DNA or fingerprints match?
Different incidents with multiple culprits
A serial killer commits a series of murders
Personalized marketing without personal information
A paradigm shift
Maze's DNA considers behavioural traits, not identity.
visit
entry time
order menu
companion
behavior pattern
stay
seat
Store A
13:28
Einspenner
ID878
Chat
35mins
Window
visit
entry time
order menu
companion
behavior pattern
stay
seat
Store B
15:31
Iced Latte
ID9121
Study
80mins
Hallway
visit
entry time
order menu
companion
behavior pattern
stay
seat
Store A
16:22
Iced Latte
ID878
Chat
50mins
Window
visit
entry time
order menu
companion
behavior pattern
stay
seat
Store C
12:55
Latte(HOT)
ID878
Chat
20mins
Window
When the same person appears on a different date, in a different space
The only technology in Korea to verify identity
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