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1
Introduction
2
Motivation for data simulation
3
Data simulation definition
4
Data simulation techniques
5
Particle filtering
6
Interactive notebook
7
Model agnostic
8
Data simulation setup
9
Data simulation plots
10
Tech stack
11
Parallelization
12
Parallelization overview
13
Parallelization performance
14
Future work
15
Thank you
16
Takehome
17
Tsunami
18
Comparison
19
Error
20
Parameter evolution
21
Questions
22
Digital twin
23
Digital twins
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Python implementation
25
Contacts
26
QA
27
AI trained models
28
Cloudbased measurements
29
Realtime questions
30
Realtime requirements
31
Realtime observations
32
Realtime drift
33
Email ramturingacuk
34
Workshop
35
Sensors
36
Sensors moving
37
Workshops
38
Thanks
39
Deployments
40
Scaling plots
41
Finding a workflow
42
Integration with Julia
43
Outro
Description:
Explore real-time data assimilation techniques for digital twins in this 57-minute workshop from the AI UK 2022 Research in Action series. Dive into the motivation behind data simulation, its definition, and various techniques, with a focus on particle filtering. Engage with an interactive notebook to understand model-agnostic approaches, data simulation setup, and visualization. Learn about the tech stack and parallelization strategies to enhance performance. Discover applications in tsunami modeling, error analysis, and parameter evolution. Gain insights into AI-trained models, cloud-based measurements, and real-time implementation challenges. Discuss sensor deployment, scaling issues, and workflow integration. Connect with experts and explore potential collaborations in this cutting-edge field of digital twin technology.

AIUK 2022 Workshop - RADDISH: Real-Time Data Assimilation for Digital Twins

Alan Turing Institute
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