Presentation by Adrian Arroyo Perez Research & Innovation Engineer, Atos FIWARE Global Summit 23-24 October 2019 - Berlin, Germany

1. Scale Up for a Real Smart Future
Berlin, Germany
23-24 October, 2019
Advanced ML/AI Techniques with FIWARE
and Connected IoT Devices
Adrián Arroyo
IoE Lab. Research & Innovation, Atos Spain, Spain
adrian.arroyo@atos.net
@arroyadr

2. How to address the challenge of transforming data
into intelligence?
§ IoT ↔ Big Data
§ AI technologies and Machine Learning techniques are
suitable for IoT scenarios
• Detecting patterns and behaviours from gathered data
§ Analysing these patterns, it is possible to transform data
into intelligence
• Generating lots of smart services

3. How to address the challenge of transforming data
into intelligence?
§ Appearance of new IoT hardware with better performance
capabilities on AI in the Edge
§ Power demanding is an issue for IoT
• Hardware performance
• Connectivity issues
• Energy efficiency
§ Move data and intelligence to the cloud is not a solution for
IoT
• Accessibility to the cloud is not guaranteed every time
(24h/7d)
• Delays in responses may appear

4. Our solution: EASIER
A Data Intelligence platform with a Hybrid
Architecture Cloud-Edge

5. EASIER: Architecture
§ Data manager: brings IoT data to the
platform (NGSIv2 supported)
§ Automatic Cloud/Edge data
synchronization
§ Cloud platform to implement your data-
science tasks: create, train and test
models with the Micro Trainers
§ Use the models in the edge (or cloud) with
automatic model synchronization with
the Micro inferencers
§ Models optimized for specific hardware
platforms (TPU, Raspberry Pi, etc.).

6. EASIER: Artificial Intelligence as a Service
Raspberry Pi
Data
Manager
DataData
Google Coral
dev board

7. EASIER: Artificial Intelligence as a Service
Raspberry Pi
Google Coral
dev board
Data

8. EASIER: Artificial Intelligence as a Service
Trainer
Raspberry Pi
Google Coral
dev board
Data

9. EASIER: Artificial Intelligence as a Service
Inferencer
Raspberry Pi
Google Coral
dev board

10. EASIER: Artificial Intelligence as a Service
Trainer
Trainer
Inferencer
Inferencer
Trainer Inferencer
Raspberry Pi
Google Coral
dev board

11. Data Storage
& Processing
Data
Transform
Data
Manager
Data
Transport
Data
Intelligence
Data
Management
Smart
Services
Data Sources
Deployment
EASIER: Architecture technologies
Parking prediction Traffic estimation Vehicle insurance Worker safety Failure prediction

12. Use Case:
§ https://synchronicity-iot.eu/
§ Data ingestion (NGSIv2): Orion, STH
Comet, …
§ Data sources: Parking, Traffic, Noise
§ Smart services
• Prediction of future data
Data
Manager
• Free/occupied ratio vs time of day

13. Smart Service Demo: Parking area availability
prediction

14. Contact for related proposals
Adrián Arroyo Pérez <adrian.arroyo@atos.net>
Internet of Everything Lab
Atos Research and Innovation

15. Thank you!
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