The Future of Internet of Things is Artificial Intelligence | GDR Saudi’20

Transcript

1. The future of Internet of Things is Artificial Intelligence Ahmed Sobhy | @Sobhydo | www.xiot.io
4. © limestonedigital.co
6. Source : Cisco / https://www.ncta.com/broadband-by-the-numbers
7. © quora.com
8. At the most basic level, machines equipped with AI imitate the human thought process such as the ability to identify an apple and orange. Source ( qualcomm)
9. With machine learning, a system improves its pattern recognition capabilities by learning from its own mistakes. Source ( qualcomm)
10. Through deep learning, a machine can process large amounts of data, recognize complex patterns, and provide more detailed insights. Source ( qualcomm)
13. The AI Hierarchy of Needs
14. Internet Cloud Mobile/web app Internet IoT Typical Architecture Things
15. Things Protocol (over internet) Ingestion Analytics Storage Visualization Device Management Cloud API Message Broker Mobile Apps 3rd party systems Typical IoT Architecture
16. Microcontroller Radio Transceiver Network Interface Sensor Actuator Circuitry Energy Source A Thing
17. When we’re talking about full stack we mean end--to-end IoT Development. Developing for Things, Cloud & Mobile.
18. Image : sdfsystems.com
19. Developer Skill set Thing side Backend side Mobile side [Obj-C] Image : andriyadi.com
20. Thing’s side
21. ESP8266 Arduino nRF BLE Espruino Particle.io Photon, Electron Arduino 101 Raspberry Pi and many more ………. Dev Board Image : andriyadi.com
22. Dev Platform and many more… Teensy Image : andriyadi.com
23. Dev Tool/Ide Image : andriyadi.com
24. ESP-01 ESP-12 ESP-12E ESP-14 ESP-WROOM-02 ESP-07 ESP-13 ESP8266 Family Image : andriyadi.com
25. Did I mention it’s only$2
26. ESP8266 Dev Board Olimex NodeMCU ESPino Thing Dev ESPresso Digistump Oak Wemos D1 Mini Witty and more… Image : andriyadi.com
27. Cloud side
28. Cloud Platform Azure IoT Hub and a whole lot more… Image : andriyadi.com
29. IoT Core
30. IoT Core handles device management and bi-directional device communication as part of an over all GCP IoT Solution
31. Simple UI for monitoring and management Cloud Platform
32. Device Manager • Maintains registries of devices as named logical resources • Protects these entries with IAM permissions ◦ eg who can delete a device • Associates device credentials with these resources • Acts as the identity provider (IdP) for the MQTT broker • Provides storage and delivery API for device configurations • Maintains some operational state metadata for the device: ◦ enabled/disabled ◦ connectivity and error status What Services are in IoT-Core ? MQTT Broker • Provides a stateful socket connection to devices for bidirectional communication • Brokers device->cloud telemetry data onto Cloud PubSub for use in downstream GCP products or customer applications • Delivers configuration updates via a Device Manager API • Is exposed through a global DNS endpoint over multiple ports
33. What is MQTT MQTT is a machine-to-machine (M2M)/"Internet of Things" connectivity protocol. It was designed as an extremely lightweight publish/subscribe messaging transport. • Originally developed at IBM in 1999 and designed for constrained devices • Is now a ratified standard • Is a binary protocol making efficient use of over-the-wire bandwidth • Is simple to implement and so has many small memory footprint libraries available • Has become a common and de-facto standard used in many IoT projects
34. Ingest Pipelines Storage Analytics Application & Presentation Standard Devices HTTPS Constrained Devices Non-TCP e.g. BLE Gateway Architecture: General > Real Time Stream Processing - Internet of Things App Engine Container Engine Cloud Storage Cloud Pub/Sub Cloud Dataflow Monitoring Logging Cloud Dataflow Cloud Datastore Cloud Bigtable BigQuery Cloud Dataproc Cloud Datalab Compute Engine Cloud IoT Core
35. Buildings Transportation Healthcare Retail Manufacturing & Industrial Cities Home
38. Retail warehouses
41. Transportation
43. Derive Systems helps customers maximize vehicle performance by collecting real-time data and using that data to enable customers to optimize the driving experience, including fuel economy and driver safety.
44. Manufacturing & Industrial
46. Train manufacturer Talgo revolutionizes train maintenance with Google Cloud Platform, by streaming sensor data in real time and applying machine learning to stop problems, without stopping service.
47. Google Cloud Results • Streams data in real time from 2,000 on-board sensors for immediate analysis, anywhere in the world • Collects 2,000% more data per train, per day than using a previous system • Uses machine learning for potential savings of over 200 hours a year per train in maintenance inspection time
48. Home
49. Thank you! @Sobhydo www.XIOT.io