Internet of Things introduction
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This document discusses the Internet of Things (IoT) and provides an overview of key concepts: 1) The "perfect storm" of falling sensor costs, ubiquitous connectivity, cloud computing, APIs, big data analytics, and artificial intelligence has enabled the rise of IoT. 2) IoT connects physical devices via the internet and collects data that can be analyzed for insights. An IP-based reference model is commonly used. 3) Intelligence in IoT systems can be distributed between devices, gateways, fog computing, and the cloud depending on factors like latency requirements, failure tolerance, costs, and privacy/security needs.
Internet of Things introduction
- 1. Veselin Pizurica CTO, veselin@waylay.io
- 2. Internet of Things Introduction Guest lecture, UGent, 17/11/2015
- 3. Why so much interest in IoT?
- 4. IoT - Tectonic Shift Impact of science and engineering - invisible force that is changing our daily life
- 6. What is Internet of Things?
- 7. Why now? - Perfect storm β Cost of adding new connected sensors/actuators has come down dramatically β Connectivity β Cloud β API economy β Big Data/Analytics β AI β Robotics
- 8. Devices are becoming widely available Off-the-shelf gadgets Programmable devices
- 11. Cloud β Storage β Computing power β Scalability/elasticity β Distributed applications
- 12. Cloud infrastructure - hardware view
- 13. Cloud infrastructure - software view
- 14. API economy β APIs have become new patents β Who holds the data, holds the knowledge β Companies donβt share their know-how, but they are willing to share their know-what (via Application Programming Interface API) β API economy will be the major driver of the profit for many companies
- 15. Weather API - monetization
- 16. IoT -> (Big) Data -> Analytics
- 18. What connects these two pictures?
- 20. So letβs talk about AI! Y = f (X) Y = f (X)
- 22. Intelligence - where? βSwarmβ intelligence Logic in the gateway βFogβ computing Logic in the cloud Logic in the device
- 23. Swarm Intelligence - in sensor networks? β Limited storage, power and processing power β Sensors and actuators local
- 24. Logic in the gateway - (mostly) home automation
- 25. Fog computing β Anomaly detection β Compress sensing (not for computing, but bandwidth optimization, as data leaves the edge) β Fast reaction time β No privacy issues if data doesnβt leave the edge β Doesnβt work for LoRA and Sigfox, as data deduplication happens in the cloud β Mostly in factory settings - transition from SCADA (legacy) systems to more internet oriented solutions
- 26. Why NOT intelligence in the cloud? β Latency requirements β Failure (in)tolerance (lack of redundancy) β adding more blocks system even less stable β Cost of pushing data in the cloud (storage, bandwidth) β SW cost of integration β Lack of standardization β Security concerns: Authentication/Authorization β Privacy concerns
- 27. Why intelligence in the cloud? β Device-agnostic and decouples logic from the presentation layer β Combination of the sensor data with API βeconomyβ β Integrating multiple IoT vertical solutions β Cloud-capacity scales horizontally, while distributed HW often needs to be swapped when HW resources are no longer sufficient β Cloud intelligence also allows easy generation of analytics regarding the usage of the logic itself. Which rules fired and why? How often? β An architectural model arises where logic is built together with a REST API
- 28. Our vision
- 29. Waylay - smart agent concept for IoT
- 30. Waylay platform