Meetup 4/2/2016 - Functionele en technische architectuur IoT
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The document outlines the 'City of Things' initiative led by Philip Leroux, which upgrades urban infrastructure through IoT technology to enhance data collection and analysis involving citizens and businesses. It describes a three-layer architecture that includes a network layer for connectivity, a data layer for real-time open data access, and a business layer that supports innovation through a living lab. Additionally, it discusses challenges in technology interoperability and emphasizes the need for dynamic management of IoT devices and data processing systems.
Meetup 4/2/2016 - Functionele en technische architectuur IoT
- 1. • City of Things City of Things Philip Leroux – - IBCN
- 2. Upgrading the city with Internet of Things Technological capacity to gather and analyse data Involving citizens and companies at large-scale New public-private collaboration models
- 3. Three layers Network-layer Deploying a city-wide network connecting multiple wireless technologies Data layer Providing an open data platform with a real-time view on the city Business layer Living lab and analytics infrastructure for evidence-based innovation
- 4. integrating smart city sensors 100 multi-technology gateways
- 19. Three layers Network-layer Deploying a city-wide network connecting multiple wireless technologies Data layer Providing an open data platform with a real-time view on the city Business layer Living lab and analytics infrastructure for evidence-based innovation
- 20. Gateway IoT Sensors & ActuatorsSensor Actuator LoRa BasestationLoRa Basestation LoRa Networkserver Network experimentation WiFi, BLE, ... LoRa WiFi, BLE, LoRa, ... jFEDNetwork test VM jFED Authority BOSS OPS City Of Things Services & Data Experiments Services & Experiments
- 21. Gateway IoT Sensors & ActuatorsSensor Actuator LoRa BasestationLoRa Basestation LoRa Networkserver Network experimentation WiFi, BLE, ... LoRa WiFi, BLE, LoRa, ... jFEDNetwork test VM jFED Authority BOSS OPS DYAMAND Sensor Data Collection & Service Discovery DYAMAND City Of Things Services & Data Experiments Sensor Management
- 22. Scattered landscape in terms of technologies • Different standards prevail in different application domains • Within each domain there are by default a number of competing technologies • Even within the same standard, implementation quirks hinder interoperability DYnamic, Adaptive MAnagement of Networks and DevicesDYAMAND
- 23. Scattered landscape in terms of technologies • Different standards prevail in different application domains • Within each domain there are by default a number of competing technologies • Even within the same standard, implementation quirks hinder interoperability DYnamic, Adaptive MAnagement of Networks and DevicesDYAMAND A unified interface to various COTS device technologies on the market.
- 24. There exist a number of general interoperability platforms with a gateway centric approach. DYnamic, Adaptive MAnagement of Networks and DevicesDYAMAND But, in general … • Manual/technical configuration steps still necessary • Serial port for communication with dongle, Sensor ID, Sensor type, etc. • Device types are not abstracted • Applications still need to be aware of technology internals
- 25. Advantages over other platforms: 1. Device discovery/eventing/control protocol is abstracted • Devices can be used across technologies • Application developer does not need expertise of different technologies 2. No user configuration • Everything is dynamically discovered whenever possible 3. Runtime modifiability • Help applications adapt to their surroundings without restarting/redeploying • Adapt to application’s APIs 4. No technical limitation with regards to supportable technologies DYnamic, Adaptive MAnagement of Networks and DevicesDYAMAND
- 26. DYnamic, Adaptive MAnagement of Networks and DevicesDYAMAND
- 27. (Gateway IoT Sensors & ActuatorsSensor Actuator LoRa BasestationLoRa Basestation LoRa Networkserver Network experimentation WiFi, BLE, ... LoRa WiFi, BLE, LoRa, ... jFEDNetwork test VM jFED Authority BOSS OPS DYAMAND Sensor Data Collection & Service Discovery DYAMAND Tengu Data Processing & Storage CoT Sensor Data City Of Things Services & Data Experiments Data Processing
- 28. BIG DATA Tengu 天狗 Enabling Dynamic Data ManagementTengu
- 29. Enabling Dynamic Data ManagementTengu Competitors
- 30. Enabling Dynamic Data ManagementTengu CUSTOMER LOCK-IN Competitors
- 31. Enabling Dynamic Data ManagementTengu CUSTOMER LOCK-IN FOCUS ON 1 TECHNOLOGY ONLY Competitors
- 32. Enabling Dynamic Data ManagementTengu CUSTOMER LOCK-IN FOCUS ON 1 TECHNOLOGY ONLY TOO COMPLEX/LABOUR INTENSIVE Competitors
- 33. Enabling Dynamic Data ManagementTengu Sojobo Tokin Hauchiwa … REST API Metadata ... UI CLI … Charm s
- 34. TenguEnabling Dynamic Data Management
- 35. TenguEnabling Dynamic Data Management Visual Configuration
- 36. Enabling Dynamic Data ManagementTengu iFEST Research projects using Tengu
- 37. Enabling Dynamic Data ManagementTengu Data processing/filtering: Data storage: Message system: ESB:
- 38. Enabling Dynamic Data ManagementTengu Data processing/filtering: Data storage: Message system: ESB: limeDS
- 39. Enabling Dynamic Data ManagementTengu http://gettengu.io
- 40. (Gateway IoT Sensors & ActuatorsSensor Actuator LoRa BasestationLoRa Basestation LoRa Networkserver Network experimentation WiFi, BLE, ... LoRa WiFi, BLE, LoRa, ... jFEDNetwork test VM jFED Authority BOSS OPS DYAMAND Sensor Data Collection & Service Discovery DYAMAND Tengu Data Processing & Storage CoT Sensor Data City Of Things Services & Data Experiments LimeDS Data Service Composition City Open Data GIS Information Panel DataNGSI Data Web Data ACPaaS Data External Data Sources Data Access
- 41. Polyglot Visual development Prototyping Robustness Lightweight Modular Environment for Data- oriented Services LimeDS
- 42. LimeDSLightweight Modular Environment for Data- oriented Services • Lower level • more rewriting boiler plate code • No visual paradigm • More complex • No robustness features • No programming API Competitors
- 43. •Web service platform •Integration framework •Rapid Prototyping Typical use cases LimeDSLightweight Modular Environment for Data- oriented Services
- 44. Example use case limeDS LimeDSLightweight Modular Environment for Data- oriented Services
- 45. LimeDSLightweight Modular Environment for Data- oriented Services 1st phase (Q1 2016) : sign in to sensor data streams 2nd phase(~Q2 2016): direct sensor/actuator steering Security: currently support for Interface APIs • LD DATA API (open transport, mobility & Geo Data) • Tourism API (location-based mobile services for tourists) • Open 311 IP (city feedback system, e.g. to report broken street signs) Fi-WARE NGSI 10 API • OMA NGSI compliant Restfull API to exchange context information
- 46. (Gateway IoT Sensors & ActuatorsSensor Actuator LoRa BasestationLoRa Basestation LoRa Networkserver Network experimentation WiFi, BLE, ... LoRa WiFi, BLE, LoRa, ... jFEDNetwork test VM jFED Authority BOSS OPS DYAMAND Sensor Data Collection & Service Discovery DYAMAND Tengu Data Processing & Storage CoT Sensor Data City Of Things Services & Data Experiments LimeDS Data Service Composition City Open Data GIS Information Panel DataNGSI Data Web Data ACPaaS Data External Data Sources Data EnrichmentAIOLOS DIANN E MASSIF SUMO DS HI2 … Data Analysis
- 48. CONTACT DETAILS Philip Leroux https://www.iminds.be/ Philip.Leroux@intec.UGent.be +32 9 331 49 40 CONTACT: WEBSITE: EMAIL: TELEPHON E: