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Sensor Web Introduction Geospatial Sensor Web Conference – Tutorials Sensor Web Introduction Simon Jirka ([email protected]) - 52°North GmbH 28th August 2017 – Münster (Germany) Motivation • More and more sensors are deployed • Human observations • Lots of different phenomena – Weather – Pollution – Biodiversity – Hydrological Data – Traffic – ... 2 3 Motivation • Different structures and elements of observations • Sensor interfaces are very heterogeneous • Need for harmonisation interoperability • Provide a layer on top of observation databases and low level sensor network technology integration into web applications 4 Motivation • Traditional services allow to – request maps (images) • Web Mapping Service – request (binary) raster data • Web Coverage Service – request vector data • Web Feature Service • Lack of a generic framework for integration observation data into spatial data infrastructures 5 Motivation 6 Motivation 7 SWE Building Blocks 8 Observations & Measurements • Conceptual model for – Representing observations – Exchanging observations • Implementation as application schema – XML schemata extending the Geography Markup Language (GML) • Primary use: Encode SOS GetObservation response documents • O&M 2.0 is now available (OGC and ISO standard) 9 O&M Basic Observation Model • Observation – Act of observing a phenomenon – Producing an estimate for a property of a feature of interest – Specialized event with result • Inherits temporal attributes – Observation properties support result interpretation (e.g. quality) 10 O&M Observation Model Source: OGC 11 O&M Basic Observation Model • Procedure – Determines the value of a phenomenon – A procedure can be an instrument, a sensor, a human observer, a computation, a simulation … – O&M contains only a short description of the process – More detailed information is provided via SensorML / TML 12 O&M Basic Observation Model • FeatureOfInterest – A Feature represents the observed real-world object – The feature of interest is the target of the observation – Examples: River, road, person, scene, specimen, … 13 O&M Basic Observation Model • ObservedProperty – Identifies or describes the observed phenomenon – Examples: Air temperature, water level, wind speed, air pollution concentration – Description of the observed properties are often accessible through dictionaries 14 O&M Observation Example (XML) 15 O&M Observation Example (JSON) 16 SensorML • General sensor information discovery • Facilitate processing and analysis of sensor measurements • Geolocation of observed values • Description of the process by which an observation was obtained • Current version: SensorML 2.0 17 SensorML Overview 18 Process • Base for all processes in SensorML physical and non-physical processes • Elements – Inputs & Outputs – Parameter – Processing method – Reference systems – Any further metadata 19 Aggregate process • Process chains are modelled as aggregate processes • An aggregate process describes – Processes of the chain – Data sources – Connections between processes 20 (Physical) System • Extension of process chain • Defines relative positions of all components (processes and data sources) within the system • Spatial and temporal position • Describes interfaces of the system to the external world 21 Process Metadata • Allows discovery and interpretation of results • Possible content – Common metadata (ID, classification, textual Description, Contact information) – Constraints (e.g. temporal validity of document) – Capabilities and characteristics of the sensor – References – History 22 SensorML – Example (i) 23 SensorML – Example (ii) 24 SWE - Interfaces 25 SMS Email Fax Phone Call Response Request (O&M, SensorML) Subscribe Request Response Alerts SOS Event Notification SPS Processing Service Observations Observations Commands 26 Sensor Observation Service (SOS) • Pull-based access to observations • Mediator between: – client data archive / simulation / real- time sensor system • Hides the heterogeneous structure of proprietary sensor data formats and protocols • Data formats: O&M and SensorML • Versions: 1.0 and 2.0 27 Sensor Observation Service (SOS) Response Request (O&M, SensorML) SOS Observations NetCDF NetCDF NetCDF 28 SOS – Requirements Classes Core: -GetCapabilities -DescribeSensor -GetObservation Transactional ResultHandling -InsertSensor -InsertResultTemplate -DeleteSensor -InsertResult -InsertObservation Enhanced -GetResultTemplate -GetFeatureOfInterest -GetResult -GetObservationById 29 SWE Eventing • Sensor Alert Service • Sensor Event Service • Web Notification Service • Pub-Sub Extension recently adopted as OGC standard 30 OGC Publish/Subscribe Standard 31 Sensor Planning Service (SPS) • Standardized interface for tasking sensors and sensor systems • Task management – Defining tasks – Checking tasks – Updating/modifying tasks – Cancelling tasks • Does not archive the data itself points to access points for the data 32 Introduction • Usage: – Parameterization of: • Sensors, Simulations – Planning and executing of: • UAVs, Robots, Satellites, … • Asynchronous communication with clients that submit tasks via WNS (e.g. notification if a task is completed) 33 Operations • Mandatory in SPS 1.0 and 2.0 – GetCapabilities: Request a self description of a SPS instance – DescribeTasking: Request which information is needed for submitting a task – Submit: Submitting tasks – DescribeResultAccess: Request information where the data resulting of a task can be retrieved 34 SPS workflow 35 Summary • Data Models/Encodings: – Sensor Descriptions: SensorML – Observation Data: Observations & Measurements • Web Services: – Pull-based access: Sensor Observation Service – Eventing – Tasking sensors: Sensor Planning Service 36 Further Information: https://52north.github.io/sensor-web-tutorial/ Questions? Simon Jirka ([email protected]) 37 Geospatial Sensor Web Conference – Tutorials Practical Exercise: Helgoland - A Sensor Web Viewer Simon Jirka ([email protected]) - 52°North GmbH 28th August 2017 – Münster (Germany) Helgoland • Based on JavaScript • Web application to – Discovery data offered by SOS servers – Explore sensor networks – Visualise observation data • Diagrams • Tables • Tracks (in development) • Uses 52°North Sensor Web REST-API to connect to SOS servers 39 Helgoland 40 Helgoland 41 Helgoland • Open source: https://github.com/52North/helgoland • Test it: http://sensorweb.demo.52north.org/client/ – Select a data provider – Use the map view to discover a sensor/station – Visualise the data as a diagram – Open the table view • Advanced version: http://sensorweb.demo.52north.org/client/ 42 Questions? Simon Jirka ([email protected]) 43 Geospatial Sensor Web Conference – Tutorials Deployment Strategies for the 52°North SOS Simon Jirka ([email protected]) - 52°North GmbH 28th August 2017 – Münster (Germany) Agenda 1. How to integrate the 52°North SOS into your existing IT infrastructure? 45 Existing DB via new SOS Data Access Layer SOS Client GetObservation O&M SOS Server Database (e.g. PostgreSQL, MySQL, Oracle) 46 Existing DB via Hibernate SOS Client GetObservation O&M SOS Server Hibernate Database (e.g. PostgreSQL, MySQL, Oracle) 47 Existing DB via Views SOS Client GetObservation O&M SOS Server Database Views Database (e.g. PostgreSQL, MySQL, Oracle) 48 Default SOS DB with Transactional Feeding SOS Client Data Feeder GetObservation O&M InsertObserva- tion (O&M) SOS Server Default DB 49 Default SPS DB with SQL Feeding SOS Client GetObservation O&M SOS Server SQL Data Feeder Default DB 50 SOS as Proxy SOS Client GetObservation O&M SOS Server (Translator) Proprietary Service 51 Questions? Simon Jirka ([email protected]) 52 .
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