Middleware for indoor location-based services
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Slides used for my tutorial on indoor location-based services at ACM/IFIP/USENIX Middleware 2016
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Middleware for indoor location-based services
- 1. Middleware for Indoor Location-Based Services Daniele Miorandi U-Hopper & ThinkIN daniele.miorandi@u-hopper.com 1
- 2. Why me? 2
- 3. Went all the way from research to innovation & business 3
- 4. Background ⢠Wireless networking background (PhD in Telco Engineering) ⢠10 years in research (130+ papers, 4 patents, 20+ projects acquired) 4
- 5. Background (2) ⢠Executive VP R&D at U-Hopper since 2012 ⢠Coordinating R&D activities of the company (focus: big data analytics) ⢠Leading strategic innovation projects ⢠Founder & Chief Research OfďŹcer at ThinkIN since 2015 ⢠Leading algorithms design for indoor location-based services 5
- 6. Background (3) ⢠Started working on indoor LBS products since 2012 ⢠All the way from algorithm design to full-scale implementation & commercialisation ⢠Hands-on experience ⢠Led the design & implementation of the open source i-locate toolkit (more later on) 6
- 7. What are indoor LBSs? 7
- 8. DeďŹnition Indoor location-based services (LBSs) make use of the knowledge of the position of entities (people and assets) in indoor spaces to deliver value to their users 8
- 9. Why are they relevant? 9
- 10. 93% vs 7% ⢠According to US EPA we spend 93% of our time indoor ⢠For the 7% we spend outdoor we have a number of LBSs (think just of Google Maps) ⢠What do we have for the remaining 93% of our time? 10
- 11. Why now? 11
- 12. Unique combination of three factors ⢠Indoor positioning tech becoming mature ⢠Sub-meter accuracy possible, coarse-grained location cheap ⢠Standards for indoor spaces representation ⢠IndoorGML by OGC (http://www.opengeospatial.org/ standards/indoorgml) ⢠Standards ensuring interoperability among vendors & integrators ⢠InLocation Alliance (http://inlocationalliance.org/) 12
- 13. Are they fundamentally different from outdoor LBS? 13
- 14. Yes 14
- 15. In detail ⢠Indoor spaces are very different from outdoor spaces ⢠Outdoor can be represented as 2D, indoor is 3D (or 2.5D) ⢠Indoor you have building, rooms etc. Outdoor you donât ⢠Indoor positioning techniques are inherently noisy and inaccurate 15
- 16. Is there a real market for indoor LBSs? 16
- 17. Yes 17
- 18. Market data ⢠4.72 $B in 2016 ⢠CAGR of 37.4% ⢠Estimate to reach 23.13 $B in 2021 18 Source: Markets&Markets - http://www.marketsandmarkets.com/Market-Reports/indoor-positioning-navigation-ipin-market-989.html
- 19. Key messages ⢠Indoor LBS market is blooming ⢠There are plenty of opportunities ⢠And space for doing both high-impact research and delivering innovation 19
- 20. What are the application domains where indoor LBSs are taking off? 20
- 21. Hot verticals ⢠Retail ⢠ProďŹle shoppers behaviour in-store ⢠Context-aware marketing ⢠Industry ⢠Real-time location service ⢠Asset tracking & management (incl. logistics and warehouses) ⢠WorkďŹow optimization 21 ⢠Healthcare ⢠WorkďŹow optimization ⢠Asset tracking ⢠Patient monitoring ⢠Government ⢠Indoor navigation
- 22. Are there concrete and understandable use cases with an actual application potential? 22
- 23. Case #1: Indoor navigation ⢠Take me to a given ofďŹce ⢠Across outdoor and indoor spaces ⢠Navigate me also indoor (turn-by-turn instructions) ⢠Could be useful in: ⢠Government ofďŹces ⢠Large hospitals ⢠Shopping malls ⢠âŚ. 23
- 24. Case #2: (Portable) Asset management ⢠Access all information about assets in your organization ⢠Including the actual location of portable ones ⢠E.g., a deďŹbrillator in a hospital ⢠Real-time search ⢠For usage ⢠For maintenance 24
- 25. Case #3: People tracking ⢠Monitor the movement of fragile patients at home or in a semi- controlled environment (nursing home) ⢠Couple with geofencing for alerting risk situations (e.g., exiting the building or waking up at night) 25
- 26. Case #4: WorkďŹow Optimization ⢠Track the movement of workforce and assets in a factory ďŹoor ⢠Translate movement patterns into execution status of industrial workďŹows ⢠Real-time dynamic optimization and ex-post analysis of execution efďŹciency 26
- 27. Case #5: Safety of Personnel ⢠Track in real-time the position of personnel in hazardous environments (e.g., oil reďŹnery or offshore rig) ⢠Alert in case of entering safety-critical areas ⢠Track and guide in case of evacuation alarm or mustering 27
- 28. Case #6: Location-based content delivery ⢠You walk in a museum ⢠As you approach an artwork you get delivered multimedia content explaining the context in which it was created 28
- 29. Who are the key market players? 29
- 30. Positioning tech Estimote - kontakt.io - Quuppa - Zebra - Cisco - OpenRTLS 30 Retail solutions RetailNext - Walkbase - RetailerIN - Euclid - Tyco Retail Solutions Healthcare solutions Senion -TeleTracking - Locatible - GE Healthcare - Nively Indoor Mapping Google - Micello - OpenStreetMap - IndoorAtlas Industry solutions SkyeTech - OmniID - Extronics - Engica - ThinkIN
- 31. Watch out⌠31
- 33. Think about google maps⌠⢠Render a map ⢠Position yourself on said map ⢠Search for a place & show that place on the map ⢠Includes resolving the place name to a position ⢠Compute a route from A to B ⢠Multiple transportation means, even combined (multimodality) ⢠Navigate from A to B along the route 33
- 34. KETs for indoor LBSs ⢠Indoor Positioning ⢠Maps ⢠Geocoding ⢠Geofencing ⢠Routing ⢠Analytics 34
- 35. Positioning: Qs ⢠What indoor positioning technologies are available? ⢠How do they compare with one another? ⢠Are they sufďŹciently stable? 35
- 36. Positioning: Existing technologies ⢠Based on radio technologies ⢠Proximity: beacons, RFID ⢠Location: WiFi, BLE, UWB, ZigBee ⢠Based on cameras 36
- 37. Positioning: Existing technologies (2) ⢠The practitionerâs view: cluster in two main categories ⢠Sub-meter accuracy: ⢠BLE (Quuppa) ⢠UWB (whatever based on Decawave chip) ⢠Coarse-grained (room-level accuracy): ⢠Beacons ⢠WiFi (with trilateration) ⢠ZigBee 37
- 38. Positioning: Existing technologies (3) 38 High AccuracyLow Accuracy Low TCO High TCO Quuppa UWB Beacons WiFi Camera ZigBee
- 39. Positioning: Existing technologies (4) ⢠Additional approaches: ⢠Based on variations in the Earthâs magnetic ďŹeld ⢠Dead reckoning ⢠Visible light communication-based ⢠FM radio-based ⢠etc.etc. 39
- 40. Positioning: stability ⢠Indoor position is intrinsically noisy ⢠Fundamentally different from outdoor positioning (where GPS signal - maybe with EGNOS - provides good enough accuracy/reliability in 99% for use cases) ⢠Requires a lot of post-processing ⢠No silver bullet ⢠No out-of-the-box solution 40
- 41. Maps: Qs ⢠How to represent indoor spaces? ⢠What about standards? ⢠Are there sufďŹcient indoor maps available? ⢠Are there open data repositories of maps? 41
- 42. Maps: How to represent indoor spaces ⢠Various approaches are possible ⢠For a good overview: Worboys, M.F., Modeling indoor space (keynote). Third ACM SIGSPATIAL International Workshop on Indoor Spatial Awareness (ISA 2011), November, Chicago, IL. 2011. ⢠Semantic models represent the types of entities in indoor space, as well as their properties and relationships (â> ontology) ⢠Topological models: focus on connectivity properties of a space ⢠Geometrical models: focus on geometry of indoor spaces (e.g., CAD) ⢠Hybrid: topological with geometrical features embedded in the description 42
- 43. Maps: standards ⢠Various standards have been proposed for the representation of indoor spaces ⢠The key standardization body in this ďŹeld is the Open Geospatial Consortium (OGC, http:// www.opengeospatial.org/ogc) ⢠Our focus: indoorGML 43
- 44. Maps: indoorGML ⢠IndoorGML = open data model & XML schema for indoor spatial information ⢠Concepts: ⢠Space is structured as cells (cell~room) ⢠Geometry of cells can be described either directly, through external representation (CityGML) or can be omitted ⢠From geometry (primal space) to topology (dual space) through PoincarÊ duality ⢠Multi-layer representation of connectivity (walking user, wheelchair, robot, drone etc.) ⢠Anchor node: connection with outdoor graphs (e.g., OSM) 44
- 45. Interconnecting indoor - outdoor ⢠Entrance of the building is a special node ⢠Anchor point where outdoor and indoor networks are connected 45
- 46. Special links - vertical connectors ⢠For each ďŹoor a graph is constructed ⢠The graphs are interconnected through vertical links representing elevators or stairs 46
- 47. Maps: Availability ⢠How many indoor maps available out there? ⢠In the range of thousands (estimate) ⢠The point is accessibility ⢠Indoor is NOT outdoor (!) ⢠A building is not a public space ⢠Access depends on the owner/manager ⢠In some cases (e.g., governmental buildings) there may be security reasons to prevent making data openly accessible 47
- 48. Maps: Open Data? ⢠Fragmented landscape (in total few hundreds): ⢠From i-locate portal: http://portal.i-locate.eu/ ⢠From OSM community: http://wiki.openstreetmap.org/wiki/ Indoor_Mapping ⢠From OpenStationMap: http://openstationmap.org/ 48
- 49. Geocoding: Qs ⢠How to translate description of spaces to coordinates? ⢠What about the other way round (from coordinates to description)? 49
- 50. Geocoding: As ⢠Geocoding for outdoor spaces: commercial/open source solutions already out there ⢠Need to augment it for indoor spaces ⢠Similar functioning, can be implemented using, e.g., PostGIS extension to PostgreSQL ⢠And then combine outdoor + indoor results (indoor are 3d!) ⢠Same for reverse geocoding 50
- 51. Geofencing: Qs ⢠How to handle matching of indoor position data with a space-time rule (enter an area, exit an area, stay in an area for a given time)? ⢠How to make it scalable? 51
- 52. Geofencing: As ⢠At the abstract level: ⢠Understand whether a point (=position of an entity) is inside a region (deďŹned as a generic polygon) ⢠In case it is and it was not before, ďŹre an event ⢠No major differences wrt outdoor, but: ⢠Finer-level granularity (room? close to an object in a room?) ⢠Need to cope with noisy position data 52
- 53. Geofencing: As ⢠Various commercial solutions available ⢠Some opensource solutions, but hard to scale ⢠Processing-intensive â> big data streaming architecture ⢠Imagine 10,000 geofences and data about 1M entities transmitting their position every 1sâŚ. ⢠For a good intro look at John Murrayâs approach (using MongoDB features, http://www.johnmurray.io/) 53
- 54. Routing: Qs ⢠How to route in indoor spaces? ⢠How to route across outdoor and indoor spaces? ⢠What are the differences to outdoor spaces only? 54
- 55. Routing: As ⢠Requires a graph representation (connectivity graph) of the indoor space ⢠Natively supported if space represented as indoorGML ⢠Possibility of supporting different transportation means (walking, wheelchair etc.) ⢠Outdoor-to-indoor routing: just connect the two graphs through anchor node ⢠Differences from outdoor routing: 3D! ⢠Need to account for ďŹoor changes (lift or stairs) ⢠Lot of subtleties (e.g., what about half ďŹoors?) 55
- 56. Analytics: Qs ⢠Do I need speciďŹc data processing pipelines for producing analytics related to the occupation of indoor spaces? ⢠How to make it scalable? 56
- 57. Analytics: As ⢠Data processing pipelines used for computing outdoor analytics need to be tailored to deal with the speciďŹc features of indoor environments ⢠In particular, noisy positioning data ⢠Presence of physical barriers ⢠Use of contextual information for data cleaning 57
- 58. Analytics: examples ⢠Tracking assets ⢠Utilization ⢠Where used ⢠and by whom 58
- 59. Analytics: examples (2) ⢠Tracking people ⢠Visits over time ⢠Dwell time in a given area ⢠Heatmaps ⢠Frequency ⢠Duration ⢠Common paths 59
- 60. Analytics for indoor spaces ⢠Computing analytics for indoor spaces is a processing-intensive process ⢠Can be implemented using `standardâ big data stacks based on open-source stuff (kafka+spark +redis+cassandra) ⢠Algorithms for data processing and scalable KPIs computation are an active research ďŹeld 60
- 61. How are indoor LBSs structured? 61
- 62. Is there a reference architecture for indoor LBS? 62
- 65. No matter if you are a smart hackerâŚ
- 66. .. or a Web entrepreneurâŚ
- 68. ..with a clever idea for a new application enabled by indoor positioning
- 69. This will be your expression when you start building it!
- 70. At the moment.. ⢠Applications developed using a silo-like approach ⢠Integrated all the way down to the positioning system ⢠App developer are required to have understanding of domain speciďŹc issues (geocoding? WMS? handling noisy data?) ⢠â> Inhibiting innovation in the ďŹeld ⢠â> High entry barrier for new players 70
- 72. wasting time
- 73. and money!
- 75. ⢠http://www.i-locate.eu/ ⢠âIndoor/outdoor location and asset management through open geodata" ⢠EU project, funded under the CIP/PSP programme ⢠Open by default (code, maps, data, papers etc.) ⢠Relevance: developed an open-source toolkit for allowing app developers to quickly build & deploy indoor LBS ⢠Coupled with a portal for hosting maps and indoorGML representations 75
- 76. ⢠Consortium comprising ⢠Led by Trilogis (IT), including high-tech SMEs (U-Hopper, ZigPos, IndSoft, Epsilon, GeoSys, Fida Solutions), innovation ďŹrms (Technoport, UrbaSoďŹa, GSIG, C3L, Gist), research institutions (TUE, FBK) as well as end users (Alba Iulia Hospital, Brasov Municipality, Velletri Municipality, Rijeka Municipality, Tremosine Municipality, APSS, Bruckenthal Museum, Municipality Baia Sprie, Genova Municipality, Mitera Hospital) ⢠14 pilots across 8 countries ⢠Covering a variety of use cases spanning outdoor and indoor spaces 76
- 77. What are the key middleware functionality required? 77
- 78. Key functionality required 78 ⢠Retrieve the position of an entity indoor ⢠Search for an indoor place & show that place on the map ⢠Includes resolving the place name to a position ⢠Compute a route from A to B ⢠Navigate from A to B along the route ⢠Create geofences
- 79. Is there anything from GIS that can be reused? 79
- 80. Indoor GIS ⢠A lot of concepts and technical enablers can be taken from the GIS ďŹeld ⢠Yet, indoor information is inherently different ⢠Requires knowledge related to: ⢠Signal processing ⢠Indoor-speciďŹc standards (indoorGML) ⢠Big data 80
- 81. How do I build indoor LBSs? Are there open-source framework I can (re-)use? 81
- 84. released under a permissive open source license (Apache v.2) and enabling out-of-the-box two types of indoor LBSs:
- 85. #1: Self-app ⢠Know where you are (outdoor/indoor) ⢠Compute route to intended destinations (outdoor/indoor) ⢠Turn-by-turn navigation to intended destinations (outdoor/indoor) As added-value service (more later)
- 86. #2: Asset tracking ⢠Track the position of portable equipment in (near) real-time ⢠Plus geofencing, asset maintenance etc.etc.
- 87. i-locate toolkit design principles 1. Loosely coupled components 2. All is REST 3. Data is king 4. G&G (Grab&Go)
- 90. Proxy ⢠Localization is done server-side ⢠The proxy: ⢠Combining data from different positioning technologies (sensor fusion) ⢠Using them to estimate current position ⢠Makes higher-level components positioning technology agnostics
- 91. Proxy ⢠Unique access point for locating entities ⢠Currently supported technologies: ⢠Quuppa ⢠eeRTLS ⢠WiFi (through outdoor localization + Combain + passive PI-Radar) ⢠GPS ⢠QR codes ⢠Beacons ⢠EGNOS (through external device) ⢠Implemented in PHP, using YII framework ⢠Easily extensible 91
- 92. ConďŹguration ⢠Allows to read/write speciďŹc attributes of tracked entities ⢠E.g., battery level, RSSI etc. ⢠REST interface ⢠GET ilocate/conďŹgura3on/getLocaliza3onSystems ⢠PUT ilocate/conďŹgura3on/put/{localiza3onSystem_id}/{obj_id} ⢠Requires to be deployed locally on a gw or local server able to connect to the gw over REST ⢠Supported Indoor Localization Systems: ⢠Quuppa ⢠eeRTLS ⢠Implemented in Java 92
- 93. Communication bus ⢠Based on the MQTT protocol ⢠Lightweight pub/sub system for IoT ⢠OASIS standard ⢠Using the Mosquitto broker implementation ⢠All location updates dispatched through mqtt broker ⢠Additional plugin developed for handling authorization for subscriptions 93
- 94. Monitoring ⢠Aimed at sysadmins: check the status of services & support troubleshooting ⢠Based on the Elastic (former: ELK) stack ⢠Shippers read logs from VMs (or: containers) hosting services and send to a centralized logstash server ⢠Logstash server processes logs and stores them in an ElasticSearch DB ⢠A Kibana dashboard is attached to the DB for visualizing logs ⢠Can be easily conďŹgured to deďŹne which data to log 94
- 95. Security & Privacy ⢠Provides self-registration, authentication, validation & authorization functionality ⢠Authorization based on policies designed around a RBAC scheme ⢠Based on openAM opensource framework 95
- 96. OGC Spatial ⢠Provides access to geographical information in a standardized, interoperable way ⢠OGC standard ⢠WMS, Web Map Service ⢠WFS, Web Feature Service ⢠Makes i-locate data accessible by the most common GIS client ⢠Based on open source engine (geoserver) ⢠Includes geoserver functionality 96
- 97. Spatial solver ⢠Provides an interface to access the i- locate Open Repositories ⢠Includes tools and functions to ďŹlter and process geodata ⢠Based on PostGIS, includes RestFUL APIs ⢠Able to process also external datasets 97
- 98. Geofencing ⢠Generate alerts when tracked entities move in or out of a given region ⢠Push and pull notiďŹcations ⢠[Proprietary tech by Trilogis] ⢠[Check John Murray site for alternative open source implementations] 98
- 99. Location analytics ⢠Provides statistics on the usage of indoor spaces ⢠Based on proprietary ThinkIN platform (thinkin.io) ⢠Open APIs and wrapper (data ingestion) based on Apache Kafka 99
- 100. Routing ⢠Based on the OpenTripPlanner (OTP) open-source platform for multimodal routing ⢠It supports multiple indoorGML graphs and outdoor OpenStreetMap data 100 Routing service Routing algorithm Navigationgraph Indoor Graphs Outdoor Graphs indoorGML OpenStreetMap Multimodal routing Avoidance setting Etc.Start/end locations (latitude/longitude/level) Travel plan (with turn-by-turn navigation information)
- 102. Asset Management ⢠Connector to Box3 asset management service by Trilogis ⢠Integration of the assets representation and geographical information ⢠Compliant with ISO 55000 (asset representation) and supporting indoorGML 102 i-locate - Indoor/outdoor LOCation and Asset management Through open gEodata (GA 621040) Figure 24: Web Client e web client is composed by two main parts. A frontend, composed by web client itself, and a ckend, consisted by two component, application server hosting the client and the engine for the et management. The web client is a solution based on Terra3 webgis provided by Trilogis and is inly based on Javascript and OpenLayer libraries. The Asset Management engine is based on x3 application provided by Trilogis and is a stand alone solution developed in .NET technologies ning on a dedicate machine. e template comes in the form of a prototype which supports:
- 103. ⢠S u p p o r t a s s e t management use case ⢠WebGIS functionalities ⢠R e a l T i m e a s s e t s position ⢠Extensible Framework Web Client template 103
- 104. Mobile App Template ⢠Support citizen guidance use case (indoor/outdoor) ⢠Developed using Titanium Appcelerator SDK (cross-platform support) ⢠Template to be personalised for matching speciďŹc use case requirements ⢠Supports: ⢠Locating user on a map (indoor/outdoor) ⢠Search for a place ⢠Compute route ⢠Display route on the map ⢠Turn-by-turn navigation 104
- 106. Are we forgetting something? ⢠We need a way to retrieve (indoor) maps ⢠We need a way to create/manage/retrieve indoorGML representations ⢠(And yes, we also need to retrieve outdoor maps) ⢠â> The i-locate portal 106
- 107. The i-locate portal ⢠An infrastructure able to handle indoor/outdoor GIS ⢠Maps ⢠IndoorGML ⢠Based on âstandardâ GIS tools: ⢠Geoserver/PostGIS/PostgreSQL ⢠Available as open source as well 107
- 108. Hands-on 108
- 109. Portal Demo 109
- 112. Whatâs in the Postman collection ⢠Get a map (portal) ⢠Give me my position (proxy) ⢠Compute the position of an entity (proxy) ⢠Resolve an indoor address (geocoder) ⢠Compute route from A to B (routing) ⢠âŚplus a number of convenience calls 112
- 115. Training Material http://www.gisig.eu/platform/course/index.php?categoryid=15 115 Videos and lectures freely available (registration required) at: