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On Physical Web models

The Physical Web is a generic term describes interconnection of physical objects and web. The Physical Web lets present physical objects in a web. There are different ways to do that and we will discuss them in our paper. Usually, the web presentation for a physical object could be implemented with the help of mobile devices. The basic idea behind the Physical Web is to navigate and control physical objects in the world surrounding mobile devices with the help of web technologies. Of course, there are different ways to identify and enumerate physical objects. In this paper, we describe the existing models as well as related challenges. In our analysis, we will target objects enumeration and navigation as well as data retrieving and programming for the Physical Web

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On Physical Web models

  1. 1. On Physical Web models Manfred Sneps-Sneppe Ventspils University College, Latvia Dmitry Namiot Lomonosov Moscow State University, Russia SIBCON 2016 12.05.2016
  2. 2. What is Physical Web •The Physical Web: describes interconnection of physical objects and web. •The basic idea: to navigate and control physical objects in the world surrounding mobile devices with the help of web technologies. •The target: objects enumeration and navigation as well as data retrieving and programming for the Physical Web.
  3. 3. How to enumerate physical objects • QR-code • RFID • Wireless tags: iBeacons, EddyStone • Hotspot on mobile phone can play a role of tag
  4. 4. Context • Context is anything we can add to location • Models for context-aware systems: • Data exchange depending on the context • Situational awareness • Context-aware data discovery and data search
  5. 5. Network proximity • A special model for context-aware services • Context described as a set of wireless networks (nodes) • Wi-Fi access points, Bluetooth nodes, Bluetooth tags • Data could be directly associated with network nodes.
  6. 6. Network proximity • Describe data models based on the detection of surrounding network nodes. • Lets us build mobile computing systems based on the detection of physical objects via network proximity. • The proximity is a very conventional way for context-aware programming in the mobile world. • The idea is to allow mobile web pages dependencies on proximity of physical objects (wireless nodes)
  7. 7. Why network nodes? • Wi-Fi (Bluetooth) devices are everywhere • Wi-Fi (Bluetooth) is presented in every mobile phone • Easy to measure (existing standards) • We can reuse existing infrastructure • There is no connection with location (geo- coordinates). Data are linked to nodes “visibility” instead of location
  8. 8. Metrics • The basic element: fingerprint • A list of “visible” nodes: ID, MAC-address, RSSI (signal strength) • Occurrence counting • RSSI-based “distance”
  9. 9. QR-Code for Physical Web • QR-code contains some URL • The modified QR- code reader adds parameters about context • The final URL contains information about surrounding wireless nodes
  10. 10. iBeacons
  11. 11. Google Physical web • Google own protocol for Bluetooth low energy (BLE). • Eddystone defines a BLE message format for proximity beacon messages. • The general idea is the same as with the “classical” iBeacons: tags broadcast some ID, an application uses ID for getting data from the cloud.
  12. 12. Google Physical Web Application on the mobile device automatically discovers nearby objects, obtains associated data (URLs in this case) and pushes this information to the user.
  13. 13. Software architecture • Data base for network proximity rules and content • Rules editor • Application server (API for developers) • Mobile application for access to content (context-aware browser) The business process could be presented as a set of productions (rules). Each of the rules depends on some available data, on some global variables (states).
  14. 14. Data model Rules: productions If (fingerprint condition) then { present some content } RETE algorithm REST API with JSON output: [ { “type”:”some_type”,”data”:”some_data”}, {“type”: ...},... ] The data availability always assumes the presence of data for any finite set of timestamps. The application makes conclusions (actions) depending on some window of measurements.
  15. 15. Google Nearby API • Tag’s attributes: advertised ID, current status, expected stability, geo-coordinates (latitude, longitude pair), ID for Google Places, indoor floor level and text description • Nearby API: create features based on proximity. • Exposes simple publish and subscribe methods that rely on proximity
  16. 16. Bluetooth Data Points (BDP) • BDP: link (associate) user- defined data with existing wireless networks nodes. • The BDP project targets Bluetooth nodes in the discoverable mode • Any mobile users should be able to create (open) Bluetooth node right on the own mobile phone, associate some data with this node and so, make them available for other mobile users in the proximity. • Bluetooth node in the car: car’s owner can attach data to the own node.