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On Physical Web models

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On Physical Web models Manfred Sneps-Sneppe Ventspils University College, Latvia [email protected] Dmitry Namiot Lomonosov Moscow State University, Russia [email protected] SIBCON 2016 12.05.2016
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Page 1: On Physical Web models

On Physical Web models

Manfred Sneps-SneppeVentspils University College, Latvia

[email protected]

Dmitry NamiotLomonosov Moscow State University, Russia

[email protected]

SIBCON 2016 12.05.2016

Page 2: On Physical Web models

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.

Page 3: On Physical Web models

How to enumerate physical objects

• QR-code• RFID• Wireless tags:

iBeacons, EddyStone• Hotspot on mobile

phone can play a role of tag

Page 4: On Physical Web models

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

Page 5: On Physical Web models

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.

Page 6: On Physical Web models

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)

Page 7: On Physical Web models

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

Page 8: On Physical Web models

Metrics

• The basic element: fingerprint• A list of “visible” nodes: ID, MAC-address,

RSSI (signal strength)• Occurrence counting• RSSI-based “distance”

Page 9: On Physical Web models

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

Page 10: On Physical Web models

iBeacons

Page 11: On Physical Web models

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.

Page 12: On Physical Web models

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.

Page 13: On Physical Web models

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).

Page 14: On Physical Web models

Data modelRules: productionsIf (fingerprint condition) then { present some content }RETE algorithmREST 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.

Page 15: On Physical Web models

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

Page 16: On Physical Web models

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.


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