On data model for context–aware services

Dmitry NamiotLomonosov Moscow State University

dnamiot@gmail.com

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.

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

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)

Metrics

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

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

iBeacons

Related projects

Related projects

CityProximus: prototype

• The prototype (Fraunhofer, FOCUS):

CityProximus:shortly

• A set of rules:• Network fingerprint – > data chunks

(information)• Can use existing networks as well as

especially created wireless nodes

CityProximus: 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)

CityProximus: data modelRules: productionsIf (fingerprint condition) then { present some

content }RETE algorithmREST API with JSON output:[ { “type”:”some_type”,”data”:”some_data”}, {“type”: ...},...]

CityProximus: NoSQL model

• Key-value store• Key: MAC-address• Value: JSON array• Apache Accumulo• Query by index• Bloom filter for cache