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SATWARE: A Semantic Middleware for Multi Sensor Applications

Sharad Mehrotra

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SAFIRE Stream Middleware

Writing sensor applications is hard: - Continuous data- Sensor heterogeneity - Diversity of platforms- Tolerance to failures

• Powerful programming abstractions to ease application development• Hide heterogeneity, failures,

concurrency

• Core Services• alerting, triggering, data &

stream management, queries.

• Mediation• application needs with

resource constraints of devices & networks

Sensor

FICB FiltersAlerts Analysis

Networks

SA Applications

Middleware – glue between H/w, networks, OS and applications

Networks

Stream Middleware Goals

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Key Concepts Driving SATWARE

Semantic Level: Entities -- people, appliances, and

buildings, rooms; Relationships – interactions.

Infrastructure Level: sensing devices, computing devices,

network devices.

Virtual Sensors: maps data captured by sensors into

events in the semantic world.

Event Logs: evolution of physical world as

observed by the sentient system

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SATware models sensor embedded spaces at two levels

sentient Applications

Virtual Sensor

High level stream language like CQL

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Key Concept: Virtual Sensors

Provide the “bridge” between sensors & the semantic “real” world concepts.

L, Room12, t>Filter

[L=Room1]

AP Readings Listener

AP Readings

to location

Translate Location to

Lon./Lat.

FingerprintDB

Location Virtual Sensor

WiFi fingerprints, t>

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Virtual Sensors: Multi-Sensor Fusion to improve quality

<Peter, L, PDF, t>

AP Readings Listener

AP Readings to location

FingerprintDB

<Pet

er, L

, PD

F, t>

Signal strength Listener

Signal strength

triagulation

APlocations

Merge

<Person, L, Room12, t>

Location Virtual SensorUsing fingerprints

Location Virtual SensorUsing signal Strength

triangulation

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Virtual Sensors: Speech illustrating how semantics can help improve quality

<victim, fire, help>

speechDB

<loud, fast>Acoustic analysis

Location Virtual SensorUsing speech recognition

Location Virtual SensorUsing acoustic

analysis

Audio listeners

Audio stream

Speech recognizer

Data Cleaning using semantics

Merge

<n-best-list>

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Building Applications using Semantic Model

Virtual Sensors “hide” complexity of sensor programming from application developers Convert heterogeneous sensor streams into semantic event streams Hide sensor failures / imprecision through

Noise reduction (e.g., averaging over multiple samples) multi-sensor fusion (e.g., multiple location sensing technologies provide more accurate

location assessment) Semantics (e.g., speech sensors exploit word correlation to improve on ASR)

Applications can view the system as consisting of high level concepts such as entities, events, artifacts, spaces, etc.

SATWARE supports high level query languages for implementing queries & triggers: SQL style stream language (at design stage – not yet implemented) Event graph based language

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Event Graphs in SATWARE

Triggers/continuous queries are converted into an event graph network. SATWARE Deployer submits the resulting event graph into an executable

pipeline based on available resources, machines and networks. Mediates with resources to guarantee application needs are met Multiple optimizations possible in executing such networks.

Locoperator

[FF1]

<FF1, L, Room12, t>

<FF1, L, Room12, t>

Join[t]

Filter[L=first floor]

Locoperator

[FF2]

<FF2, L, Room15, t>

{<FF1, L, Room12,t><FF2, L, Room15, t>}

Near[5 Rooms]

Detect when Fire Fighter 1 is on the 1st floor

Detect when FF1 & FF2 are near each other

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Demo

5/27/09

Programming

Execution

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SATWARE Summary Middleware to ease multi-sensor applications

provides a powerful semantic interface for complex multi-sensor applications this feature used extensively in building SAFIRE SA

Applications

Supports core services Alerts, triggers, storage, archival, & replay capabilities.

Mediation between application needs & system resources E.g., sensor stream scheduling based on application quality

requirement

5/27/09