using ontologies to reduce user intervention to deploy sensing campaigns with the incense toolkit

Using Ontologies to Reduce User Intervention to Deploy Sensing Campaigns with the InCense ToolkitPresented by:Marcela D. Rodríguez

CICESE/UABC, Ensenada, Mé[email protected]

1st International Workshop on Ubiquitous Mobile Instrumentation

Challenges to deploy a sensing campaign Deciding the granularity of the sensed

informationComponents that collect low-level data vs high-

level data Calibrating the sensing components to the

population to be monitored.To the particular participants characteristics Indicating a calibration criteria

The target users are researchers with little or no technical background

Developing a tool for behavioral data collection from mobile phones to enable researchers with low technical

skills to implement a sensing application: InCense

InCense implementation model Session: group of

components connected to achieve a sensing goal.

Sensors: act as interfaces with the mobile phone’s sensors

Filters: preprocess raw data from sensors

Survey: multiple choice or open- ended questions

Triggers: start sessions if certain conditions are met

Sink: data pool wherein the sensed information is assembled into files

OntoInCense<ontology>

User

Customize

Deploy

Analyse

Implement

Ontology-based GUIOntology to support customization

Code generation

Sensors Library Filters Library

Specification language and re-usable components

InCense API

Template Engine

Class Builder

<plug-in>

Contextual Database

Mobileapplication

Project Server

JSON< / >

Filter Explorer

Filter Generator

<template>

Configuration file Generator

<template>

InCense Architecture

InCense Manager

Use of the InCense API for implementing a sensing application


User

Customize

Deploy

Analyse

Implement

Ontology-based GUIOntology to support customization

Code generation



InCense API

Template Engine

Class Builder

<plug-in>

Contextual Database

Mobileapplication

Project Server

JSON< / >

Filter Explorer

Filter Generator

<template>


<template>


InCense Manager

OntoInCense


User

Customize

Deploy

Analyse

Implement

Graphical WidgetOntology to support customization

Code generation



InCense API

Template Engine

Class Builder

<plug-in>

Contextual Database

Mobileapplication

Project Server

JSON< / >

Filter Explorer

Filter Generator

<template>


<template>


InCense Manager

Scenario: “A public health organization (PHO) is interested in

comparing the walking habits of older adults in the winter and in the spring. They began using InCense for data gathering from 392 individuals during two weeks in the middle of January, and then again in May. The application captures the individual location, the activity level obtained from the accelerometers. A filter infers from the GPS and accelerometer, if the individual is walking or in a vehicle as he leaves his home. When InCense detects that the user is back at home, the mobile phones, will ask the individuals to complete a survey with question related to the activity being performed and their wellness. The data captured from the individuals is sent to the PHO to find interesting correlations with standard statistical packages.”

Extending the Filter Library

Implement a Filter Register a FilterRegistrar variables

to callibrate

Add the Filter to OntoIncense

Graphical Widget

Filter Explorer



to callibrate


Graphical Widget

a

b



to callibrate


Graphical Widget

Develop a sensing campaign

Select/drag Components

Add Relationships

Calibrate components

Participant height

Conclusions and Future work The ontology acts:

As a representational model: Facilitates to understand the implementation model of InCense

As a graphical user: Adds flexibilty to InCense Toolkit for customizing a sensing application.

We plan to evaluate InCense

using ontologies to reduce user intervention to deploy sensing campaigns with the incense toolkit

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