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Synthesis and Sharing of Sensory Datasets in Pervasive Spaces

This project aims to develop a standard for synthesizing and sharing sensory datasets in pervasive spaces, to facilitate testing of new ideas and algorithms. The proposed XML-based standard, SDDL, provides a hierarchical representation of dataset metadata and numeric data, allowing for easy sharing and reuse of existing datasets.

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Synthesis and Sharing of Sensory Datasets in Pervasive Spaces

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  1. Synthesis and Sharing of Sensory Datasets in Pervasive Spaces Shantonu Hossain shossain@cise.ufl.edu Mobile and Pervasive Computing Lab

  2. Motivation • Synthesis and realistic simulation of Sensory Datasets is becoming more important for thoroughly testing new ideas and algorithms - • High cost of building pervasive spaces with correct design and planning. • Huge time required to generate enough data for a meaningful collection of pattern/events. • Inability to explore additional goals/concerns which was not thought of during data collection. • Synthesis requires sharing and utilizing existing datasets culminated from various deployments.

  3. Motivation

  4. Why Do We Need Standardization? • To be able to reuse datasets collected by other researchers. • Describe and specify the dataset in terms of – • space • sensory data • researcher-implicit assumptions/methods. • To foster a greater level of interoperability and cross use of datasets and extend the utility of the dataset for advanced research. • To pave the way for simulating new ideas and algorithms more rigorously. • So, we have proposed an XML-based standard for Sensory Dataset Description Language (SDDL), which is driven from examining existing datasets owned by several research collaborators.

  5. Project Overview Research Community Research Community Research Community Research Community Evaluate new ideas Evaluate new ideas Existing Dataset Existing Dataset PerSim-Synthetic Data Simulator SDDL Converter Sensory Dataset in SDDL format

  6. PerSim: Synthetic Dataset Simulator for Pervasive Spaces

  7. Dataset in SDDL Algorithm for Simulating Synthetic Dataset Simulation Project Simulation Project Simulation Element Handler Simulation Parameter Controller SDDL Parser Graphical User Interface Architectural Overview

  8. SDDL: Sensory Dataset Description Language

  9. SDDL Features • Provides hierarchical and structured representation of both meta-data related to the dataset and numeric data collected from the space. • Organizes the dataset in a compact way so that all information can be accommodated into a single XML file. It also eliminates redundant information and saves space. • Provides self-explanatory presentation of data so that any person who is not familiar with the dataset can get the insight of the data very quickly without much effort. • XML representation of SDDL makes it powerful and easy to parse which can be useful for sharing and reusing existing datasets for further research.

  10. SDDL Development Methodology Phase 1: Initial Development Phase 2: Iterative Analysis and Refinement

  11. - Data Set Id - Data Set Name Sensory Dataset • Contact Name -Organization • Phone - Email Contact Info Project Description Sensor Info History Project Specification Actuator Info Space Layout Activity Info Dataset Description Location Info Parameters Data Set Contexts Separators • - Date - Timestamp • Sensor ID - SensorVal • ActivityPerformed - SensorLabel Sensor Event

  12. Example: A part of WSU Smart Apartment Dataset <Sensory_Datasetname="Participant performing task 1" id="p01.t1"> <Contact_Info name="Dr. Diane J. Cook" organization="Washington State University, Pullman, WA 99163r" email="cook@eecs.wsu.edu" phone=""/> <History> <Project_Description>The experiment is performed in WSU Smart Apartment is part of the ongoing CASAS smart home project at WSU. T</Project_Description> <Space_Layout> <description>The apartment is a three-bedroom apartment located on the Washington State University campus. It includes three bedrooms, one bathroom, a kitchen, and a living / dining room.</description> <Project_Specification> <Sensor_Info count="59"> <Sensor id="M01" name="" type="motion sensor" unit=""min_value=""max_value=""location_id=""/> <Sensor id="M02" name="" type="motion sensor" unit=""min_value=""max_value=""location_id=""/> <Sensor id="M03" name="" type="motion sensor" unit=""min_value=""max_value=""location_id=""/> <Activity_Info count=“5"> < Activity id=“” name=“make a phone call” /> < Activity id=“” name=“cooking” /> <Sensor_Event id=“”> <Data>2008-02-27 12:43:27.416392 M08,ON2008-02-27 12:43:27.8481 M07,ON008-02-27 12:43:28.487061 M09,ON 2008-02-27 12:43:29.222889 M14,ON2008-02-27 12:43:29.499828 M23,OFF <Activity_Performed>make a phone call</Activity_Performed> </Sensor_Event> </Sensory_Dataset>

  13. SDDL Converter • A web based interface to convert existing datasets to SDDL format. • Provides user friendly interface for- • Organizing datasets in a structured way. • Specifying necessary information about the dataset. • Performing dataset post-labeling based on activity/active contexts. • Can be extended to perform noise estimation for extreme points for a given dataset.

  14. How to obtain ? • An overview of Sensory Dataset Description Language (SDDL) is available at http://www.icta.ufl.edu/persim/sddl/ • A pdf version of SDDL Specification v1.0 can be downloaded from the same location.

  15. References • A. Helal, A. Mendez-Vazquez, S. Hossain, “Specification and Synthesis of Sensory Datasets in Pervasive Spaces”, IEEE Symposium of Computers and Communications, Tunis, Tunisia, July 2009. • D. J. Cook and M. Schmitter-Edgecombe, “Activity Profiling using Pervasive Sensing in Smart Homes”, IEEE Transactions on Information Technology for Biomedicine, 2008.

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