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Internet of Things and Smart Spaces

SmartConference System

Development of new technologies brings people new possibilities such as smart spaces. Smart spaces can provide better user experience by allowing a user to connect new devices flexibly and to access all the information in the multi device system from any of the devices. Smart Conference system developed in the course of this project is the interactive system for conferences, meetings, symposiums, other similar events. The project is based on the open source Smart-M3 system which implements the concept of the smart space.

This system has been tested on the FRUCT 7 Conference (St. Petersburg, Russia), RUSmart 2010 (St. Petersburg, Russia), FRUCT 8 Conference (Lappeenranta, Finland), and FRUCT 9 Conference (Petrozavodsk, Russia). Also it has won the Russian Mobile VAS Award in 2009 and 2010.

Project Description

 

The conference room is equipped by two LCD projectors. The first screen is used for showing presentation and the second for showing agenda of the conference section. The room represents a smart space which integrates stationary devices, different external or internal services, and mobile devices of the conference participants. This allows providing an extended access to the information and services independently of their physical location. It is assumed that every conference participant has a personal mobile device (for example Nokia N810, N900).

Every event participant has the appropriate software installed on his/her mobile device which includes graphic user interface form and Smart-M3 based module for interaction with smart space. Also this software implements participants’ profiles and interfaces to access them. The profile provides to the system the information about the participants: personal information, presentation title, interests, presentation URL which is useful for other event participants.

The software possesses intuitive graphical interface developed for the Maemo OS based mobile devices. It allows managing by the agenda of the event, viewing information about participants, viewing participants presentations and changing information in own profile. Time management functions of the software allows to remind to the participants about the time remaining for presentation. When the time of the presentation is over the software asks the participant if he/she finished the presentation. If needed, the software provides the participant with additional time for the presentation.

Every participant who registers in the smart-space is assigned time interval for the presentation. List of the participants is shown in second screen and in participant’s mobile devices. The current presentation is highlighted. When presentation is started the LCD projector automatically shows it. Participants can change their presentation slides using their mobile devices.

The conference chairman has possibility to change the order of the speakers during the section (this is useful in case of one of the speaker is absent in time of his/her presentation), and also he/she has a possibility to close current presentation and run next presentation.

Timing and Deliverables

 

April 2009 - Initial plan. Requirements specification.

October 2009 – Development Maemo based interface forms.

November 2009 – Studying of Smart-M3 platform.

April 2010 – Organizing smart space section on the FRUCT seminar using developed software.

May 2010 – December 2010 – Testing the System on the conferences specification of the new useful features, its implementing, bug fixing.

Jan 2011 – April 2011 – Integration the Smart Conference System and Scribo System (PetrSU).

May 2011 – November 2011 – Development extensions and modifications to SCS.

Project Team

Contact person: Alexey Kashevnik , PhD, project leader, SPIIRAS

Developers:

Juras Valchenko, M.Sc. Student
Michael Sitaev, M.Sc. Student
Sergey Kokorin, PhD Student

 

SmartSlog: An ANSI C Code Generator for the M3 Platform

Web ontology language (OWL) allows structuring smart space content in high-level terms of classes, relations between them, and their properties. In Smart-M3, a semantic information broker (SIB) maintains the smart space in low-level terms of triples, based on resource description framework (RDF). SmartSlog supports constructing Smart-M3 knowledge processors (KPs) that consume/produce smart space content according to high-level ontology terms. The solution is based on the code generation approach.

Building a Model of a Smart City

Project motivation and summary


Every day a citizen of a big city faces such occurrences as problems in municipal sphere, disadvantages of public transport, traffic jams, overcrowded streets, imperfection of ervices, etс. And there is a need of more effective time usage that correlates with ighlighted problems. Infrastructure that already exists and potentially can be developed provides citizens with opportunity to solve globalization problems.

An idea of "Smart City" is the idea of interaction (informational exchange) between the citizen and city infrastructure. However, this information exchange is profitable not only or the citizen, but also for city authorities. They are interested in it in order to facilitate accomplishment of additional process and concentrate on solving core tasks. The project ill be done in 2 parts addressing short–term and long-term targets the first phase is expected to last about 9-12 months and focus primary on the gathering information and corresponding theoretical investigation. The second long-term part is technical part that uses theoretical findings of the first part for developing and implementing prototype solution for the identified problems.

Project goals


Short-term goals

  1. Make an overview of existing theoretical achievements similar to “Smart city”
  2. Investigate non-technical ( e.g. administrative and legal ) infrastructure issues
  3. Analyze and assess existing city (Saint-Petersburg) infrastructure
  4. Assess constantly growing necessities

Long-term goals

  1. Create a prototype of facilitating mechanism named “Smart City”
  2. Implement the proposed mechanism.

Timeline and deliverables


The short-term (9-12 month) deliverables are following:

  1. An article describing current infrastructure conditions and determining existing problems.
  2. An article describing basic features of the system needed for solving of the current problems.

The long-term deliverable is a proposal and development of the full technical solution for reating "Smart City" system.

Project team


Pavel Gonchukov, student, SUAI - project leader
Anastasia Starkova, student, SUAI
Alexey Koren, PhD student, SUAI

System analysing pedestrian movement in city environment

Motivation and summary


Advanced system for pedestrian movement analysis become necessary during development Spirit Guide - interactive tourist support system. The Spirit Guide is a system providing voice guide service for tourists. The provided content depends on location and according to user's movements audio stream switches to one or another.

One of the problems to be solved is positioning with high accuracy. We have number of positioning system, and every system has its advantages and disadvantages. Using GSM etworks we can determinate position with accuracy about 200–400 meters in big city. Another issue is pattern of position switching. After jump from one base station to another coordinates change to new point in a couple of hundreds meters away what is no good for analysing algorithm.

GPS (or A-GPS) accuracy is affected by a number of factors, including satellite positions, noise in the radio signal, atmospheric conditions, and other barriers to the signal such as buildings. GPS can give accuracy up to 10 meters with good conditions. But other problems of GPS positioning are time of cold start which can be up to 20 minutes and big power consumption.

Also GPS can lose signal or go to "bad" state, especially at small streets. In this research we are going to investigate possible solutions of problems described above using combination of GSM, GPS, user interaction, city map and introducing a mathematical model based on behavioural patterns.

Project goals


  1. Make an overview of existing positioning solutions and technologies
  2. Determine and analyze problems of those technologies
  3. Propose functional specification for mathematic model which would collect data from different positioning technologies, combine them, analyze and predict possible user's movements
  4. Implement prototype of the system based on mathematic model described in 3.

Timeline and deliverables


  1. The short-term (9–12 month) deliverables are following:
  2. An article describing current state of positioning technologies and our approach to solving this problems
  3. An article describing mathematic model which will be able to solve these problems
  4. A prototype of the system which uses combination of existing positioning technologies and implements mathematical model described in article 2

Project team and contacts


Alexander Buntakov, student at SUAI, project leader

Alexander Sidorenko, PhD student at SUAI

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