Analysis of Service-Oriented Infomobility System and Architecture

Model

Stanislav Simeonov

1 a

, Ekaterina Gospodinova

2 b

, Ivan Torlakov

and Asen Iliev

1 c

Department of Computer Systems and Technologies “Prof. Dr Assen Zlatarov” University, Burgas, Bulgaria

Department of Electronics, Automation and Information Technologies, Technical University of Soﬁa, Sliven, Bulgaria

ﬁ

Keywords:

Infrastructure, Multiples Theory, Multimodality, Ontology, Travel Planning.

Abstract:

This paper examines the development of a method and a model for building a service-oriented information

mobility system that improves the quality of user service by using open data and services in travel planning,

taking into account the formulated requirements, the semantic operability of the services and changes in their

behavior depending on alterations in the system. In contrast to existing systems, a multimodal route planning

method for local, regional, national and international trips with public and personal transport has been de-

veloped, which uses the methods of set theory, ontology management, context management, system analysis,

privacy protection, geosearch and recommendation generation, with the ability to merge applications.

1 INTRODUCTION

In the course of analyzing the problems of road in-

frastructure development, scientists have derived the

concept of comfortable living. One of the charac-

teristics is the ability to move comfortably. It can

be concluded that a developed transport network and

the presence of convenient pedestrian infrastructure

are essential components (Adomavicius et al., 2005).

To improve the efﬁciency of urban transport planning

management, a comprehensive analysis of the exist-

ing transport network is required, which includes all

available modes of transport and the existing road in-

frastructure. The mix of modes of transport used in

a city largely depends on its size and characteristics.

For a small town, the choice of modes of transport is

usually not a particular problem. Most of the needs

of city dwellers can be met by individual transporta-

tion - on foot, by bicycle or by car. For cities with a

low level of motorization or with a large number of

inhabitants, public transport services must be devel-

oped. Thus, small cities with a high level of motor-

ization are the only place where a unimodal car-road

system supplemented by pedestrian infrastructure can

be considered adequate and efﬁcient. As the size of

the city increases, so does the need for public trans-

https://orcid.org/0000-0002-8145-405X

https://orcid.org/0000-0001-9083-7135

https://orcid.org/0000-0001-7813-3688

port, which has a signiﬁcant load capacity. At the

same time, a number of problems arise related to the

use of cars within the city, excessive consumption of

available territorial resources and negative external-

ities. Therefore, such cities should introduce a bal-

anced transport system.

The goal of this work is to build a service-oriented

infomobility system that provides users with access

to multimodal, dynamic, personalized information,

tailored to context services, to increase the mobil-

ity and ease of movement of users when planning a

trip and during travel. To provide knowledge, based

on a conceptualization that includes a description of

a set of objects and concepts, knowledge and rela-

tionships between them, based on the use of services

as sources of information and the way they are pro-

cessed. The approach is based on the following prin-

ciples arising from the requirements: openness of

data and services, use of ontologies, distributed archi-

tecture, user orientation, use of contextual informa-

tion, self-contextualization of services, real-time op-

eration, multimodality of routes, information privacy

for the user. Following these principles will satisfy the

basic requirements and provide the user with quality

services to ensure their mobility.

Simeonov, S., Gospodinova, E., Torlakov, I. and Iliev, A.

Analysis of Service-Oriented Infomobility System and Architecture Model.

DOI: 10.5220/0011902000003612

In Proceedings of the 3rd International Symposium on Automation, Information and Computing (ISAIC 2022), pages 57-62

ISBN: 978-989-758-622-4; ISSN: 2975-9463

 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

2 RESEARCH AND PROJECTS IN

THE FIELD OF

INFOMOBILITY

Navitime is a mobile navigation service available in

Japan (Arikawa et al., 2007). Navitime provides users

with route calculation and guidance services by in-

tegrating several modes of transportation: walking

routes, personal vehicles, trains, taxis and airplanes.

Navitime combines mobility information provided by

disparate data sources by converting it into four com-

mon formats. The publicly available documentation

makes no direct reference to Navitime’s adherence to

existing mobility information storage and exchange

standards.

The iTransit Integration Environment is the foun-

dation for a multi-layered intelligent system architec-

ture designed to integrate modern and traditional in-

telligent transportation vehicles (Brennan and Meier,

2007). It is based on a layered object data model. The

model contains the spatial and temporal aspects of

transport and trafﬁc data and is a uniﬁed mechanism

for querying and processing information from hetero-

geneous transport systems. It also includes global in-

formation layers containing the region’s geography

and transportation network. Data exchange between

the systems making up the iTransit architecture is

based on the use of CORBA technology and web ser-

vices.

Xiang (Xiang et al., 2007a; Xiang et al., 2007b)

describes the design principles adopted to implement

the Information System for passengers on highways

in China. The HTIS architecture is aimed at providing

an environment that enables the interaction between

distributed heterogeneous systems. The focus of con-

textual information collection is on highway monitor-

ing and control information, while end-user-focused

contextual elements (e.g., location, activity, etc.) are

not considered. The emphasis is on the integration

model of heterogeneous and distributed information

systems based on multi-level architecture, common

protocols and data formats.

Arktrans is the environment for multimodal intel-

ligent transport systems in Norway (Natvig and West-

erheim, 2007). Its aim is to create a common perspec-

tive on the transport problem area for all modes of

transport (road, sea, rail and air) in terms of standard

functions and interfaces for interaction between dif-

ferent transport systems. The operation of the system

is aimed at assisting users in planning a trip, while the

integration of the navigation service is not realized.

Lol@, the local assistant, is a prototype UMTS

guide developed as part of a joint project at the Vienna

Research Center for Telecommunications (Umlauft

et al., 2002). Lol@ is a location-based travel service

that implements SIP (Session Initiation Protocol) and

the OCA/Parlay standards. It provides tourists with

navigation services for predetermined routes. Lol@

uses different positioning methods: GPS, mobile net-

work based and manual location input by users.

The main disadvantage of the described services is

the incomplete geographical coverage. Although gen-

eral maps are available worldwide, their details and

the list of services provided vary greatly by region.

For example, CIS and Asian users do not have access

to many events on the map (only trafﬁc is shown), not

all cities have a trafﬁc schedule, or not all available

transport is covered. This situation is due to the fact

that both services use third-party services to obtain

additional information, and data processing for their

own services is carried out in a semi-automatic mode

(Verma et al., 2012).

3 A CONCEPTUAL MODEL OF A

SERVICE-ORIENTED

INFOMOBILITY SYSTEM

In order to develop an infomobility system, the fol-

lowing requirements can be deﬁned that its architec-

ture must meet: support of a heterogeneous environ-

ment of mobile devices; scalability; addition of new

elements that provide new functions and are avail-

able to a wide range of users; free interaction; in the

development of the system, ontology must be used,

which provides the following advantages: it makes

the system interoperable, reduces the development

complexity associated with the variety of technolo-

gies used, and facilitates the interaction between peo-

ple and computer systems; services must be acces-

sible through various wireless technologies such as

wireless LAN or Bluetooth.

The developed system should be focused on: the

use of open data, an open information system includ-

ing transport services, that provide information de-

pending on the user’s location (weather, attractions),

information sharing mechanisms and mechanisms to

ensure semantic interoperability. This requirement

also deﬁnes the use of a distributed architecture to

organize the cooperation of services. This approach

makes it possible to support a wide variety of devices

and information services. The addition of new func-

tionality is carried out by starting a new service, with-

out the need for a substantial redesign of the system.

It is also necessary to support the planning of routes

compatible with different vehicles and for individual

modes of transport, as well as to ensure, if necessary,

ISAIC 2022 - International Symposium on Automation, Information and Computing

a change of modes of transport during the route (Xi-

ang et al., 2007a; Yudenok and Krinkin, 2012).

User preferences can be set by creating a user pro-

ﬁle that reﬂects the basic characteristics inherent to

the user. Thanks to the use of smart spaces technol-

ogy, it is possible to deﬁne a user proﬁle in the form

of an ontology.

The system must provide real-time information

and support (trafﬁc information, timely detection of

trafﬁc jams, search for objects on a map, up-to-date

information on how objects work).

In the process of operation, the infomobility sys-

tem must take into account the current situation in or-

der to provide support options that are most suitable

for the user at a given moment. For example: recom-

mending objects on the map depending on the time (it

is better to visit the park in sunny weather and wait out

the rain in the nearest cafe, which has many positive

reviews).

Unlike the centralized architecture, the distributed

one introduces additional tasks related to ensuring the

security of users’ personal information. The advan-

tage of a centralized infrastructure is that all informa-

tion is processed in a single, self-contained environ-

ment. This allows to create a secure channel through

which all processed information will be transmitted

without leaving the environment. All users are iso-

lated from each other, which prevents unauthorized

access to their personal data. In the case of a dis-

tributed architecture, it is necessary to send and col-

lect data for several services at once, some of which

may be provided by a third party (for example, col-

lecting photos of given coordinates). In this regard, it

is necessary to further develop mechanisms to ensure

the safety of the users personal.

4 MODEL OF

SERVICE-ORIENTED

INFOMOBILITY SYSTEM

(SOIS)

As a result of the analysis of publications on infomo-

bility systems, the main needs of potential users of

the developed system were also identiﬁed. The per-

formed analysis made it possible to formulate typical

user situations for working with the system, united in

a general model of SOIS (Figure 1). Individual situa-

tions can be grouped into three large groups:

1) Route planning. The system performs route

planning, if necessary, combining several modes of

transport while following the route, taking into ac-

count the schedule of public transport and providing

the possibility of joint trips with private vehicles. This

allows to reduce the waiting time at the transfer points

and to plan the route in real time.

2) Search for objects. The system provides infor-

mation support to the user when planning a route be-

tween objects on the ground. In addition to the route,

the user is provided with context-sensitive recommen-

dations for the nearest points of interest, ranked based

on feedback from other users using collaborative ﬁl-

tering.

3) Visualization of the context. The user’s de-

vice displays information about the current situation

around him: the current time, the location of the

means of transport on the routes of public transport,

trafﬁc jams and others.

Each work situation requires the use of several ser-

vices, which allows the large task to be divided into

component parts that are executed in parallel. Context

visualization involves gathering information about the

current situation from open data sources and display-

ing the gathered information on the user’s device. It

may include: temperature and weather conditions that

provide weather information depending on the spec-

iﬁed location, object list, context update notiﬁcation,

user service, object search service, recommendation

generation service, search service for site informa-

tion, route planning service, service interaction space,

additional site information, routes to sites, site rat-

ings, current road network status, road events, loca-

tion of vehicles on public transport routes. In formal-

izing knowledge about the problem domain of the ser-

vice described by the proposed ontology, the means

of object-oriented constraint networks are used (Lev-

ashova et al., 2021). In accordance with this formal-

ism, an ontology (A) is represented in the following

form:

A = ⟨O, Q, D, R⟩, (1)

where O is the set of classes representing ob-

jects; Q is a set of class attributes in which there

are three subgroups that describe: parameters of the

physical environment P = p

, ..., p

; results of in-

formation processing and other information compo-

nents, V = v

, ..., v

; user social characteristics S =

, ..., s

, n, m, l ∈ N , where Q = P, V, S; D is a set

of domains, regions of valid attribute values; R is a

set of relations by which classes are related. Rela-

tionships describe: class taxonomy, class hierarchy,

inheritance, properties, etc. When forming the ab-

stract context of the current situation, from the sets

in the ontology, corresponding subsets are formed,

which include only those elements of the original that

are used to describe the current situation. At the

same time, in an ontological model, many services are

Analysis of Service-Oriented Infomobility System and Architecture Model

Figure 1: Situation model diagram.

added that can provide knowledge and information to

form the context and services capable of performing

certain actions with the existing knowledge and infor-

mation. Thus, an abstract context can be expressed

as:

Context

abs

(C, T

abs

) = ⟨O

abs

, D

abs

, R

abs

, W S

abs

, T

abs

⟩,

(2)

where C is the simulated situation; O

abs

⊆ O is

the set of classes needed in the ﬁrst case to simulate

situation S; Q

abs

⊆ Q is the set of attributes of class

abs

; D

abs

⊆ D is a set of domains Q

abs

; R

abs

⊆ R is

the set of constraints involved in an abstract context;

W S

abs

is a set of web services that model information

resource functions that assign values to attributes Q

abs

and can perform processing of available information,

⊆ W S, where W S is the set of registered web

services; T

abs

is the predicted model adequacy time.

In order to be able to obtain information about the

current situation involved in the system, relationships

are established between ontologies and sources indi-

cating from where the corresponding property values

of an object can be obtained. As information is re-

ceived from other services, values and attributes are

assigned to the classes of the abstract context and the

formation of the operational context. The operational

context Context

top

is a model of the current situation

described by an abstract context Context

abs

, with at-

tribute values Q

abs

. This model can be interpreted as a

problem for the constraint satisfactio. The application

context model is represented as:

Context

top

(C, t) = ⟨O

, Q

, R

, W S

, T

, δT ⟩,

(3)

where t is the current time.

For the context of the user and the multimodal

travel planning service, which are part of the infomo-

bility system, an ontology that most fully meets the

speciﬁcs of the relevant problem area has been devel-

oped. In this way, the general ontology of the system

for each situation, if necessary, can be composed of

private ontologies of services formed taking into ac-

count the current situation. In addition, a description

of the ontology used on user devices to provide infor-

mation to system services is given.

ISAIC 2022 - International Symposium on Automation, Information and Computing

5 USER CONTEXT ONTOLOGY

AND MULTIMODAL TRAVEL

PLANNING SERVICE

With the help of the user context in the infomobility

system, its main characteristics and the state of the en-

vironment are described. This information is used by

system services to provide personalized support based

on the current situation (Figure 2).

Figure 2: User Context Ontology.

It consists of two parts: information provided by

the user himself, his proﬁle (name, preferences, car

ownership, key locations on the map, etc.) and au-

tomatically collected information about the environ-

ment (current location, trafﬁc speed, weather, etc..).

User context includes attributes obtained from the

sensors of the user’s devices and from the information

provider’s services.

The problem area of the route planning service

covers tasks related to the use of map, time and per-

sonal information for route planning with different

modes of transport. In this regard, the ontology of

this service should consider objects related to the rep-

resentation of map information, vehicle schedule in-

formation, vehicle characteristics, and user character-

istics ﬁgure 3.

6 INFOMOBILITY SYSTEM

ARCHITECTURE

The architecture of the infomobility system is shown

in Figure 4. According to the developed model, a

service-oriented approach was used to build the ar-

chitecture. The sources and processors of information

and knowledge are the services installed on the user’s

devices and on the servers that ensure the operation of

Figure 3: Map Context Ontology.

the infomobility system. The interaction of services

is carried out through the ”blackboard” architectural

model, implemented based on intelligent space tech-

nology (Hu et al., 2005; Hu et al., 2008).

Figure 4: Service Oriented Architecture

7 CONCLUSIONS

In this work, the authors have proposed an approach

to building an infomobility system based on the use

of services as sources of information and knowledge.

The approach is based on the following requirements:

openness of data and services, use of ontologies, dis-

tributed architecture, user orientation, use of contex-

tual information, self-contextualization of services,

real-time operation, multimodality of routes, user in-

formation privacy. Following these principles will

satisfy the basic requirements and provide the user

with quality services to ensure their mobility. One

of the main advantages of an ontology is its reusabil-

ity. Self-contextualization of services is based on this,

i.e., the ability to self-describe and change the con-

text, which can be changed by expanding the ontol-

Analysis of Service-Oriented Infomobility System and Architecture Model

ogy by including new concepts in it or narrowed by

excluding unnecessary ones. For each service, an on-

tology is deﬁned that most fully describes the relevant

subject area. Services can change the knowledge de-

scription model to better ﬁt the current situation, al-

lowing them to respond adequately to its change. The

method used to build the core services of the infomo-

bility system is to be presented in the future.

ACKNOWLEDGEMENTS

This research was funded by the European Regional

Development Fund through the Operational Pro-

gram “Science and Education for Smart Growth” un-

der contract UNITe No BG05M2OP001–1.001–0004

(2018–2023).

REFERENCES

Adomavicius, G., Sankaranarayanan, R., Sen, S., and

Tuzhilin, A. (2005). Incorporating contextual infor-

mation in recommender systems using a multidimen-

sional approach. ACM Transactions on Information

Systems, 23(1):103–145.

Arikawa, M., Konomi, S., and Ohnishi, K. (2007). Nav-

itime: Supporting pedestrian navigation in the real

world. IEEE Pervasive Computing, 6(3):21–29.

Brennan, S. and Meier, R. (2007). STIS: Smart travel plan-

ning across multiple modes of transportation. In 2007

IEEE Intelligent Transportation Systems Conference.

IEEE.

Hu, W., Jian, N., Qu, Y., and Wang, Y. (2005). Gmo: A

graph matching for ontologies. volume 156.

Hu, W., Qu, Y., and Cheng, G. (2008). Matching large

ontologies: A divide-and-conquer approach. Data

Knowl. Eng., 67:140–160.

Levashova, T. V., Smirnov, A. V., Pashkin, M. P., and Pono-

marev, A. V. (2021). Conceptual framework of intelli-

gent decision support based on user digital life traces

and ontology-based user categorisation. Journal of

Physics: Conference Series, 1801(1):012005.

Natvig, M. and Westerheim, H. (2007). National multi-

modal travel information – a strategy based on stake-

holder involvement and intelligent transportation sys-

tem architecture. IET Intelligent Transport Systems,

1(2):102.

Umlauft, M., Pospischil, G., Niklfeld, G., and Michlmayr,

E. (2002). Lol@, a mobile tourist guide for umts. J.

Inf. Technol. Tour., 5:151–164.

Verma, S., Kumar, S., and Singh, M. (2012). Comparative

analysis of role base and attribute base access control

model in semantic web. International Journal of Com-

puter Applications, 46:1–6.

Xiang, Q., Ma, Y., Lu, J., Xie, J., and Sha, H. (2007a).

Framework design of highway traveller information

system of jiangsu province in china. IET Intelligent

Transport Systems, 1(2):110.

Xiang, Q., Ma, Y., Lu, J., Xie, J., and Sha, H. (2007b).

Framework design of highway traveller information

system of jiangsu province in china. IET Intelligent

Transport Systems, 1(2):110.

Yudenok, K. and Krinkin, K. (2012). Distributed service

environment (smart spaces) security model develop-

ment. In 2012 12th Conference of Open Innovations

Association (FRUCT). IEEE.

ISAIC 2022 - International Symposium on Automation, Information and Computing