=Paper=
{{Paper
|id=Vol-3191/paper21
|storemode=property
|title=Intelligent Urban Environment Lab Infrastructure Design (short paper)
|pdfUrl=https://ceur-ws.org/Vol-3191/paper21.pdf
|volume=Vol-3191
|authors=Toma Tomov,Ioannis Patias,Vasil Georgiev
|dblpUrl=https://dblp.org/rec/conf/isgt2/TomovPG22
}}
==Intelligent Urban Environment Lab Infrastructure Design (short paper)==
https://ceur-ws.org/Vol-3191/paper21.pdf
Intelligent Urban Environment Lab Infrastructure
Design
Toma Tomov 1, Ioannis Patias 1 and Vasil Georgiev 1
1
University of Sofia “St. Kliment Ohridski“, Faculty of Mathematics and Informatics, 5
James Bourchier blvd., Sofia, 1164, Bulgaria
Abstract
MIRACle (Mechatronics, Innovation, Robotics, Automation, Clean
technologies) project refers to the Establishment and development of a
Center for Competence in Mechatronics and Clean Technologies. The
specific activities for the Laboratory Intelligent Urban Environment
require the deployment of a modern infrastructure. The main design goal
was that the infrastructure should support both real-time and in batch data,
various database management systems, and sensor types. In this paper, the
focus is on the infrastructure design. In this paper, we present the generic
infrastructure model that is under development in the IUE-Lab as planned
to cover the related activities and use cases.
Keywords
Intelligent public environment, intelligent home environment, intelligent
personal assistant, research and development, infrastructure
1. Introduction
Given the importance of infrastructure for the success of any newly estab-
lished laboratory, we aim to adopt existing best practices, maximize the potential,
and achieve innovation at scale. The main idea is to start the deployment of the
infrastructure based on a clear strategy. Thus, any efforts will not stop to small
pilots, and fail to further scale up and achieve significant impact. Efforts will be
invested to design pilots and other projects with an end-to-end approach, and
incorporation of all the necessary elements for successful implementation. In ad-
dition, of course in this direction our relations with the business play an important
role. [1, 3]
Now days, data driven research and development (R&D) needs to both take
advantage of data, but also try and connect cross-sector players, and opportuni-
ties. Vertical development in a sector is no longer enough; now R&D labs must be
Information Systems & Grid Technologies: Fifteenth International Conference ISGT’2022, May 27–28, 2022, Sofia, Bulgaria
EMAIL: tomat@uni-sofia.bg (T. Tomov); patias@fmi.uni-sofia.bg (I. Patias); v_georgiev@fmi.uni-sofia.bg (V. Georgiev)
ORCID: 0000-0002-6307-8409 (T. Tomov); 0000-0003-1355-7433 (I. Patias); 0000-0003-3291-1274 (V. Georgiev)
© 2022 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR Workshop Proceedings (CEUR-WS.org)
cross-sector. Development of expertise on specific functions, and expanding this
expertise over and above specific sector expertise, is the key question.
MIRACle (Mechatronics, Innovation, Robotics, Automation, Clean technol-
ogies) project refers to the Establishment and development of a Center of Com-
petence (CoC) in Mechatronics and Clean Technologies. It is a research project
and a joint effort of advanced institutes in Bulgaria. The Laboratory Intelligent
Urban Environment (IUE-Lab) under MIRACLe project will integrate its activi-
ties in three different application scenarios in the areas: Intelligent Home Envi-
ronment (IHE), Intelligent Public Environment (IPE), and Intelligent Personal
Assistant (IPA). For the purpose, IUE- Lab requires the deployment of a modern
infrastructure.
With all this in mind, we will try to explain how to develop best practices and
translate it into impact. In this paper, we will discuss how to design, and develop
the right infrastructure for a successful CoC. The specifics of IUE-Lab infrastruc-
ture design are discussed. The main design goal was that the infrastructure should
support both real-time and batch data collection and storage, in various database
management systems, and from different sensor types. [4, 5, 6, 7]
2. Data flow
In the frame of IUE-Lab activities under MIRACLe project, we aim in de-
veloping interactions both cross-platform, and cross networks, and include in all
those different smart objects. All those should take place in dynamic, scalable,
decentralized and intelligent environments of Internet of Things (IoT) elements.
Such elements are usable and highly demanded by many sectors including, pub-
lic sector, home applications, and by quite specific needs, including, vulnerable
groups, supported by autonomous interacting intelligent systems and even net-
works of smart, intelligent, embedded systems [8, 9].
In this direction, the main objectives of the data flow requirements are:
• diversity of data sources;
• secure storage, and testing platforms, and applications;
• compliant to privacy regulations data analysis;
• provision of trustworthy Artificial Intelligence (AI) and machine learning
(ML) solutions.
This infrastructure, in terms both of hardware and software, should be able
to support the data flow from observational and real-time data collection, storage,
analysis, and their further use in applications using AI&ML (see Figure 1).
229
Figure 1: IUE-Lab activities under the MIRACle project
3. Lab activities – use cases
One key limitation of modern autonomous and intelligent systems is that
their functionalities are designed and delivered independently. No matter most of
the devices are connected to the Internet, they do not coordinate their activities.
Their integration is possible, there are IoT platforms, but most of the autonomous
and intelligent systems operate in isolation. This is a great loss of the opportunity
for the development and the deployment of innovative functionalities and the de-
livery of new advanced services. The barriers and limitations of such integration
of IoT elements and devices with smart autonomous intelligent systems such as
robots is the overall focus of IUE-Lab. [10]
IUE-Lab will develop four main activities, or use cases covering a wide
range of applications (see Figure 2), namely:
• iVille – mobile (incl. flight) autonomous hub of data and control signals
for the urban environment;
• iÉcole – mobile autonomous hub of data and control signals for pub-
lic structured environment – for example in education and administrative
services. Within the IUE-Lab, it will be prototyped for the purposes of the
educational environment;
• iVac – mobile autonomous hub of data and control signals for the home
environment; and
• iChien – an electronic guide for blind people, based on a smartphone and
integration into the IUE.
230
Figure 2: IUE-Lab activities under the MIRACle project
3.1. Ville
The mobile autonomous data and control signals hub for integrated urban
environment can be used to cover the respective needs. According to the Inter-
national Federation of Robotics (IFR) services robots related to integrated urban
environment could be used for the delivery of services related to (see Figure 3)
[2, 11]:
• Professional cleaning;
• Floor cleaning;
• Window and wall cleaning (incl. wall climbing robots);
• Tank, tube and pipe cleaning;
• Hull cleaning (aircraft vehicles etc.);
• Other cleaning tasks;
• Inspection and maintenance systems;
• Facilities, plants;
• Tank, tubes, pipes and sewers;
• Other inspection and maintenance systems;
• Construction and demolition;
• Nuclear demolition & dismantling;
231
• Building construction;
• Robots for heavy/civil construction;
• Other construction and demolition systems.
Figure 3: Ville services
3.2. iÉcole
In the same direction the IFR services robots related to public, and other kind
of administrative environment could be used for the delivery of services related
to (see Figure 4) [2, 11]:
• Robot companions/assistants/humanoids;
• Floor cleaning;
• Window and wall cleaning (incl. wall climbing robots);
• Multimedia/remote presence;
• Education and research.
Figure 4: iÉcole services
232
3.3. iVac
The IFR advices that services robots related to home environment could be
used for the delivery of services related to (see Figure 5) [2, 11]:
• Robot companions/assistants/humanoids;
• Vacuuming, floor cleaning;
• Lawn-mowing;
• Pool cleaning;
• Window cleaning;
• Home security & surveillance.
Figure 5: iVac services
3.4. iChien
Finally, the IFR proposes services robots related to the support of people
with disabilities, and as an electronic guide for the blind people, based on a smart-
phone and integration into IUE could be used for the delivery of services related
to (see Figure 6) [2, 11]:
• Robotized wheelchairs;
• Personal aids and assistive devices;
• Other assistance functions;
• Home security & surveillance.
233
Figure 6: iChien services
4. Design specifics and challenges
Robots performance related data generated by autonomous and intelligent
systems is of interest to the researchers from various fields and currently the
unification of the access to such data remains a challenge from the scientific com-
munity [3]. Consequently, an important issue is whether the data generated in the
IUE lab should be provided for use, for example, in research. In such case, it must
be clear for which purposes the research community use the data generated in the
lab, meaning respective procedures and tools must be in place.
As second challenge was identified whether the participating researchers,
generating data will be willing to share their data with other participants from
the research community. The development of the infrastructure must have proce-
dures and tools in place for such dissemination of data also.
Third challenge appears to be the quality of the generated data. This cov-
ers from one side the question of whether the data are appropriate to be used for
the initial purpose, but also whether the design of the data collection model is
reliable, meaning whether it covers the requirements described in the data flow
model in the previous sections.
However, apart the technological limitations there is also a business related
limitation. A sustainable business model must also be part of the infrastructure
design aspects. The sustainability of the IUE lab is a key component and in terms
of design limitations poses the idea of fragmentation avoidance. All the equip-
ment, data, knowhow and people both at individual and research, and policy en-
vironment should be considered as one part, and provided as such.
Finally, the generation and further usage of any data by the robots and the
autonomous intelligent systems in the IUE lab involve a wide range of stakehold-
ers. Thus, we need to develop a platform to cover the concrete needs of each
stakeholder together with the coordination between all the stakeholders.
234
5. Conclusions
In this paper, the main design goals for the IUE-Lab were discussed. It was
reported the IUE-Lab data flow and management system model. The proposed
data management model serves the needs of MIRACle project: Mechatronics,
Innovation, Robotics, Automation, and Clean technologies – Establishment and
development of a Center for Competence in Mechatronics and Clean Technolo-
gies, and more specific for the Laboratory Intelligent Urban Environment. The
design goal that the underlying infrastructure should have was described. Based
on a generic infrastructure model that is under development the specifics of the
IUE-Lab activities and use cases are met.
6. Acknowledgements
This paper is prepared with the support of MIRACle: Mechatronics, Innova-
tion, Robotics, Automation, Clean technologies – Establishment and develop-
ment of a Center for Competence in Mechatronics and Clean Technologies –
Laboratory Intelligent Urban Environment, funded by the Operational Program
Science and Education for smart growth 2014-2020, Project BG 05M2OP001-
1.002-0011.
7. References
[1] Stanev, I. and Koleva, M. (2017). ”Method For Information Systems Auto-
mated Programming” (2017). MCIS 2017 Proceedings. 9. http://aisel.ais-
net.org/mcis2017/9, last accessed 2021/18/02.
[2] International Federation of Robotics (2015a) Definition of service robots,
URL: http://www.ifr.org/service-robots/. Accessed 17 Feb 2015.
[3] Pisano, G. (2015). “You Need an Innovation Strategy”, HBR, Innovation,
https://hbr.org/2015/06/you-need-an-innovation-strategy, last accessed
2021/31/02.
[4] Ristevski, B., Savoska S., Blazheska-Tabakovska, N. (2020). “Opportuni-
ties for Big Data Analytics in Healthcare Information Systems Develop-
ment for Decision Support”. Proc. of ISGT 2020, Sofia, Bulgaria, May
29-30, 2020, online CEUR-WS.org/Vol-2656/paper4.pdf, last accessed
2021/08/02.
[5] Leventi, N., Velikov, S., and Yanakieva, A. (2020). “Evidence-Based Med-
icine and Computer Skills of Medical Profes- sionals in Bulgaria”, Pro-
ceedings of the Information Systems and Grid Technologies, ISGT 2020,
148–158, 2020, http://ceur-ws.org/Vol-2656/paper6.pdf, last accessed
2021/10/02.
235
[6] Leventi, N., Yanakieva, A., Pilot survey of the medical professionals in
Bulgaria on integration of EBM training in medical education curriculum.
In: Proc. of CBU International Conference on Innovations in Science and
Education, pp. 922–927, Prague, Czech Republic (2018).
[7] Leventi, N., Vodenitcharova, A., & Popova, K. (2020). “Ethical aspects of
the use of innovative information technologies in clinical trials”. Proceed-
ings of CBU in Medicine and Pharmacy, 1, 66–70. https://doi.org/10.12955/
pmp.v1.100, last accessed 2021/11/02.
[8] Papapostolu, T. μσADL: An Architecture Description Language for Mi-
croServices. In: Human Interaction and Emerging Technologies. IHIET
2019. Advances in Intelligent Systems and Computing, vol 1018. Springer,
Cham (2020).
[9] Arnaoudova, K., and Nisheva, M. (2020). “Document Understanding:
Problems and Technological Solutions”. In: Proceedings of the Information
Systems and Grid Technologies – ISGT 2020, Sofia, Bulgaria, 148–158,
2020, http://ceur-ws.org/Vol-2656/paper15.pdf, last accessed 2021/11/02
[10] Velikov, S. “Analytical Modeling”, MU-Sofia, FPH, Sofia. (2018).
[11] [11] International Organization for Standardization, Robotics – Ap-
plication of ISO 8373:2021, 2021, URL: https://www.iso.org/obp/
ui/#iso:std:75539:en.
236