Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Erschienen in:
A Social and Pervasive IoT Platform for Developing Smart Environments Kapitel lesen Erstes Kapitel lesen

2019 | OriginalPaper | Buchkapitel

Swarm Intelligence and IoT-Based Smart Cities: A Review

verfasst von : Ouarda Zedadra, Antonio Guerrieri, Nicolas Jouandeau, Giandomenico Spezzano, Hamid Seridi, Giancarlo Fortino

Erschienen in: The Internet of Things for Smart Urban Ecosystems

Verlag: Springer International Publishing

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Smart cities are complex and large distributed systems characterized by their heterogeneity, security, and reliability challenges. In addition, they are required to take into account several scalability, efficiency, safety, real-time responses, and smartness issues. All of this means that building smart city applications is extremely complex. Swarm Intelligence is a very promising paradigm to deal with such complex and dynamic systems. It presents robust, scalable and self-organized behaviors to deal with dynamic and fast changing systems. The intelligence of cities can be modeled as a swarm of digital telecommunication networks (the nerves), ubiquitously embedded intelligence (the brains), sensors and tags (the sensory organs), and software (the knowledge and cognitive competence). In this chapter, swarm intelligence-based algorithms and existing swarm intelligence-based smart city solutions will be analyzed. Moreover, a swarm-based framework for smart cities will be presented. Then, a set of trends on how to use swarm intelligence in smart cities, in order to make them flexible and scalable, will be investigated.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Vorheriges Kapitel Aggregation Techniques for the Internet of Things: An Overview
Nächstes Kapitel Cost Saving and Ancillary Service Provisioning in Green Mobile Networks
Literatur
1.
J. Kennedy, Swarm intelligence, in Handbook of Nature-Inspired and Innovative Computing (Kluwer Academic Publishers, Boston, 2001), pp. 187–219
2.
R.S. Parpinelli, H.S. Lopes, New inspirations in swarm intelligence: a survey. Int. J. Bio-Inspired Comput. 3(1), 1 (2011)CrossRef
3.
S. Garnier, J. Gautrais, G. Theraulaz, The biological principles of swarm intelligence. Swarm Intell. 1(1), 3–31 (2007)CrossRef
4.
V. Angelakis, E. Tragos, H.C. Pöhls, A. Kapovits, Designing, Developing, and Facilitating Smart Cities (Springer International Publishing, Cham, 2017)CrossRef
5.
G. Garofalo, A. Giordano, P. Piro, G. Spezzano, A. Vinci, A distributed real-time approach for mitigating CSO and flooding in urban drainage systems. J. Netw. Comput. Appl. 78, 30–42 (2017)CrossRef
6.
O. Zedadra, C. Savaglio, N. Jouandeua, A. Guerrieri, H. Seridi, G. Fortino, Towards a reference architecture for swarm intelligence-based internet of things, in the Proc. of the 10th International Conference on Internet and Distributed Computing Systems (IDCS 2017) (Springer, December, Fiji, 2017), pp. 11–13
7.
M. Dorigo, M. Birattari, T. Stutzle, Ant colony optimization IEEE Computational Intelligence Magazine 1(4), 28–39 (2006)
8.
F. Cicirelli, A. Forestiero, A. Giordano, C. Mastroianni, Transparent and efficient parallelization of swarm algorithms. ACM Trans. Auton. Adapt. Syst. 11(2), 14:1–14:26 (2016)
9.
D. Karaboga, An idea based on honey bee swarm for numerical optimization. Technical Report-tr06, Erciyes University, Engineering Faculty, Computer Engineering Department (2005)
10.
H.A. Abbass, MBO: marriage in honey bees optimization-a Haplometrosis polygynous swarming approach, in Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No. 01TH8546), vol. 1 (IEEE, 2000), pp. 207–214
11.
X.S. Yang, X. He, Firefly algorithm: recent advances and applications. Int. J. Swarm Intell. 1(1), 36–50 (2013)
12.
K.N. Krishnanand, D. Ghose, Detection of multiple source locations using a glowworm metaphor with applications to collective robotics, in Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005 (SIS 2005), vol. 2005 (IEEE, 2005), pp. 84–91
13.
K.M. Passino, Biomimicry of bacterial foraging for distributed optimization and control. IEEE Control Syst. Mag. 22(3), 52–67 (2002)
14.
R.C. Eberhart, J. Kennedy, Particle swarm optimization, in Proceedings of the International Conference on Neural Networks, Piscataway, vol. 1000, pp. 1942–1948 (1995)
15.
X.S. Yang, S. Deb, Engineering optimisation by cuckoo search. Int. J. Math. Model. Numer. Optim. 1(4), 330 (2010)
16.
X.-S. Yang, A new metaheuristic bat-inspired algorithm. Stud. Comput. Intell. 284, 65–74 (2010)MATH
17.
M. Eusuff, K. Lansey, F. Pasha, Shuffled frog-leaping algorithm: a memetic meta-heuristic for discrete optimization. Eng. Optim. 38(2), 129–154 (2006)MathSciNetCrossRef
18.
X. Li, J.-x. Qian, Studies on artificial fish swarm optimization algorithm based on decomposition and coordination techniques. J. Circuit Syst. 1, 1–6 (2003)
19.
C. Liu, X. Yan, C. Liu, W. Hua, The wolf colony algorithm and its application. Chin. J. Electron. 20(2), 212–216 (2011)
20.
S.C. Chu, P.W. Tsai, Computational intelligence based on the behavior of cats. Int. J. Innov. Comput. Inf. Control 3(1), 163–173 (2007)
21.
L.G. Anthopoulos, Understanding the smart city domain: a literature review, in Transforming City Governments for Successful Smart Cities (Springer, 2015), pp. 9–21
22.
C. Harrison, B. Eckman, R. Hamilton, P. Hartswick, J. Kalagnanam, J. Paraszczak, P. Williams, Foundations for smarter cities. IBM J. Res. Dev. 54(4), 1–16 (2010)CrossRef
23.
D. Toppeta, The smart city vision: how innovation and ICT can build smart, “livable”, sustainable cities. Innov. Knowl. Found. 5, 1–9 (2010)
24.
A.C. Lundin, A.G. Ozkil, J. Schuldt-Jensen, Smart cities: a case study in waste monitoring and management. in Proceedings of the 50th Hawaii International Conference on System Sciences (2017)
25.
A. Picon, Smart Cities: A Spatialised Intelligence (Wiley, 2015)
26.
A. Medvedev, P. Fedchenkov, A. Zaslavsky, T. Anagnostopoulos, S. Khoruzhnikov, Waste management as an IoT-enabled service in smart cities, in Conference on Smart Spaces (Springer, 2015), pp. 104–115
27.
J.M. Gutierrez, M. Jensen, M. Henius, T. Riaz, Smart waste collection system based on location intelligence. Procedia Comput. Sci. 61, 120–127 (2015)CrossRef
28.
T. Anagnostopoulos, A. Zaslavsky, A. Medvedev, Robust waste collection exploiting cost efficiency of loT potentiality in smart cities, in 2015 International Conference on Recent Advances in Internet of Things (RIoT), pp. 7–9, Apr 2015
29.
T. Anagnostopoulos, K. Kolomvatsos, C. Anagnostopoulos, A. Zaslavsky, S. Hadjiefthymiades, Assessing dynamic models for high priority waste collection in smart cities. J. Syst. Softw. 110, 178–192 (2015)CrossRef
30.
A. Medvedev, A. Zaslavsky, M. Indrawan-Santiago, P.D. Haghighi, A. Hassani, Storing and indexing IoT context for smart city applications, in Internet of Things, Smart Spaces, and Next Generation Networks and Systems (Springer, 2016), pp. 115–128
31.
M. Aazam, M. St-Hilaire, C.-H. Lung, I. Lambadaris, Cloud-based smart waste management for smart cities, in 2016 IEEE 21st International Workshop on Computer Aided Modelling and Design of Communication Links and Networks (CAMAD) (IEEE, 2016), pp. 188–193
32.
S. Lokuliyana, J.A.D.C. Anuradha Jayakody, L. Rupasinghe, S. Kandawala, IGOE IoT framework for waste collection optimization, in National Conference on Technology and Management (NCTM) (IEEE, 2017), pp. 12–16
33.
Y. Simmhan, S. Aman, A. Kumbhare, R. Liu, S. Stevens, Q. Zhou, V. Prasanna, Cloud-based software platform for big data analytics in smart grids. Comput. Sci. Eng. 15(4), 38–47 (2013)CrossRef
34.
L.A. Hurtado, P.H. Nguyen, W.L. Kling, Smart grid and smart building inter-operation using agent-based particle swarm optimization. Sustain. Energy Grids Netw. 2, 32–40 (2015)
35.
J. Kane, B. Tang, Z. Chen, J. Yan, T. Wei, H. He, Q. Yang, Reflex-tree: a biologically inspired parallel architecture for future smart cities, in 2015 44th International Conference on Parallel Processing (IEEE, 2015), pp. 360–369
36.
E. Asimakopoulou, N. Bessis, Buildings and crowds: forming smart cities for more effective disaster management, in 2011 Fifth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing (IEEE, 2011), pp. 229–234
37.
B. Molina, C.E. Palau, G. Fortino, A. Guerrieri, C. Savaglio, Empowering smart cities through interoperable sensor network enablers, in 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC), vol. 2014-Janua. (IEEE, 2014), pp. 7–12
38.
A. Guerrieri, G. Fortino, A. Ruzzelli, G.M.P. O’Hare, A WSN-based building management framework to support energy-saving applications in buildings, in Advancements in Distributed Computing and Internet Technologies: Trends and Issues (IGI Global, 2012), pp. 258–273
39.
G. Fortino, R. Gravina, A. Guerrieri, G. Di Fatta, Engineering large-scale body area networks applications, in Proceedings of the 8th International Conference on Body Area Networks (ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering), 2013), pp. 363–369
40.
J. Cano, C.E. Jimenez, S. Zoughbi, A smart city model based on citizen-sensors, in 2015 IEEE First International Smart Cities Conference (ISC2), vol. 81 (IEEE, 2015), pp. 1–2
41.
A. Zanella, N. Bui, A. Castellani, L. Vangelista, M. Zorzi, Internet of Things for smart cities. IEEE Internet of Things J. 1(1), 22–32 (2014)
42.
M.S. Jamil, M.A. Jamil, A. Mazhar, A. Ikram, A. Ahmed, U. Munawar, Smart environment monitoring system by employing wireless sensor networks on vehicles for pollution free smart cities. Procedia Eng. 107, 480–484 (2015)
43.
V.C.C. Roza, O.A. Postolache, Citizen emotion analysis in smart city, in 2016 7th International Conference on Information, Intelligence, Systems & Applications (IISA) (IEEE, 2016), pp. 1–6
44.
J. Shah, B. Mishra, IoT enabled environmental monitoring system for smart cities, in 2016 International Conference on Internet of Things and Applications (IOTA) (IEEE, 2016), pp. 383–388
45.
A. Giordano, G. Spezzano, A. Vinci, Smart agents and fog computing for smart city applications, in International Conference on Smart Cities (2016, June), pp. 137-146
46.
S. Kumar, S.K. Singh, Monitoring of pet animal in smart cities using animal biometrics. Future Gener. Comput. Syst. (2016)
47.
F. Cicirelli, A. Guerrieri, G. Spezzano, A. Vinci, An edge-based platform for dynamic smart city applications. Future Gener. Comput. Syst. 76, 106–118 (2017)CrossRef
48.
F. Cicirelli, A. Guerrieri, G. Spezzano, A. Vinci, O. Briante, G. Ruggeri, iSapiens: a platform for social and pervasive smart environments, in 2016 IEEE 3rd World Forum on Internet of Things (WF-IoT) (IEEE, 2016), pp. 365–370
49.
F. Cicirelli, A. Guerrieri, G. Spezzano, A. Vinci, O. Briante, A. Iera, G. Ruggeri, Edge computing and social internet of things for large-scale smart environments development. IEEE Internet of Things J. 4662(c), 1–1 (2017)
50.
F. Cicirelli, G. Fortino, A. Guerrieri, G. Spezzano, A. Vinci, Metamodeling of smart environments: from design to implementation. Adv. Eng. Inform. 33, 274–284 (2017)CrossRef
51.
F. Cicirelli, G. Fortino, A. Mercuri, A. Guerrieri, G. Spezzano, A. Vinci, Exploiting the sem framework for modeling smart cities, in International Conference on Internet and Distributed Computing Systems (Springer, 2017)
52.
M. Alhussein, Monitoring Parkinson’s disease in smart cities. IEEE Access 5(c), 19835–19841 (2017)
53.
J.-P. Calbimonte, J. Eberle, K. Aberer, Toward self-monitoring smart cities: the OpenSense2 approach. Informatik-Spektrum 40(1), 75–87 (2017)CrossRef
54.
O. Cosido, C. Loucera, A. Iglesias, Automatic calculation of bicycle routes by combining meta-heuristics and GIS techniques within the framework of smart cities, in 2013 International Conference on New Concepts in Smart Cities: Fostering Public and Private Alliances (SmartMILE) (IEEE, 2013), pp. 1–6
55.
M. Patrascu, M. Dragoicea, A. Ion, Emergent intelligence in agents: a scalable architecture for smart cities, in 2014 18th International Conference on System Theory, Control and Computing (ICSTCC) (IEEE, 2014), pp. 181–186
56.
D.H. Stolfi, E. Alba, Red Swarm: reducing travel times in smart cities by using bio-inspired algorithms. Appl. Soft Comput. 24, 181–195 (2014)CrossRef
57.
D.H. Stolfi, E. Alba, Eco-friendly reduction of travel times in European smart cities, in Proceedings of the 2014 Conference on Genetic and Evolutionary Computation (GECCO’14) (ACM Press, New York, USA, 2014), pp. 1207–1214
58.
P. Chamoso, F. De Prieta, F. De Paz, J.M. Corchado, Swarm agent-based architecture suitable for internet of things and smartcities, in Advances in Intelligent Systems and Computing, vol. 373 (Springer International Publishing, Cham, 2015)
59.
P. Chamoso, F. De La Prieta, Swarm-based smart city platform: a traffic application. ADCAIJ: Adv. Distrib. Comput. Artif. Intell. J. 4(2), 89 (2015)
60.
Z. Li, M. Shahidehpour, S. Bahramirad, A. Khodaei, Optimizing traffic signal settings in smart cities. IEEE Trans. Smart Grid 8(5), 2382–2393 (2017)
61.
J. Liu, X. Yu, Z. Xu, K.-K.R. Choo, L. Hong, X. Cui, A cloud-based taxi trace mining framework for smart city. Softw. Pract. Exp. 47(8), 1081–1094 (2017)
62.
G.-J. Horng, The adaptive recommendation mechanism for distributed parking service in smart city. Wirel. Pers. Commun. 80(1), 395–413 (2015)
63.
L. Baroffio, L. Bondi, M. Cesana, A.E. Redondi, M. Tagliasacchi, A visual sensor network for parking lot occupancy detection in smart cities, in 2015 IEEE 2nd World Forum on Internet of Things (WF-IoT) (IEEE, 2015), pp. 745–750
64.
M. Amin, R. Kawaguchi, N. Shirmohammad, M. Sato, BlueParking, in Proceedings of the Second International Conference on IoT in Urban Space - Urb-IoT ’16, vol. 24–25-May (ACM Press, New York, New York, USA, 2016), pp. 86–88
65.
A. Yavari, P.P. Jayaraman, D. Georgakopoulos, Contextualised service delivery in the internet of things: parking recommender for smart cities, in 2016 IEEE 3rd World Forum on Internet of Things (WF-IoT) (IEEE, 2016), pp. 454–459
66.
R. Grodi, D.B. Rawat, F. Rios-Gutierrez, Smart parking: parking occupancy monitoring and visualization system for smart cities, in SoutheastCon 2016 (IEEE, 2016), pp. 1–5
67.
I. Aydin, M. Karakose, E. Karakose, A navigation and reservation based smart parking platform using genetic optimization for smart cities, in 2017 5th International Istanbul Smart Grid and Cities Congress and Fair (ICSG) (IEEE, 2017), pp. 120–124
68.
H. Chourabi, T. Nam, S. Walker, J.R. Gil-Garcia, S. Mellouli, K. Nahon, T.A. Pardo, H.J. Scholl, Understanding smart cities: an integrative framework, in 2012 45th Hawaii International Conference on System Sciences (IEEE, 2012), pp. 2289–2297
69.
N. Bicocchi, A. Cecaj, D. Fontana, M. Mamei, A. Sassi, F. Zambonelli, Collective awareness for Human-ICT collaboration in smart cities, in 22nd IEEE International WETICE Conference (WETICE, 2013, June), pp. 3-8, IEEE
70.
L. Sanchez, L. Muñoz, J.A. Galache, P. Sotres, J.R. Santana, V. Gutierrez, R. Ramdhany, A. Gluhak, S. Krco, E. Theodoridis, D. Pfisterer, SmartSantander: IoT experimentation over a smart city testbed. Comput. Netw. 61, 217–238 (2014)
71.
F. Zambonelli, Engineering self-organizing urban superorganisms. Eng. Appl. Artif. Intell. 41, 325–332 (2015)
72.
J. Muvuna, T. Boutaleb, S.B. Mickovski, K.J. Baker, Systems engineering approach to design and modelling of smart cities, in International Conference for Students on Applied Engineering (ICSAE) (IEEE, 2016), 437–440
73.
N. Mohamed, J. Al-Jaroodi, I. Jawhar, S. Lazarova-Molnar, S. Mahmoud, SmartCityWare: a service-oriented middleware for cloud and fog enabled smart city services. IEEE Access, 5(c), 17576–17588 (2017)
74.
C.A. Kamienski, F.F. Borelli, G.O. Biondi, I. Pinheiro, I.D. Zyrianoff, M. Jentsch, Context design and tracking for IoT-based energy management in smart cities. IEEE Internet of Things J. 5(2), 687–695 (2018)
75.
L. van Zoonen, Privacy concerns in smart cities. Gov. Inf. Q. 33(3), 472–480 (2016)
76.
Y. Li, W. Dai, Z. Ming, M. Qiu, Privacy protection for preventing data over-collection in smart city. IEEE Trans. Comput. 65(5), 1339–1350 (2016)
77.
G. Fortino, D. Grimaldi, L. Nigro, Multicast control of mobile measurement systems. IEEE Trans. Instrum. Meas. 47(5), 1149–1154 (1998)
78.
G. Fortino, W. Russo, Using P2P, GRID and agent technologies for the development of content distribution networks. Future Gener. Comput. Syst. 24(3), 180–190 (2008)
79.
G. Aloi, G. Caliciuri, G. Fortino, R. Gravina, P. Pace, W. Russo, C. Savaglio, Enabling IoT interoperability through opportunistic smartphone-based mobile gateways. J. Netw. Comput. Appl. 81, 74–84 (2017)
80.
G. Fortino, A. Garro, W. Russo, An integrated approach for the development and validation of multi-agent systems. Int. J. Comput. Syst. Sci. Eng. 20(4), 259–271 (2005)
81.
F. Aiello, G. Fortino, A. Guerrieri, R. Gravina, Maps: a mobile agent platform for WSNs based on java sun spots, in Proceedings of ATSM (2009)
Metadaten
Titel
Swarm Intelligence and IoT-Based Smart Cities: A Review
verfasst von
Ouarda Zedadra
Antonio Guerrieri
Nicolas Jouandeau
Giandomenico Spezzano
Hamid Seridi
Giancarlo Fortino
Copyright-Jahr
2019
Buch
The Internet of Things for Smart Urban Ecosystems

Print ISBN: 978-3-319-96549-9

Electronic ISBN: 978-3-319-96550-5

Copyright-Jahr: 2019

DOI
https://doi.org/10.1007/978-3-319-96550-5_8

Neuer Inhalt

    Bildnachweise