| Title |
Swarm Intelligence and IoT-Based Smart Cities: A Review |
| ID_Doc |
44256 |
| Authors |
Zedadra, O; Guerrieri, A; Jouandeau, N; Spezzano, G; Seridi, H; Fortino, G |
| Title |
Swarm Intelligence and IoT-Based Smart Cities: A Review |
| Year |
2019 |
| Published |
|
| DOI |
10.1007/978-3-319-96550-5_8 |
| 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. |
| Author Keywords |
Swarm intelligence; Swarm intelligence-based algorithms; IoT Smart cities |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Book Citation Index – Science (BKCI-S) |
| EID |
WOS:000487747000009 |
| WoS Category |
Computer Science, Hardware & Architecture; Computer Science, Information Systems; Computer Science, Interdisciplinary Applications |
| Research Area |
Computer Science |
| PDF |
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