| Title | Framework for Smart City Applications Based on Participatory Sensing |
|---|---|
| ID_Doc | 45388 |
| Authors | Szabó, R; Farkas, K; Ispány, M; Benczúr, AA; Bátfai, N; Jeszenszky, P; Laki, S; Vágner, A; Kollár, L; Sidló, C; Besenczi, R; Smajda, M; Kövér, G; Szincsák, T; Kádek, T; Kósa, M; Adamkó, A; Lendák, I; Wiandt, B; Tomás, T; Nagy, AZ; Fehér, G |
| Title | Framework for Smart City Applications Based on Participatory Sensing |
| Year | 2013 |
| Published | |
| Abstract | Smart cities offer services to their inhabitants which make everyday life easier beyond providing a feedback channel to the city administration. For instance, a live timetable service for public transportation or real-time traffic jam notification can increase the efficiency of travel planning substantially. Traditionally, the implementation of these smart city services require the deployment of some costly sensing and tracking infrastructure. As an alternative, the crowd of inhabitants can be involved in data collection via their mobile devices. This emerging paradigm is called mobile crowd-sensing or participatory sensing. In this paper, we present our generic framework built upon XMPP (Extensible Messaging and Presence Protocol) for mobile participatory sensing based smart city applications. After giving a short description of this framework we show three use-case smart city application scenarios, namely a live transit feed service, a soccer intelligence agency service and a smart campus application, which are currently under development on top of our framework. |
Similar Articles
| ID | Score | Article |
|---|---|---|
38213
|
Habibzadeh, H; Qin, Z; Soyata, T; Kantarci, B Large-Scale Distributed Dedicated- and Non-Dedicated Smart City Sensing Systems(2017)Ieee Sensors Journal, 17, 23 | |
| 45493
|
Amaxilatis, D; Lagoudianakis, E; Mylonas, G; Theodoridis, E Managing Smartphone Crowdsensing Campaigns through the Organicity Smart City Plafform(2016) | |
| 44199
|
Flanigan, KA; Lynch, JP Community Engagement Using Urban Sensing: Technology Development and Deployment Studies(2018) | |
| 67352
|
Capponi, A; Fiandrino, C; Franck, C; Sorger, U; Kliazovich, D; Bouvry, P Assessing Performance of Internet of Things-based Mobile Crowdsensing Systems for Sensing as a Service Applications in Smart Cities(2016) | |
| 39573
|
Farkas, K; Lendák, I Simulation Environment for Investigating Crowd-sensing Based Urban Parking(2015) | |
| 43498
|
Miranda, R; Ramos, V; Ribeiro, E; Rodrigues, C; Silva, A; Duraes, D; Analide, C; Abelha, A; Machado, J Crowdsensing on Smart Cities: A Systematic Review(2022) | |
| 43349
|
Regalia, B; McKenzie, G; Gao, S; Janowicz, K Crowdsensing smart ambient environments and services(2016)Transactions In Gis, 20, 3 | |
| 44422
|
Khoi, NM; Rodríguez-Pupo, LE; Casteleyn, S Citizense - A generic user-oriented participatory sensing framework(2017) | |
| 41203
|
Zimmermann, T; Wirtz, H; Puñal, O; Wehrle, K Analyzing Metropolitan-area Networking within Public Transportation Systems for Smart City Applications(2014) | |
| 44528
|
Foschini, L; Martuscelli, G; Montanari, R; Solimando, M Edge-enabled Mobile Crowdsensing to Support Effective Rewarding for Data Collection in Pandemic Events(2021)Journal Of Grid Computing, 19, 3 |