Name
Abstract | ||
|---|---|---|
A critical step towards smarter and safer cities is to endow them with the abilities to massively gather a wide variety of data sets and to automatically feed those data to decision support tools and applications that leverage artificial intelligence. We present UrbanSense, a platform deployed on the streets of a mid-size European city (Porto, Portugal) to collect key environmental data. The main innovations of UrbanSense are (1) design for affordability and extensibility, (2) its ability to leverage heterogeneous networks to send the data to the cloud (using both real-time and delay-tolerant communications), and (3) its Internet of Things integration to expose the data streams to smart city tools and applications. Beyond discussing the design choices, we present operational results for 6 months of operation and give a detailed account of the challenges faced by the successful deployment of urban sensing technologies in the wild. |
Year | Venue | Field |
|---|---|---|
2016 | IEEE SECOND INTERNATIONAL SMART CITIES CONFERENCE (ISC2 2016) | Data science,Data stream mining,Software deployment,Computer science,Computer security,Decision support system,SAFER,Smart city,Environmental data,Heterogeneous network,Cloud computing |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
4 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yunior Luis | 1 | 0 | 0.34 |
| Pedro M. Santos | 2 | 1 | 0.73 |
| Tiago Lourenço | 3 | 8 | 0.95 |
| Carlos M. Pérez-Penichet | 4 | 31 | 6.29 |
| Tânia Calçada | 5 | 5 | 3.62 |
| Aguiar, A. | 6 | 45 | 9.11 |