The concept of smart cities envisions services that provide distraction-free support for citizens. To realize this vision, the services must adapt to the citizens' situations, behaviors and intents at runtime. This requires services to gather and process the context of their users. Mobile devices provide a promising basis for determining context in an automated manner on a large scale. However, despite the wide availability of versatile programmable mobile platforms such as Android and iOS, there are only few examples of smart city applications. One reason for this is that existing software platforms primarily focus on low-level resource management which requires application developers to repeatedly tackle many challenging tasks. Examples include efficient data acquisition, secure and privacy-preserving data distribution as well as interoperable data integration. In this paper, we describe the GAMBAS middleware which tries to simplify the development of smart city applications. To do this, GAMBAS introduces a Java-based runtime system with an associated software development kit (SDK). To clarify how the runtime system and the SDK can be used for application development, we describe two simple applications that highlight different middleware functions.
[1]
Tim Berners-Lee,et al.
Linked Data - The Story So Far
,
2009,
Int. J. Semantic Web Inf. Syst..
[2]
G. Schiele,et al.
The BASE Plug-in Architecture-Composable Communication Support for Pervasive Systems
,
2010
.
[3]
Pedro José Marrón,et al.
Configuration folding: An energy efficient technique for context recognition
,
2012,
2012 IEEE International Conference on Pervasive Computing and Communications Workshops.
[4]
Gregor Schiele,et al.
Fine-Grained Access Control for RDF Data on Mobile Devices
,
2013,
WISE.
[5]
Nigel Shadbolt,et al.
Resource Description Framework (RDF)
,
2009
.
[6]
Danh Le Phuoc,et al.
RDF On the Go: RDF Storage and Query Processor for Mobile Devices
,
2010,
SEMWEB.
[7]
Pedro José Marrón,et al.
The NARF Architecture for Generic Personal Context Recognition
,
2010,
2010 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing.
[8]
Pedro José Marrón,et al.
PIKE: Enabling secure interaction with piggybacked key-exchange
,
2013,
2013 IEEE International Conference on Pervasive Computing and Communications (PerCom).