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.

In this paper we introduce a public transit schedule and route planner application for urban public transportation. The application was developed for the Android Operating System. It works offline and does not need a permanent internet connection.While transport agencies usually make their schedules available online, browsing them outdoors is not always possible, or requires too much effort on the small screen of a mobile phone. The solutions of this problem are the GTFS databases, which describe the urban public transportation systems. Developers can create applications which use the GTFS databases. However, these databases are not applicable for fast processing needed for route planning on mobile devices with limited resources. Therefore we created a data structure from the GTFS database which is easier to manage, smaller and faster to process. The Android application uses this data structure.The application lists the departure times, journey times and the stops of the lines. It can display the lines on the map. It also shows the stops nearby with the name of the lines passing through. The user can choose one or more stops and view details about the lines passing through.The main function of the application is the route planner. It plans at least one route from a starting-point to a destination. Before the route planning the user can set parameters which are taken into account by the route planner.

In the field of smart city mobile applications based on crowdsourced data, the automation of the data collection process is a substantial requirement. Continuous user interaction can not be expected and feedback heavy solutions can discourage the masses from participating. Luckily, the currently available mobile devices already carry the sensors we need and large number of developer tools are at our disposal to overcome this issue. Mobile sensors can provide two important information we can benefit from: the user's location and the user's activity. On a large scale the sensory data may vary due to the diversity of the devices, thus reassurance from the user and strict supervision of collected information can not be neglected. Although a great number of solutions already had come to realization regarding user activity recognition, they usually serve as stand-alone solutions as they are not bind to solve a specific problem. In urban environments these solutions carry a great potential. In this paper we would like to share our experiences in user activity recognition, present a sensory module implemented using the latest Google API-s for Android platform and how can it function as a valuable asset of a Smart Public Transport Service.