EU FP7 CityPulse Project- Open Source Tools and Components's repositories
CityPulse-City-Dashboard
The CityPulse framework provides immediate and intuitive visual access to the results of its intelligent processing and manipulation of data and events. The ability to record and store historical (cleaned and summarized) data for post-processing makes it possible to analyse the status of the city not only on the go but also at any point in time, enabling diagnosing and “post mortem” analysis of any incidents or relevant situation that might have occurred. To facilitate that, a dashboard for visualising the dynamic data of the smart cities is provided on top of the CityPulse framework.
CityPulse-3D-Map
This application has been developed with the core goal to provide a 3D visualisation and experience to the users. By using it the users can “fly” around this 3D model of a city and visualise the effect of real-time data in the model. The map has been integrated with the CityPulse framework for displaying events aroud the city of Aarhus on traffic, parking, pollution and noise.
Knowledge-Acquisition-Toolkit
The Knowledge Acquisition Tool (KAT) is a software toolkit that implements the state-of-the-art machine learning and data analytic methods for sensors data. The algorithms and methods implemented in KAT are used for processing and analysing the smart city data in the CityPulse project.
Social-Media-Analyser
This is package includes a php subpackage for Twitter data collection via connection to streaming API, a python Annotation GUI for labelling the collected data and finally a Twitter analysis sub-package in python and java that are used in the CityPulse project.
Brasov-Bus-Route-Planner
In order to demonstrate how the CityPulse framework can be used to develop applications for smart cities and citizens, we have implemented a context-aware real time Travel Planner using the live data from the city of Brasov, Romania. This scenario aims to provide bus travel-planning solutions, which go beyond the state of the art solutions by allowing users to provide multi dimensional requirements and preferences such as the fastest route, number of buses, minimum number of stops as well as busses with special facilities for people with disabilities. In this way the users receive bus route recommendations based on the current context of the city. In addition to this, Travel Planner continuously monitors the user context and events detected on the planned route. User will be prompted to opt for a different route if there are reported incidents ahead. All the CityPulse framework components are deployed on a back-end server and are accessible via a set of APIs. As a result of that the application developer has only to develop a user-friendly front-end application, which calls the framework APIs. In our case we have developed an Android application.
Event-Detector
The Event detection component in the CityPulse framework provides the generic tools for processing the annotated as well as aggregated data streams to obtain events occurring into the city. This component is highly flexible in deploying new event detection mechanisms, since different smart city applications require different events to be detected from the same data sources.
Knowledge-Acquisition-Toolkit-2.0
The Knowledge Acquisition Tool (KAT) is a software toolkit that implements the state-of-the-art machine learning and data analytic methods for sensors data. The algorithms and methods implemented in KAT are used for processing and analysing the smart city data in the CityPulse project.
CityPulse-Dynamic-Bus-Scheduler
A research project of Ericsson (Department of Research and Development, Stockholm, Sweden) within the field of Smart City Internet of Things (IoT) Applications.
Composite-Data-Quality-Monitoring
Composite Monitoring and Evaluation Code. The Composite Monitoring Component is used to evaluate correlations between individual data streams. It is used to check the plausibility of space-time congruent data sets.
EventReportApp
The CityPulse Event Report Application for Android enables the user to see ongoing events reported by the CityPulse framework and other users.
Resource-Manager
The Resource Management component in the CityPulse framework is responsible for managing all Data Wrappers. During runtime an application developer or the CityPulse framework operator can deploy new Data Wrappers to include data from new data streams.
CityPulse-Journey-Planner
In order to demonstrate how the CityPulse framework can be used to develop applications for smart cities and citizens, we have implemented a context-aware real time Travel Planner using the live data from the city of Aarhus, Denmark. This scenario aims to provide travel-planning solutions, which go beyond the state of the art solutions by allowing users to provide multi dimensional requirements and preferences such as air quality, traffic conditions and parking availability
CityPulse-Pick-up-Planner
The Pickup planner aims to provide a travel service for users located around Stockholm. Users specify pickup location, destination, arrival time constraints and preferences in travel requests, from which the system devises a pickup path to be used by vehicle(s) in delivering users to their intended destinations.
Data-Quality-Explorer
Web-based tool to monitor information about sensor quality and framework reliability. In the CityPulse Framework it provides a visualisation of the Monitoring Component.
Data-Stream-Generator
CPA is a tool for datastream generation and playback. The CityPulse framework uses this component to run some of the demonstrators.
Decision-Support-and-Contextual-Filtering
The Decision Support component utilises contextual information to provide optimal solutions of smart city applications. The Contextual Filtering component continuously identifies and filters critical events that might affect the optimal result of the decision making task.
Documentation
This repository includes all documentation on the overall CityPulse framework
Common-Libraries
This package includes java classes which represent the models of input and output for the Decision Support, Contextual Filtering, and Data Federation components in the CityPulse project.
CityPulse-Geospatial-Data-Infrastructure
The Geospatial Data Infrastructure (GDI) component is used by a number of other CityPulse components to tackle geo-spatial tasks.
CityPulse-Tourism-Planner
This project combines sources of data related to events and points of interest (PoIs) in the city of Stockholm, and generates a schedule to explore the PoIs that the users select. The schedule is created based on the opening times of each PoI as well as the user's budget, travel period, and type of transport.
CityPulse-Wiki
This Repository is uses to host the CityPulse Development Wiki: https://github.com/CityPulse/CityPulse/wiki
Event-Testing
An Android application for reporting events and a R Shiny application for webbrowsers to show and inspect events generated by the application and the CityPulse Event Detection.
Fault-Recovery
The Fault recovery component ensures the continuous and proper operation of the CityPulse enabled application by generating estimated values for the data stream when the quality drops or it has temporally missing observations.
IoT-Framework
A mechanism for converting data points stored in the IoT-Framework into semantically annotated data. This can be use for searching and accessing raw sensory data in a smart city data analytics framework.
SAOPY
SAOPY is a sensor annotation library that embodies well-known ontologies in the domain of sensor networks that are used in the CityPulse project. It enables to prevent common syntax errors (e.g. undefined properties and classes, poorly formed namespaces, problematic prefixes, literal syntax) in RDF documents during the annotation process before it is published as linked data.
Stream-Discovery-and-Integration-Middleware
The Automatic Complex Event Implementation System (ACEIS) is a middleware for complex event services. It is implemented to fulfill large-scale data analysis requirements in the CityPulse project and is responsible for event service discovery, composition, deployment, execution and adaptation. It is mainly used in the Data Federation and Technical Adaptation components in CityPulse framework.
Stream-Processing-Benchmark
Configurable benchmark for RSP engines using citypulse datasets