There are a lot of activities going on in the IoTCrawler project, some of them especially deals with technical build, development and data connections. The following gives a technical status on the project in the beginning of April 2019 from The University of Applied Sciences Osnabrück (Germany) and The University of Murcia (Spain).
The University of Applied Sciences Osnabrück (Germany) and The University of Murcia (Spain) are two of the 10 partners in the IoTCrawler project and contributes with expertise in quality analysis and testing in the framework. Their role is to define the requirements for sensor modelling, monitoring and fault recovery and the design of Data attributes and QoI metrics.
STATUS FROM University of Applied Sciences Osnabrück (Germany)
Quality Ontology for IoT Data Sources
At the beginning of the year 2019 University of Applied Sciences Osnabrückfinished the development of the “Quality Ontology for IoT Data Sources” and its metrics. The ontology is used to clearly define the metrics used to rate the Quality of Information (QoI) of data sources handled by IoTCrawler. Therefore, it is used to build a machine readable model of relations between the IoT data and the metadata of the sensor, including QoI. The ontology is the representation of the QoI calculated within framework.
The QoI is important, because it can rate the quality of delivered data and with QoI, IoTCrawler will be able to rank data sources based on their quality. In this way, IoTCrawler can check the data for its correctness. As an example, the framework will check if the delivered data is within an expected value range (e.g. the temperature inside a building is unlikely to be below 10°C) or compare it with other sensors/data sources nearby.
The best fitted data for IoTCrawler
Therefore, the usage of QoI will ensure that IoTCrawler is able to rate data sources based on the quality of provided data. This ensures delivery of the best IoT data sources and will automatically increase user acceptance. IoTCrawler will always select the best data sources and, in case of faulty data, it will try to correct the delivered data or replace it by other (virtual) data sources.
Currently we are working on the development of the abovementioned components and their integration into the IoTCrawler framework. The focus at the moment is to define the APIs/connections to the other partners – and how these can be integrated into the planned components
STATUS FROM University of Murcia (Spain)
Development environment sat up
At the beginning of April 2019 University of Murcia have set up a development environment and deployed an instance of an NGSI-LD broker (mechanism to represent information in the form of entities, and relationships between them) to allow other partners to interact with NGSI-LD entities and properties.
Integrating environmental information
Additionally, Murcia are working on integrating the environmental information from a Smart Building facility of the University of Murcia, for the information to be handled by the project partners. This information provided by deployed sensors in the facility comprises luminosity, temperature, humidity, and energy consumption.
Security and privacy
Furthermore Murcia is working on the adaptation of the authorization enabler and proxy to work with the NGSI-LD broker, in order to meet the needs of security and privacy in IoTCrawler. By letting the authorization enabler and proxy work with the NGSI-LD broker, every query to the broker will be controlled, allowing only legitimate users, process, or devices to access the stored information.