In these scenarios we move beyond technical demonstration and into creating prototypes show-casing the value of the IoT search engine in the domains we are addressing.
Scenarios have been used in two phases to illustrate potential uses of the IoTCrawler framework and with the purpose of extracting technical and non-technical requirements, that will provide the basis for evaluating the results of the project.
For a full presentation of the scenarios download the presentation here.
Scenario 1: Flexibillity trading for small assets
A Smart Energy use case by Siemens
IoTCrawler scans IoT networks for assets (EV, buildings, homes) that can be used for flexible energy trading of control power, which will enable small energy prosumers to join the trading market via an aggregator.
Scenario 2: Machine monitoring
An Industry 4.0 use case by Digital Worxx
This concept will use IoTCrawler–enabled data search to add a digital data layer on approved KAIZEN processes on the industrial shop floor to identify anomalies.
Scenario 3: Pop-up experimentation spaces
A Smart City use case by the city of Aarhus
An IoT experimentation platform where flexible urban experimentation spaces in a city can be created by geo–fencing an area. The experimentation space then automatically integrates any IoT devices being implemented in the space from approved citizens or companies.
Scenario 4: Room booking
A Smart City use case by Aarhus University
This concept is a room booking monitoring system for students at a campus that gives analytical insights about room and equipment availability by using automatic sensor discovery.
Scenario 5: Smart Connect
A smart home use case by AGT
A solution that provides automatic integration of Smart Home products across different vendors into Smart Home platforms. This provides value to the end–user in the Smart Home and to the Smart Home platform developers who can easier create platforms that handles different types of devices.
Scenario 6: Smart Parking
A use case by University of Murcia/ OdinS
a parking app that crawls and searches for Regulated Parking Zone information across the city of Murcia to find the best parking spot for the citizens based on different parameters. This scenario will also develop a web portal and associated web services to analyses the traffic flow in cities and gives high–level information about traffic patterns (low, medium high), which can also be used to support a smart parking scenario. The data from the City of Aarhus will be used for the latter.
Scenario 7: Elderly care
A health care use case by University of Surrey
Showcasing a healthcare platform that discovers and integrates health-related sensors in a home in order to save integration costs and to provide data that can be analyzed to give a status of the well-being of an elderly person with dementia.
Scenario 8: Comparisense
A Smart City use case by the city of Aarhus
This concept is an IoT Product Validation platform that provides reference data sets (real and virtual) by crawling all available IoT devices across a city. Using the data from these IoT devices IoT startups and their customers are able to validate the data being generated from their own new solutions.
A number of scenarios were initially defined, in order to illustrate potential uses of the IoTCrawler framework. Below you will find a description of some of them. The use of scenarios have the purpose of extracting technical and non-technical requirements, that will provide the basis for evaluating the results of the project: The interface that will enable distributed crawling, discovery, indexing, search and integration of the dynamic data and services already available in the frameworks of IoT resources. Below you find a selection of these examples.
The Smart Cities provide many opportunities for IoT applications and are particularly well suited for crawling as they provide openly accessible data sources.
City Lab Analytics: A trend amongst Smart Cities is to establish outdoor urban testbeds to demonstrate and experiment in the public with new smart city solutions. Bringing the experiments directly into an urban setting means faster feedback and a greater chance to come up with the right solutions to tackle the city’s challenges. To enable Smart Cities to track the development of their City Lab and the potential interest from outside a City Lab Analytics scenario is described. IoTCrawler discovers what known and unknown IoT sources are placed at the City Lab, while also tracking the activities by looking for specific KPI’s
IF THIS THEN THAT (IFTTT): Homemade Digital Citizen Services & Experiments: This scenario is about integrating IoTCrawler into IFTTT.com (or a similar platform like Zapier.com) in order to get citizens started on creating smart services. IFTTT can connect two different platforms/ services in a simple way, where one act as a trigger to do something in the other. In IoTCrawler you could e.g. use this to create a “Remember the umbrella”-service by using local weather data (from IoTCrawler) as the trigger to create an action in Facebook Messenger with a helpful note.
The domain relates to applications in which IoT data is used to create social networks.
In one variant, sensor data may be collected independently from social groups that consume the data.
Examples include some commercial applications in basketball and mixed martial arts. In other variants a large number of people may provide IoT data themselves. The social IoT domain is strongly connected to events in different settings and is related to the Smart City domain.
Social media participations: This scenario demonstrates how IoTCrawler can use data generated by spectators/ participants, in creating additional insights about the event.
Sensors of the Crowd: IoTCrawler can discover sensor data from wearables and mobile phones of a large crowd if they are willing to share their data. The focus is on using audio data for creating excitement insights.
Find My Lost Child: Real-time detection of geolocation for particular people (potentially children, school classes, dementia patients etc.) through public IoT devices.
This domain is represented by two scenarios. The scenarios will demonstrate how sensitive information and services provided by building management systems, which are unknown to a grid operator but operate within its grids, can be integrated in the operator’s operation and planning processes. IoTCrawler will allow to significantly reduce the integration effort while maintaining data privacy and security requirements of the involved entities.
IoT aided Smart Grid Planning: This scenario demonstrates how IoT-Crawler technology can be used to enable a secure and managed access of location-specific prosumer data in the context of grid planning. The specific scenario will facilitate the integration of services and information provided by prosumers and other intelligent smart grid entities into the planning process of distribution system operation.
IoT aided Smart Grid Operation: This scenario demonstrates how IoT-Crawler technology can be used to enable a secure and managed access of location-specific prosumer data in the context of grid operation. The specific scenario will facilitate the integration of services and information provided by prosumers and other intelligent smart grid entities into distribution system operation. Being able to access real-time information on load and generation helps distribution system operators to forecast daily operational parameters in order to keep its grid operation wit
This domain is represented by one initial scenario. We consider IoTCrawler to play an important role in this domain as it will allow to significantly reduce the integration effort and costs of sensor data from manufacturing machines: In this scenario IoT Crawler performs in an environment with a predefined scope for crawling and will semi-automatically discover related data.
Condition Monitoring and process optimization: Will be updated soon.