The IoT Learning Agent (LA) is bing developed for all kind of store-less data processing, from simple data annotation or aggregation to complex data machine learning techniques. The LA fulfill the task of a LinkSmart® Processor and a bit of a Message Handler (see LinkSmart® Specification), and they are ideal for intelligent on-demand data management or analysis in IoT environments, from edge computing to cloud computing. The LA can be used as edge standalone service or as a computational node in the cloud.
The LA is a service that offer Complex-Event Processing as service and Real-time Machine Learning as a service. The agent provides three APIs, the Stream Mining API (Statement API), the Learning API (CEML API) and the IO API. The Statement and CEML APIs are CRUD (Create, Read, Update, Delete) and JSON based, while the IO are write-only (for Input) or read-only (for Output). The APIs are implemented as HTTPs RESTful and MQTT. There is a lightweight version of the LA without the learning API, named Data-Processing Agent (DPA)
For more documentation please see IoT Learning Agent Wiki.
Using Docker
docker run -p "8319:8319" linksmart/la:latest
Without docker
curl -O eu/linksmart/services/events/gpl/distributions/iot.learning.universal.gpl.agent/1.8.2/iot.learning.universal.gpl.agent-<current.version>.jar
env_var_enabled=true cep_init_engines=eu.linksmart.services.event.cep.engines.EsperEngine env_var_enabled=true cep_init_engines=eu.linksmart.services.event.cep.engines.EsperEngine java -cp ./* "org.springframework.boot.loader.PropertiesLauncher"
git clone https://github.com/linksmart/data-processing-agent.git code
cd code
mvn install
To install maven in Linux:
apt-get install maven
For use maven in docker see: Maven Docker Image
cd gpl-artifacts/distribution/IoTAgent/target
env_var_enabled=true cep_init_engines=eu.linksmart.services.event.cep.engines.EsperEngine env_var_enabled=true cep_init_engines=eu.linksmart.services.event.cep.engines.EsperEngine java -cp ./* "org.springframework.boot.loader.PropertiesLauncher"
cd gpl-artifacts/distribution/IoTAgent/target
env_var_enabled=true cep_init_engines=eu.linksmart.services.event.cep.engines.EsperEngine env_var_enabled=true cep_init_engines=eu.linksmart.services.event.cep.engines.EsperEngine java -cp ./* "org.springframework.boot.loader.PropertiesLauncher"
For more please see: IoT Learning Agent.
Feel free to create an issue or pull request in GitHub in case you want to contribute to the software.
This work was applied and supported by the European Commission through:
- The ALMANAC FP7 project under grant no. 609081.
- The IMPReSS H2020 project under grant no. 614100.
- The EXCELL H2020 project under grant no. 691829.
- The COMPOSITION H2020 project under grant no. 723145.
- An online machine learning framework for early detection of product failures in an Industry 4.0 context
- Optimization Framework for Short-Term Control of Energy Storage Systems
- Enabling Smart Cities through IoT: The ALMANAC Way
- Industry 4.0: Mining Physical Defects in Production of Surface-Mount Devices
- CEML: Mixing and moving complex event processing and machine learning to the edge of the network for IoT applications
- ALMANAC: Internet of Things for Smart Cities