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Mtel, a.d. , Banja Luka , Bosnia and Herzegovina
Faculty of Computer Science, University PIM , Banja Luka , Bosnia and Herzegovina
The paper describes the implementation of an Elastisearch, Logstash and Kibana (ELK) stack to process, analyze and display of IoT data originating from several types of sensors. The prepared Elasticsearch platform collects and integrates real data generated by various sensors for further processing and publishing the desired information. Storing different format inputs, finding and extracting the desired information is a key issue that we needed to solve in our IoT environment. We used Grok filters within Logstash to parse unstructured data and as a result we got structured data in JSON format. Using Logstash allowed us to route filtered data to Elasticsearch. Elasticsearch simplifies the storage of large amounts of records in a database that can be easily searched. Depending on the type of data received from the IoT sensors, we have applied custom filters to analyze the received data, index it and store it in the database. We have presented the relevant information and introduce it to the user using a Kibana interface. By using Kibana, we achieve the near-real-time display of desired analytical information from the IoT network. The presented concept and data analytics system can be used in more sophisticated IoT networks to automate the generation of required analytics, giving the IoT system the ability to take automated actions based on analyses of collected IoT information
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