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TICK Stack, Grafana® & InfluxDB - How IoT service providers visualise sensor and machine data

One of the most important interfaces of a IoT project are the User interfaces. System states can be defined at any time during integration using Dashboards efficiently and clearly. InfluxData and Grafana® offer open-source solutions for this, both of which are based on the InfluxDB Enable visualisations for IoT data. We show you your direct Getting started with data visualisation!

 

Update: The term TICK Stack is obsolete

As described in the article, the term TICK Stack refers to a series of open source tools for data collection and monitoring. In the previous iteration, the solution for visualising dashboards for IoT companies consisted of Telegraph, InfluxDB, Chronograph and Capacitor. The further development of the components means that the chronograph and Kapacitor are now available in InfluxDB v2 are integrated. In addition, the query language has changed with the update from InfluxDBv1 to InfluxDBv2 from InfluxQL to Flux changed. Telegraf is therefore the only remaining separate component in the stack.

 

InfluxDB as the technological basis - TICK and TIG Stack

The technology stack based on InfluxDB, the so-called TICK Stack stands for the co-operation of Telegraph, InfluxDB, Chronographer and Kapacitor. The logical basis is a Database (InfluxDB), here all Measuring and Sensor data stored and organised. A translator (telegraph) is required to fill InfluxDB with meaningful data from various sources, such as camera or heat sensors. This understands the raw data from the sensors and prepares it for InfluxDB. The Visualisation of the data to a dashboard (chronograph) enables the Service provider and Customers one Efficient monitoring. The system's simplified alarm clock (Kapacitor) can detect changes according to desired parameters and release them for visualisation. It displays the Interface between the InfluxDB Database and the Dashboard represent.

Alternative to the TICK Stack is the TIG Stack, consisting of Telegraph, InfluxDB and Grafana®. Similar to TICK, the variant with Grafana® is also a Open source platform. The advantage of using Grafana® is that Multiple data sources can be used efficiently at the same time and the operator is not limited to InfluxDB as a database. Furthermore, Grafana® offers optimised possibilities to easily share data and efficiently create notifications about changes and status. The Grafana® option simplifies the overall InfluxData package. The obligatory actions/trigger system does not need to be set up if not necessary or undesired. Grafana® thus offers the possibility of a leaner installation without having to forego the functionality of InfluxDB. Furthermore, the basic InfluxDB also offers the option of switching from TIG to TICK at a later stage of the IoT project without a "restart".

 

Monitoring - advantages for service providers of an IoT project

The Monitoring of machine and sensor data is a fundamental requirement for service providers of IoT projects. A valuable advantage of a dashboard based on Grafana® or InfluxDB already exists during the integration of artificially intelligent sensor systems. This is because both the service provider and the operator can efficiently monitor the status of all sensors right from the start of integration.

Another major advantage is that deviations and optimisation possibilities in the alignment of sensors can be identified immediately and optimisations can be made. This Real-time monitoring service providers and the operator's employees can act directly if necessary. The customised user environment presents the data in a suitable context, from which a Increased productivity can result. Employees can thus more efficient and demand-based work.

As a further iteration of this process AI assistants and AI-based Functions from Real time Recognising data trends and forecast. These monitoring forecasts can in turn be used for early adjustments and optimisations. For example in the Quality assurance can thus be Successes can be achieved, while at the same time production errors can be avoided or reduced.

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