It's time to listen! ESYS use cases with ThingsBoard

ThingsBoard is launching a series of customer experience publications. For your convenience, we will tag the stories with #ThingsBoardInAction. Recently we'd already came up with case studies of our customers and now we want to make these printings on a regular basis.

The very first #ThingsBoardInAction story came from ESYS GmbH. The company has a large number of customers from various industries. Hereunder we present some of the solutions ESYS has implemented with Thingsboard. Initially, the company started with Community version and then migrated to the Pro version of the platform.

#bthvn2020

"In the course of the Beethoven Year 2020, the Berlin State Library has exhibited and made available to the public its substantial collection of Ludwig van Beethoven's music manuscripts.

ESYS GmbH ensured the climatic monitoring of the sensitive exhibits and made them accessible to the responsible persons via Thingsboard Dashboard", — says Dr. Robby Rochlitzer, Managing Director Research and Development at ESYS.

Agriculture

For the agricultural industry ESYS team has developed a product that uses Modbus sensors for soil moisture and climate monitoring (temperature, relative humidity, wind direction, wind speed, rainfall) to optimize irrigation and fertilization and allows for evaluation using a Thingsboard.

Monitoring Industry 4.0

According to Dr. Rochlitzer, "In cooperation with an industrial company, a system was developed that records and monitors motor temperatures, motor current consumption, the temperatures of two motor bearings, vibrations and control cabinet temperatures in kilns".

Smart poultry production

For the purpose of monitoring of breeding houses and adjusting the quality of life index, the developed system delivered live images and ability to evaluate them via Thingsboard.

To all the customers we have and will have in the future: #ThingsBoardInAction is a good opportunity to tell the world about your company and your solutions. We are keen to support your IoT market expansion with our products and this additional option.

Deleting timeseries of deleted ThingsBoard entities

    As of ThingsBoard v.2.5.4/3.1.1, telemetry and attributes of entities are not automatically deleted when entities themselves are deleted, which causes performance degradation (because of decreasing query speed) and filling up of the disk space . Lower are queries for the PostgreSQL database to delete telemetry and attributes.

    Deleting timeseries of previously deleted entities:

 DELETE * FROM ts_kv WHERE entity_id NOT IN (SELECT id FROM device) AND entity_id NOT IN (SELECT id FROM asset) AND entity_id NOT IN (SELECT id FROM customer) AND entity_id NOT IN (SELECT id FROM tenant) AND entity_id NOT IN (SELECT id FROM entity_group) AND entity_id NOT IN (SELECT id FROM integration) AND entity_id NOT IN (SELECT id FROM converter) AND entity_id NOT IN (SELECT id FROM entity_view) AND entity_id NOT IN (SELECT id FROM tb_user) AND entity_id NOT IN (SELECT id FROM dashboard) AND entity_id NOT IN (SELECT id FROM rule_chain) AND entity_id NOT IN (SELECT id FROM role); 

    Deleting attributes of previously deleted entities:

 DELETE * FROM attribute_kv WHERE entity_id NOT IN (SELECT id FROM device) AND entity_id NOT IN (SELECT id FROM asset) AND entity_id NOT IN (SELECT id FROM customer) AND entity_id NOT IN (SELECT id FROM tenant) AND entity_id NOT IN (SELECT id FROM entity_group) AND entity_id NOT IN (SELECT id FROM integration) AND entity_id NOT IN (SELECT id FROM converter) AND entity_id NOT IN (SELECT id FROM entity_view) AND entity_id NOT IN (SELECT id FROM tb_user) AND entity_id NOT IN (SELECT id FROM dashboard) AND entity_id NOT IN (SELECT id FROM rule_chain) AND entity_id NOT IN (SELECT id FROM role); 

    However, in PostgreSQL deleted rows are not physically removed from the table, they remain present until the VACUUM command is done, as described here: https://www.postgresql.org/docs/11/sql-vacuum.html. In order to reclaim the disk space VACUUM commands with ANALYZE parameter (for statistics refreshing) needs to be executed:

 VACUUM ANALYZE attribute_kv; 

    And if reclaiming space is critical, the parameter FULL should be added (please note that it requires as much free disk space as the table currently takes up):

 VACUUM FULL ANALYZE attribute_kv; 

    In order to find the list of telemetry tables to be VACUUM’ed, the following command needs to be executed:

SELECT table_name FROM information_schema.tables WHERE table_schema = 'public' AND table_name like 'ts_kv%' ORDER BY table_name; 

    Then the resulting list of tables is put in the VACUUM ANALYZE command:

    In this example the command looks like this:

VACUUM FULL ANALYZE ts_kv, ts_kv_2004_01, ts_kv_2020_08, ts_kv_2020_09, ts_kv_dictionary, ts_kv_indefinite, ts_kv_latest; 

    Please be aware that:

1.You need to put the list of tables from the output of the previous SELECT query, not just copy the previous VACUUM command.

2.Tables are not available when you perform a VACUUM command (all incoming read and write queries are put in a queue), so the best solution would be to perform it in the (at least relative) downtime.