Kiwee Edge – Big Picture
Kiwee Edge acts as building block to collect, deduplicate and process IOT data from edge level data stream and forward enriched and value added information to IT applications, infrastructure and systems.
This section highlights capabilities and functionalities that can be established with Kiwee Edge processing. The Kiwee Thing definition and Kiwee Node processing no-code implementation allows flexible and compelling information processing and consumption already on edge level.
Edge can be any physical machine boarder if Kiwee acts as IOT building block for a machine supplier. On factory shop-floor level edge can be a WorkCenter, Line or Assembly area or entire plant.
Wherever you’d need to enrich data and create data constellations for further processing – Kiwee Edge is delivering the necessary functionality at lowest cost.
Kiwee Edge – capabilities and functionalities
Select and Trigger
Monitoring of defined IOT data stream for desired values and data constellation that should trigger subsequent processing within Kiwee Edge.
De Duplicate
Identify whether new subscribed topics have changes in data. De duplication option allows to skip identical record processing.
Thing of interest
A data stream records that triggers processing in Kiwee Edge can be enriched with additional related thing data values even if those do not actually created any direct processing scenario.
Enrichment
Kiwee Edge processing data values will be automatically enriched by unit of measure, the environment location of the related thing and other thing capability definition. A unique key prefix name can be included to create initial self-explainable customer data model. Further record enrichment from within the Kiwee Edge Node logic expression will be added.
Arithmetic
Within the node you define the selection logic across single or multiple things. Within the Kiwee Node data constellation all fields can be used for arithmetic calculations.
Statistical
The actual Kiwee Node data constellation can be enriched with statistical information related to time shifts for Count, Min/Max/Avg, Total and custom enrichment per statistical record processed.
Sequence
Sequence scenario within a node definition and related to defined time-shifts can be assessed. For each scenario a start and end record will be created and made visible within the time series database.
Action
A defined data constellation can trigger any desired action on the edge data stream for one or multiple IOT-Things that allow actuator behaviors and instructions.
Storing
Edge local data repositories can be established within longer-term historical and time series database.
Forward
Any identified Kiwee Edge data constellation with its standard enrichment and additional analytical information can be forwarded/published to any destination.
Connectors
We support various connectors transforming protocols like OPC/UA to MQTT and versa. Also, star-schema data models can be created within relational databases of IOT MQTT Stream. Forwarding Sequences as quality statements can be established individually.
Visualization
The influxdb based time series database allows Visualization of trigger information with dashboards and drill-down capability.
Kiwee Edge – Building Blocks
We build Kiwee Edge with Python and Vue.JS utilizing a modern open-source technology stack for our overall solution.
Kiwee Edge can be deployed in any environment supported by docker as central infrastructure deployment entity.
Kiwee Edge is processing information records of the IOT data Stream and is identifying and processing the defined Kiwee Node data constellation together with the selected provided value-add technologies.
With audio/video analytical based solution you can even process AV findings and related information of the IOT stream data to add additional value to the identified operational constellations during processing.
Kiwee Edge – No Code Overview
Use Case: Battery Analytics and Tracking
Battery analytics and management necessitates sophisticated tools that can handle vast volumes of data and convert it into actionable insights. This use case delves into how Kiwee Edge effectively processes and interprets data from a nine-cell battery pack, focusing on parameters such as temperature and voltage, as well as the battery’s location and status.
The Challenge
Handling a battery pack involves processing a continuous stream of unstructured data from Battery Management System (BMS) for all nine cells, from Programmable Logic Controller (PLC) for charging and energy consumption. The related data, which includes key parameters such as temperature and voltage, is typically raw and unorganised, making it difficult to directly retrieve valuable insights. Furthermore, tracking the location and status of each battery adds another layer of complexity to the process.
Kiwee Edge for Battery Analytics
Kiwee Edge provides a comprehensive solution to satisfy the mentioned requirements and challenges. We also explain initial setup activities. Within our described Battery Analytics usage scenario, we focus on Battery Cell Temperature deviation during charging, consumption but also during battery transportation and storage scenario while located in related warehouse depot’s.
MQTT data stream
The IOT devices are publishing information within multiple topics. Kiwee Edge allows no-code logic to combine the digital information and assess and publish/store evaluated data constellations. Here the overview of MQTT Topics that should be subscribed and processed to provide related battery analytics scenario’s.