Introduction

Field data is an essential asset for understanding the reality that products are exposed to. This understanding is a prerequisite to improve products and to keep them competitive on the market. But field data for products is not automatically available. It needs effort to build a sustainable process and environment for collecting and using field data. Bosch IoT Insights provides a cloud infrastructure, REST APIs, and a web application user interface . Those features allow you to store, query, and isolate data for further investigation and needs . It is further based on state-of-the-art technologies, such as MongoDB.

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Bosch IoT Insights processes the data generated by any device. The data sent to the cloud is first stored in raw format. To ensure seamless integration of data, Bosch IoT Insights offers a standard HTTPS API and the automotive-specific API of the CML Flea 3 box.
The cloud services Bosch IoT Gateway Software, Bosch IoT Remote Manager, and Bosch IoT Things can also serve as an instance to ingest data.

Once data has been stored in the object storage, the service enables you to decode, normalize, enrich, and clean your data. In a next step, you can query your data using NoSQL/MongoDB databases and visualize it using standard and user-defined dashboards.
In addition, Bosch IoT Insights also features interfaces for third-party data analytics tools, such as Matlab and Excel.

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General features

The features in detail:

  • Data ingestion

    • Via direct networking, offline transmission of data packages, encrypted channels, or raw data storage

    • Via the standard HTTPS API of the cloud services Bosch IoT Gateway Software, Bosch IoT Remote Manager, and Bosch IoT Things

    • Via Bosch IoT Things with a linked namespace

    • External interfaces, such as Flea 3 (telematics system)

    • Via web browser

  • Data storage

    • Object storage for raw data

    • MongoDB for processed data, using a highly secure, cloud-based lambda infrastructure

    • Storage of data types such as time series data, aggregated counters, statistical information, and logging information

    • Storage of device master data such as time series data, aggregated counters, statistical information, and logging information, metadata, image information, and device information

    • Interfaces for t hird-party data analytics tools, such as Matlab and Excel

  • Data processing

    • The provided data processor makes binary data readable with the industry-wide description standards, such as ODX, Fibex, A2L, MDF, DBC, and Google Protocol Buffer

    • Ingested data can be unified by bringing together different data sources and unifying their data structures

    • Removal of duplicates to guarantee high data quality with reduced costs

    • Aggregation of different data sources

    • Integration of custom processing scripts (Java, JavaScript, and Python) that can be combined with other processors

  • Data visualization

    • Customized dashboards and views with various widgets such as bar charts, location maps, tables, etc.

    • Simple NoSQL or MongoDB database query templates

  • Master data management

    • Creating and maintaining visualizations of physically existing devices

    • Clustering of device data from Bosch IoT Things based on device types

    • Overview of device status and components as well as their relationships

  • Authentication and authorization

    • Basic authentication to authenticate users

    • Five different roles with corresponding permissions to authorize users

    • Communication is secured through HTTPS and encrypted through TLS 1.2

  • Availability

Architecture

The following image illustrates the architecture of Bosch IoT Insights:

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