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What is intdash?

intdash is a bidirectional data transmission platform that streams high frequency (at intervals of in the range of 100 microseconds to 1 second) time-series data via networks of varying quality at high speed, in large volumes while maintaining a high level of stability. intdash is also the name of Aptpod-branded products and services that form a proprietary platform (brand name). It is an abbreviation for INTeractive DAta Streaming Hub.

intdash connects devices that generate a large amount of data in a extremely short time intervals, such as automobiles, robots, and industrial machines, and also has control/visualization applications which are available in real-time via mobile or internet networks. Streaming data flowing through intdash Server Core are stored in time-series data store as-is and can be used for visualization with our Visual M2M user interface and analysis processing or machine learning with our Analytics Services.

A fast data IoT solution that combines high speed, bidirectionality,
real-time properties, and data integrity

intdash use cases

intdash supports requirements necessary for realizing representative industrial IoT use cases through streaming processing of high-frequency data necessary for industrial IoT systems.

iSCP (intdash Stream Control Protocol)

Stream control protocol for data transmission between edge and server

iSCP (intdash Stream Control Protocol) is a proprietary protocol that developed by aptpod that is used for internal communication of a module. iSCP is used for data streaming between a relay broker of streaming data and the module of an edge device to deliver the main functions of intdash, such as complete data collection, efficient transmission, and flow control.

Media Services

Supporting media data such as video and voice

In addition to industrial equipment’s control data and sensor data, stream processing and the acquisition of video and voice data (which are in high demand) are also supported. Video and voice data obtained at the edge side are integrated by transmission with iSCP and integrated timestamp processing can be performed in the same way as other sensor and control signals.

Analytics Services

Supporting analysis and calculation processing of time-series data

Analytics Services supports the analysis of collected data and can execute the processing of data, summary processing, various calculation processing, and machine learning by plugging the Python program into the system. As a result, real-time processing of live stream data, as well as accumulated time-series data, can be performed.

Python SDK for intdash Analytics Services

A library for constructing and executing various processes, such as machine learning and analysis of data collected on the Intdash and Intdash Automotive Pro cloud, as well as real-time data, on Analytics Services. Facilitates data access from the Jupyter Notebook and the Python program on Analytics Services, which are widely used for data analysis and machine learning environments, to Intdash, as well as storage of processing results to the Intdash database, and provides enhanced support for processing logic development and testing by developers.

In addition, it is possible to construct a learning and operational environment around Analytics Services by combining machine learning and deep running OSS library.

Other optional functions supporting industrial IoT use cases

Functions supporting the various requirements of IoT use cases are available as options.

Notification Service
  • Supplying real-time event processing by determining the threshold value of stream data
  • Notification to e-mails, SMS, and applications, and signal transmission to edge side
Data Sequencer
  • Synchronization processing when performing control streaming from server to multiple edges with stream data
Logic Handler
  • Generating data filter logic and processing algorithm to be distributed to edge systems
Config Handler
  • Distributing setting information to edge systems
  • Distributing data filter logic generated by Logic Handler or processing algorithm to edge systems

intdash products and services

intdash and Visual M2M are delivered in the form of a cloud service subscription for testing, such as PoC, or license subscription (Linux version) for operation in the customer’s environment. In addition, optional modules or features, such as intdash Server Corecan be added according to the user’s requirements.

Server software (supply format: service subscription or license subscription)

Name Function
intdash Server Core Core asset of intdash that includes Real-time API, REST API, and data store system
Analytics Services Calculation and analysis processing and machine learning environment by plugging in Python program
Media Services Processing video data and voice data, and store environment
Notification Service Notification service by event processing
Data Sequencer Module controlling synchronization stream from server to multiple edges and UI
Logic Handler Generating logic to be distributed to edge devices
Config Handler Handling of distribution of various filters and logic to edge devices
Visual M2M Server Core Web dashboard for visualizing streaming data

Appliance with intdash Edge Module mounted, Terminal Systems, is available as an edge solution for PoC.

Edge hardware (supply format: appliance hardware)

Name Function
Terminal Systems Linux OS-based gateway hardware system with intdash Edge Module incorporated

SDK / API (to be released soon)

Supply of technological resources

Development resources for an edge, server, and application will be delivered to those who develop a system or application using intdash.

SDK・API for development (to be released soon)

Name Function
Realtime API Relay broker of streaming data
REST API Server API for management of devices and stored time-series data
intdash Edge Module Software/library for embedded devices
intdash App Module Software/library for smartphones (iOS / Android)
Python SDK Python library for interactive analysis environment and Python implementation environment to Analytics Services by user