Gain infinite insights from the edge.
SDT Cloud is an edge device and data management platform that brings immediate edge sensing, edge computing, and MLOps technology to industrial sites. SDT Cloud enhances existing industrial hardware with the power of AI, combined with SDT edge computing hardware. Focused on user experience, SDT Cloud can be installed very easily.
SDT Cloud puts users at the center. With SDT Cloud, unrestricted data flow and configuration from edge devices is possible. Significant data can be discovered for businesses without the need for data scientists or engineers. SDT Cloud allows users to intuitively control all edge devices and field data, from labeling in storage to machine learning-supported production insights.
By integrating edge connectivity from devices to the cloud into a single solution architecture, it maximizes the potential of data.
Background of SDT Cloud
The current industrial environment is highly fragmented. Various industrial sites are collecting data with diverse formats from hundreds or thousands of devices in completely different contexts through various methods.
In a world where the boundaries between industries are collapsing, companies can no longer survive if they are limited by the nature of the data they possess. Additionally, all companies are facing the challenge of finding ways to utilize the data generated in industrial sites as efficiently as possible. To address these concerns, SDT has developed a protocol library over several years by meeting various customers. Thus, SDT Cloud was born, which is an edge device and data management platform that consolidates fragmented data from industrial sites to derive insights.
Furthermore, using SDT Cloud allows for machine learning training and hardware deployment on-site. The machine learning models deployed in this way can provide new inference methods to the hardware and help gain new insights from existing data. Through the repetition of this process, SDT Cloud creates more accurate machine learning training models, making MLOps possible on-site without data scientists.
Experience insights into the hardware in industrial sites through SDT Cloud and introduce more efficient production methods.
Configuration of SDT Cloud
SDT Cloud performs the connection of hardware, data transmission, collection, storage, and visualization, as well as machine learning training and model creation accordingly. The machine learning models generated in this way can be deployed back to the original hardware, enabling continuous MLOps in industrial settings.
There may be times when the edge hardware solution needs to take action based on the information collected from the hardware.
For example, when the device is low on memory, when the CPU is too hot, or when the sensor detects a CO concentration above a certain level, notifications must be sent to the relevant parties. In such cases, SDT Cloud can automatically determine when and to whom notifications should be sent.
With SDT Cloud, precise rule settings based on edge data are possible.
SDT Cloud Compatibility
Multi Protocol
SDT Cloud supports industrial protocols such as Modbus, OPC, and Siemens S7, as well as general-purpose protocols like MQTT and AMQP, allowing connection to all SDT edge computing hardware and third-party hardware used in industrial sites.
Multi-cloud
All components of SDT Cloud operate on public clouds such as Amazon AWS and Microsoft Azure, and can interface with existing enterprise software such as MES, PLM, SCM, and ERP via APIs, enabling faster and more accurate business decision-making.
*The above image is material to aid understanding.
Please contact the sales department for specific compatibility needed for your environment (info@sdt.inc).
SDT Cloud realizes
the infinite potential of
edge devices.
SDT Cloud goes deeper and further than traditional edge management solutions.
Gartner predicts that "edge AI will remain in its early stages until 2025 due to a lack of knowledge and experience needed at the edge (embedded, devices, local servers, etc.)."
Customers have turned to SDT's edge hardware and connectivity expertise to escape the complexity of searching for countless partners for MLOps modeling and device management. With SDT Cloud, you can specify the onsite and offsite storage requirements tailored for users for continuous expansion. SDT Cloud provides convenient operations and data security across platforms as a standard. SDT's edge-to-cloud optimization technology maximizes the potential at customer sites, delivering greater value.
Experience all the capabilities of today’s edge without the constraints of resources and data silos.
BlokWorks Client
Standards for service requests and management
A component that collects over 5,000 data points per second* and transforms them into meaningful data for customers
[*Based on Modbus data]
BlokWorks
Standard for device management
A reliable system for connecting and synchronizing field devices for device and data orchestration.
Data Lake
Standard for Data Storage
Storage of structured data, unstructured data, and file-type data for machine learning.
CobiOps
MLOps of the Future
Based on the data collected on-site, we create machine learning models and deploy the generated models remotely to edge computing hardware for inference.
Scheduled to be announced
Add-ons for SDT Cloud
StackBase
It is a place where developers from around the world can share applications and create support platforms for edge devices.
There are many barriers to digitizing real environments in the cloud. Companies lacking hardware experience often fail to recognize the needs of real users and introduce software tools that are disconnected from critical issues. Traditional hardware companies are unable to provide assistance with problems occurring in the data pipeline from the edge to the cloud.
SDT Cloud addresses these issues through an end-to-end platform for digital transformation. Unlock all possibilities at the edge with SDT Cloud. Try to add value to your organization using devices. With SDT Cloud, you can build a device ecosystem for all production environments.
