ATSS's platforms are built to handle massive scale processing of real-time data from IoT devices, AI systems, Cameras, and anything else that connects the physical and digital worlds and deploys it anywhere in the environment. Go from ideation to full scale production in a fraction of the time, cost, and resources.
Real-Time Applications are applications that operate within an immediate time frame; sensing, analyzing, and acting on streaming data as it happens. This is in contrast to a database- centric application where information is ingested and stored in a database (in the cloud or on-premise) for future analysis. Most real-time applications rely on an event-driven architecture (EDA) to allow for asynchronous processing of streaming data. These applications are vital in industries where operating within a specific time constraint can mean life or death; such as identifying and repairing a gas leak at an oil refinery or locating a lost child at a public park.
Increased Situational Awareness
Quickly and easily understand what is going on in and around your business at any given moment.
Naturally Leverage IoT Devices & Sensors
IoT needs real-time applications in order to efficiently process large amounts of streaming data and take immediate action.
Better Decision Making Capabilities
Put more information directly at your fingertips through the use of smart dashboards, real-time notifications, digital twins, human- machine collaboration, and more.
Greater Operational Responsiveness
Respond to mission-critical events as they happen instead of after the fact through real-time analysis and response to streaming data.
High Scalability
Process data close to the source to scale without limits, and massively decrease bandwidth utilization.
Low Latency Edge Processing
Real-time applications enable very low latency data ingestion and analysis to fully leverage the benefits of edge computing.
A lot has changed since businesses began developing mission- critical applications using a database as the central location for ingesting, storing, analyzing, and exporting virtually everything going in and out of the business.
The problem is, as businesses become more distributed and the world more fast-paced, more types of data need to be analyzed and integrated in real time; a much more agile and responsive application architecture is required in order to simply keep up, let alone get ahead. It’s time to ditch the database and transition to event-driven architecture.
Event-driven architecture(EDA) is software development paradigm in which the application is laid out as a series of commands, events, and reactions. This is in contrast to a database- centric approach, where incoming data is stored in a database and then called upon later for further analysis.
An event, in this case, is any situation of interest that is generated with the use of Internet of Things (IoT) sensors, user-driven interfaces, camera and object recognition systems, and many more sensory mechanisms in the modern enterprise.
By switching to an event-driven approach, organizations can undergo digital transformation much easier, incorporating new technologies such as artificial intelligence, digital twins, edge computing, and more into new or already existing applications.
Real Time
Process and respond to streaming data as it occurs, reducing bottlenecks and increasing application efficiency
Asynchronous
Ingest events without blocking, no matter when they arrive or how frequently to enable dynamic, highly scalable processing
Loosely Coupled
The ability for systems to be modular so there aren’t dependencies, allowing for a more dynamic and fault-tolerant architecture
Agile
Respond quickly to a constantly changing environment. The decoupled/distributed nature of event-driven applications makes adding new modules and integrating multiple applications easier.
Scalable
Parallel, asynchronous processing allows for massive scalability to handle large quantities of streaming data
Interoperable
Effectively communicate and coordinate business events across previously disparate enterprise systems
As businesses are forced to adapt faster than ever to the constantly changing world that we live in, the need for a computing topology that allows for real-time responsiveness, minimal to no latency, increased data security, massive scalability, and more, is an absolute necessity to stay ahead of the competition.
Edge computing enables data to be processed as close to the things and people producing or consuming that information as possible, allowing for a faster response to streaming data.
Edge Computing is a networking topology that allows for the placement of compute power close to the devices and sensors that make up the Internet of Things. These devices are often away from the data center out in the “real world”.
Analysis occurs locally, on large sets of data without incurring the latency overhead that would be experienced if this analysis needed to be done in the cloud. Local connectivity also adds higher resiliency and ensures better responsiveness to critical situations, ensuring large volumes of data can be analyzed and scrubbed with only interesting data being sent to the cloud for additional analysis.
Real-Time Responsiveness
Respond to streaming data as it occurs without latency concerns, utilizing mesh architectures to enable simultaneous computing capabilities
Resiliency
Ensure the operation of and communication between edge devices continues even when connection to the internet is lost or is temporarily unavailable
Increased Data Security & Privacy
Locally process sensitive information directly on edge devices to limit both the amount of data transmitted back to data centers and data at risk in any one location
Scalability
Quickly iterate, expand, and evolve edge applications as requirements change or operations grow without needing to go back to the drawing board
Embedded Intelligence
Utilize increased local processing power to run more sophisticated and intelligent features directly on devices, at the source of data
Data Efficiency
Decentralize data processing to run as close to the source as possible and filter unnecessary data before sending back to the main system
A digital twin is a digital copy or replica of a physical object. In the past, digital twins have been used to test and monitor objects such as engines or manufacturing line components. Next-generation digital twins are being implemented on entire spaces such as a building or city park.
Digital twin technology combined with a real-time event-driven application allows for not only visualizing but taking real-time action on important business events.
Digital Twin Technology is a way of representing complex physical environments digitally such as a large building, factory, airport, or an oil refinery, through this we can monitor and control things in new and innovative ways.
Digital Twins analyze and act to address complex problems such as a flood, a major traffic accident, a factory breakdown, or suspicious behavior in an airport, all in real- time. Powerful simulations can also be run to prepare for such events in advance.
Leading companies spanning all major industries can benefit from implementing Digital Twin Technology powered by real-time applications that connect the physical and digital worlds.
Visualize Entire Spaces
Visualize large spaces such as a building complex or factory floor, or combine multiple digital twins to build an entire smart city
Manage Assets in Real Time
Gain a complete picture of everything happening in and around your organization, with the ability to view streaming data in as much or as little detail as necessary
Improve Efficiency and Productivity
Combine visualization, simulation, and real-time technology to reduce time to decision and increase the flow of business events
Orchestrate Between Systems
Contextualize data across previously disparate business systems via the shared framework that a digital twin provides
Run Powerful Simulations
Simulate different business events or configurations of equipment to maximize efficiency and prepare for the unexpected
Unlock New Business Opportunities
Utilize digital twin models to explore different outcomes, test new revenue streams, and increase organizational agility
In accordance with Gartner's perspective, a digital business technology platform embodies the fusion of technologies that empower an organization to deliver digital business capabilities. It essentially functions as the nerve center of a contemporary enterprise, adeptly ingesting streaming data, conducting real-time analysis, and orchestrating immediate actions in response to critical business events.
An ATSS digital business technology platform seamlessly integrates existing IT infrastructure and business assets, fostering the creation and exchange of services. The consolidation of operations within a centralized platform offers substantial advantages in terms of scalability, operational efficiency, situational awareness, and more. Below, explore a selection of the manifold ways in which an ATSS digital business technology platform serves as a catalyst for digital transformation.