Our platform’s core task is ensuring the right notifications and alerts from a range of sensors and data sources reach the right person at precisely the right time.
Delivering real-time data insight within IoT requires robust event handling. The way in which the Dele platform handles events, commands, and queries is key to it handling large data volumes data in real-time.
The DELE IoT Platform has been developed with an open standards, user-centric approach to ensure integrations are seamless with the customer’s cloud solution.
Our platform is modular, ensuring you can grow with the solution.
An intuitive user interface makes it easy to integrate new hardware, third-party systems and other software solutions central to your environment.
All Dele software is easily scalable and can be used by organizations of any size.
IoT has gone from an early stage technology enthusiasm to become more mature as today’s solutions need to handle increased data streams effectively as well as economically.
A key challenge for most IoT Platforms is how data is processed and distributed. Edge processing of data is necessary to ensure that solutions can handle increasing data streams.
The DELE IoT platform is made scalable, and it has been tested in environments with as much as 500 million events per second.
Setting up an IoT solution is not trivial. There are many choices, and one of the most important features for any type of IoT solution, is how easily the solution integrates across an organization’s other IT infrastructure, systems and solutions.
We have this aspect central to the DELE IoT Platform through our easy cross-platform deployment features. We also have an open standard API library that easily lets you integrate the DELE IoT Platform with the most common systems and solutions. We keep adding new APIs to our library, so please get in touch with us for a complete list.
Another key component of IoT solutions is if they are built to scale. If the data flow is not designed properly, the costs from running the solution soon will sky-rocket. Therefore, we have ensured we process as much data as possible on the edge.
Events are optionally evaluated and processed at the edge, as we sometimes have to react in near real-time. Events are pushed on the event bus. Stream processes listen to the events and process them into insights (could be trivial archiving or advanced machine learning).
Commands are evaluated and processed at the edge, as edge servers typically have access to distributed data that allows them to make decisions in near real-time. The request and the response are pushed to the event layer. Stream processes commands as events.
Queries are often simple lookups of precalculated results. We offer a query-first design of databases stored in a database perfect for the result type. The Query Path we use ensures queries received at the edge.