IoT & Edge
This session will walk through several reference architectures that solve common edge and IoT situations. The audience will gain a solid understanding of how to place many popular Eclipse IoT technologies in a software stack and form a complete set of solutions.
Environment perception is an important aspect of reliable and safe autonomous driving for automated vehicles. Typical AD software stacks provide localization, object detection and tracking using and array of sensor data. Sensor data is complemented with other information arriving from V2X connectivity, passenger behavior, person-to-device mapping and other networked data such as the urban context, degradation of traffic etc.
While Fog computing aims at providing horizontal, system-level, abstractions to distribute computing, storage, control and networking functions closer to the user along a cloud-to-thing continuum.
Whilst fog computing is increasingly recognized as the key paradigm at the foundation of Consumer and Industrial Internet of Things (IoT), most of the initiatives on fog computing focus on bringing cloud infrastructure to the edge of the nework.
Making the right data available at the right time, at the right place, securely, efficiently, whilst promoting interoperability, is a key need for virtually any IoT application. After all, IoT is about leveraging access to data – that used to be unavailable – to improve the ability to react, manage, predict and preserve a cyber-physical system.
With the raise of Edge and Fog Computing there is a growing need to maintain data locally, or at least as close as possible to where it is produced, while at the same time making it accessible globally. Yet, existing storage technologies are geared toward cloud-centric deployments, in which a pool of servers is used to shard and replicate the data. As a result there is a mismatch between the storage needs of Edge and Fog Computing applications and available technologies.
Today's development of embedded systems/IoTs and SOCs (Systems on Chip) faces the problem of a rapidly growing complexity.
Due to the decentralised nature of the development (multiple cores on external boards, specific hardware components, external communication interfaces, simulated components,...) it is difficult to visualize, debug and understand the behavior.
The information to be processed differs in nature:
Eclipse Kura recently celebrated its 5th birthday and ever since its early days, it has proven to be a very versatile and open framework for connecting IoT devices to enterprise systems. Thanks to the modularity of the Kura framework, gateways can be connected to a wide variety of backend servers, from barebones MQTT brokers such as Eclipse Mosquitto to more complete IoT platforms such as Eclipse Kapua, Azure IoT, and many others.
IoT is everywhere and the diversity of devices and sensors is overwhelming.
This leads to difficulties with the massive amount of different payload formats, APIs, and proprietary protocols.
The main issue is how to ensure that this diversity of connected devices can seamlessly communicate with platforms and applications, regardless of the different technologies, and systems.
In this session, we will talk about payload mapping with the open-source project Eclipse Vorto, which solves exactly these types of problems.