The Internet of Things (IoT), as a cornerstone of digitalization and data-driven business models, has successfully spawned cloud-centric approaches where IoT cloud platforms are central points of data collection and processing.
This cloud-centric IoT model however has limitations:
(i) unreliable cloud connectivity impedes dependable end-to-end applications,
(ii) limited bandwidth restricts the amount of data that can be processed,
(iii) high round-trip times prevent real-time operation,
(iv) high cost of data transport and intake, and
(v) privacy and trust concerns.
IntellIoT focuses on: Agriculture, where farming machinery (e.g. tractors) is semi-autonomously operated in conjunction with supporting devices. Healthcare, where patients are monitored by sensors to receive instantaneous healthcare advice and interventions from virtual advisors. Manufacturing, where plants are highly automated and shared by multiple tenants who utilize machinery from third-party vendors.
In all three use case areas, a human expert plays a key role in controlling and teaching the AI-enabled autonomous systems, for instance since clinicians need to monitor plausibility of the AI, when autonomous agricultural vehicles encounter unknown obstacles, and when manufacturing systems deal with novel production contexts.
Objective 1: Create a self-aware and semi-autonomous multi-agent system over an optimized computation and communication infrastructure that manages compositions of IoT/edge devices in closed-loop with the network.
Objective 2: Enable ultra-reliable low-latency communication over heterogeneous networks to enable tactile (real-time) and contextual (adaptive) interaction between IoT devices, humans, and services.
Objective 3: Enable semi-autonomous IoT applications by leveraging distributed AI algorithms under compute, storage, mobility and bandwidth constraints and by integrating the human-in-the-loop for safety, assistance and continuous improvement of AI.
Objective 4: Enable security, privacy and trust by design with continuous assurance monitoring, assessment and certification as an integral part of the system, providing trustworthy integration of third party IoT devices and services.
Objective 5: Development of a reference implementation of the IntellIoT framework, demonstrated and evaluated in the three use case areas: agriculture, healthcare and manufacturing.
Objective 6: Promote and exploit the IntellIoT framework through contribution to standards and open source as well as by building an active IoT ecosystem supported by two Open Calls and focused dissemination and exploitation activities.
