The AMI-Lab platform integrates five interconnected layers — from physical sensors at the edge to semantic AI engines in the cloud. Each layer is built on open, interoperable technologies enabling scalable, self-managing ambient intelligence deployments in homes, hospitals, and cities.
Node Deployment Workflow
AmI-DEU lets domain experts — not developers — build IoT applications by describing user intentions in their own language. The framework compiles these into autonomous agents (IaaC) deployed directly on ContextAA across smart homes, hospitals, and cities.
ContextAA is the intelligent middleware at the heart of AMI-Lab — a distributed multi-agent platform that ensures service continuity as users move across smart homes, cities, and hospitals. It coordinates all IaaC agents compiled by AmI-DEU and provides the context-matching engine powering the entire platform.
Lexical → Syntactic → Reasoning → Planning → Interaction
Ambient intelligence without borders — home, city, hospital, mobile.
Deploys and coordinates all AmI-DEU IaaC mission agents in real time.
Universal ontology enabling interoperability across all IoT sources.
F-AMAD — Federated Learning Standardization
F-AMAD is AMI-Lab's federated learning standardization group — enabling privacy-preserving machine learning across distributed IoT nodes. Raw health data stays on-premise on each DomoSense gateway; only model updates are shared with the Hope server for aggregation.
Evaluates federated learning strategies across four dimensions — Algorithms, Metrics, Architectures, and Data Heterogeneity — in distributed IoT environments.
FL agents are deployed via AmI-DEU and coordinated by ContextAA. Local training runs on DomoSense nodes; global aggregation runs on Hope servers — 100% private.
Platform Infrastructure
All infrastructure projects →The Hope server cluster runs acquisition and visualization microservices in separate Kubernetes namespaces with a shared Elasticsearch backend. The Sentinel servers handle security, deployment, and self-healing across the entire node fleet.
Deployment Service ↗
- Ansible-driven automation
- Node provisioning & updates
- GitLab CI/CD integration
- Rollback capabilities
Security Service
- OpenVPN tunnel management
- DNS resolution control
- Node authentication
- Access policy enforcement
Self-Healing Service ↗
- Zabbix monitoring agents
- Anomaly detection & alerts
- Automatic service restart
- Health reporting to portal
Raspberry Pi-based smart gateway with multi-protocol sensor acquisition, semantic annotation, and cloud transmission via MQTT.
Kubernetes-orchestrated cluster using Elasticsearch for time-series storage, with multi-tenant Kibana visualization and Kong API gateway.
Automated deployment, security enforcement, and self-healing across the entire AMI-Lab node fleet using Ansible, Zabbix, and OpenVPN.
Distributed multi-agent middleware providing context-aware services across heterogeneous smart environments — from homes to smart cities.
Innovation platform supporting research prototyping, experimentation, and rapid evaluation of new ambient intelligence approaches.
Companion infrastructure platform for sensor integration and experimental IoT deployments supporting the broader AMI-Lab research ecosystem.