The video begins with an installation segment guiding through prerequisites, installing MonkDB on a server (or edge), connecting the Pgwire and REST endpoints, configuring TLS. It then moves into data ingestion, showing how to connect to SCADA/Historian systems, sensor streams, RTLS tags, geospatial maps, documents and vector search inputs. Next it covers schema design and unified storage: how MonkDB handles SQL tables, time-series tables, vector indexes, document stores and geospatial layers all within one engine. The tutorial demonstrates writing queries across modalities (e.g., SQL + vector search for hyperspectral images, time-series analysis for ventilation fans) to extract insights. Further, it shows agent setup defining a MonkAgent, binding it to data sources, encoding domain logic (e.g., airflow/gas rules for mining), configuring decision policies, and deploying the agent in advisory mode. The video then transitions into semi-auto/closed-loop mode—how to shift from recommendations to automatic setpoint changes, monitor the loop, capture audit logs. Finally, the tutorial shows dashboard & analytics, M&V reports, compliance logs, traceability of decisions, and outlines best practices for scaling across sites.
How to install and configure MonkDB edge or on-prem.
How to connect multiple data sources (SCADA, sensors, RTLS, documents, vector data) and ingest them.
How to design unified multi-modal schemas: combining SQL, time-series, geospatial, vector and documents.
How to perform cross-modal queries and advanced analytics (e.g., “find all airflow anomalies in zones with RTLS delays”).
How to set up and deploy MonkAgent, encode domain logic, define automation phases (advisory → semi-auto → closed-loop).
How to tie actions to safety/compliance policy layers, capturing full audit trails.
How to build dashboards and reporting for energy savings, safety incidents, autonomous operations KPIs.
Best practices for scaling operations, governance, traceability and enterprise readiness of the engine.
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