New Jneopallium MQTT + Sparkplug B Bridge: Safe, Biologically-Inspired AI for Industrial Unified Namespaces

Hey HF community!

If you’re into neuromorphic / biologically-grounded AI and you also work with real-world industrial systems, I’m excited to share something fresh from the Jneopallium project. We just shipped a full-featured MQTT bridge (with native Sparkplug B support) that lets the Jneopallium neuron network act as a cognitive layer on top of any MQTT-based IIoT / unified-namespace architecture — while staying strictly advisory-only for safety. Why this mattersJneopallium is an open-source Java framework (BSD 3-Clause) that models natural neuron networks with typed signals, multi-receptor neurons, dual fast/slow processing loops, and built-in autonomous-AI safety (harm discriminator, hard constraints, transparency logging). The new MQTT bridge turns it into a drop-in cognitive engine for factories, energy plants, water utilities, etc.Key highlights of the bridge:

• Full Sparkplug B session state (NBIRTH/DBIRTH/NDATA/DDEATH/… + metric aliasing & wildcards)

• Plain MQTT JSON fallback for greenfield devices

• Structural ADVISORY ceiling — the aggregator never publishes to real DCMD actuator topics. All writes go to a configurable /advisory/ namespace so the HMI/operator stays in the loop.

• Per-binding SHADOW ADVISORY modes (AUTONOMOUS is rejected at config load time)

• Full audit trail (JSONL + optional MQTT mirror) with clamp, queue-full, and transport-failure records

• Quality & timestamp propagation from Sparkplug metrics

• Zero extra dependencies — everything is already in the worker artifact

Quick start (5 minutes)

yaml

# mqtt-bridge.yml
connection:
  brokerUrl: "ssl://broker.plant.local:8883"
sparkplug:
  enabled: true
  groupId: "Plant1"
  edgeNodeId: "Jneopallium-Edge-01"
  advisoryNamespace: "advisory"
reads:
  - bindingId: "TIC-101"
    sparkplugMetric: "Plant1/Edge-Reactor/Reactor1/temperature"
    signalTag: "PLANT.TIC101.PV"
    signalKind: MEASUREMENT
writes:
  - bindingId: "TIC-101-ADV"
    advisoryTopic: "spBv1.0/Plant1/DCMD/Edge-Reactor/Reactor1/advisory/setpoint_temperature"
    signalTag: "PLANT.TIC101.SP"
    minClampValue: 0.0
    maxClampValue: 100.0
    qos: 1
perTagSafetyMode:
  TIC-101-ADV: ADVISORY   # start in SHADOW, promote after validation

Then just wire it into your worker bootstrap (see the full manual in the repo). The bridge re-subscribes automatically on reconnects and plays nicely with the rest of the Jneopallium pipeline.How it fits the bigger pictureThe industrial-process-control module already ships oscillation monitoring, cascade-loop stabilization, and PID-style neurons. The MQTT bridge is the clean, auditable on-ramp that lets the network observe thousands of Sparkplug metrics and recommend setpoints without ever touching a real actuator. Perfect for shadow-mode pilots → advisory → (eventually) autonomous loops routed through OPC UA/PLC4X where safety demands it.We also have an optional LLM advisory layer (which can consume HF models via the existing integration) that can be cross-validated against the internal world model before any recommendation is emitted. So yes — you can literally bring your favorite HF model into the loop as a non-blocking knowledge source!Come play / contribute!

• Repo: https://github.com/rakovpublic/jneopallium

• Full MQTT manual (with bootstrap code, audit schema, session-state details, smoke-test instructions): docs in the repo + attached in the original release

• Looking for contributors in:

  • FPGA / gRPC deployment path (low-latency industrial edge)

  • Richer plain-MQTT JSONPath / schema support

  • More domain examples (energy, water, pharma)

  • HF model → Jneopallium neuron adapters

  • Performance benchmarks on real Sparkplug brokers (HiveMQ, EMQX, Mosquitto)

If you’ve built IIoT cognitive layers before, or you just want to try a biologically-plausible alternative to pure RL/LLM agents in industrial settings, I’d love to hear your thoughts! Drop a reply with:

• Your typical broker/stack (Mosquitto? HiveMQ Edge? Ignition?)

• Whether you need Sparkplug B or plain MQTT

• Any safety / audit requirements you care about

Happy to hop on a quick call or review PRs. Let’s make industrial AI safer and more brain-like together! (Full paper “Jneopallium: A Biologically Grounded Framework…” is also available if you want the 30 000 ft view of the whole architecture.) Looking forward to your feedback!