Edge Intelligence Modules
Turn visibility into action at the edge.
Modern supply chains don’t struggle with data collection. They struggle with what to do with it.
A modular approach to real-world operations
Midmo’s Edge Intelligence Modules extend MotionView beyond connectivity, bringing context, decisioning, and automation directly to where work happens.
Instead of pushing raw data upstream and reacting later, these modules enable real-time interpretation of events across RFID, vision, BLE, GPS, and other sensing technologies, right at the edge.
Edge Intelligence Modules are designed to be deployed individually or combined, depending on the environment and use case. Whether you’re validating shipments at a dock door, monitoring WIP on a production line, or orchestrating autonomous movements across a facility, each module builds on the same foundation:
• Item-level awareness with parent-child relationships
• Sensor fusion across multiple technologies
• Direct integration into workflows, transactions, and enterprise systems
No rip-and-replace. No single-use solutions. Just an extensible layer that evolves with your operation.
This is where signals become decisions.
Connect. Interpret. Act.
MotionView structures edge data into meaningful events, combining identification, condition, and movement into a single operational view. From dock doors to production lines to in-transit visibility, every interaction is captured, validated, and ready to trigger action.
Core Edge Intelligence Modules
Sentient Mode
Transforms handheld and fixed devices into always-on sensing infrastructure.
Convert chokepoints like dock doors and corridors into persistent visibility zones without requiring additional hardware layers or manual interaction.
SmartEvents
urns real-time signals into triggered workflows.
Define rules, thresholds, and patterns that initiate actions, whether it’s exception handling, validation, or process enforcement.
Edge Autonomy
Ensures operations continue without disruption.
Maintain local decision-making and execution when cloud connectivity is unavailable, keeping workflows active and reliable at all times..
LoadAware
Understands how items move through operations.
Combines vision and edge intelligence to track handling, staging, and loading activity, improving throughput, validation, and operational awareness.
Item Performance Profile (IPP)
Continuously improves accuracy and performance.
Builds intelligence around how items behave in real-world conditions, optimizing read performance and identifying anomalies across workflows.
FusionSense
Unifies multiple sensing technologies into a single operational view.
Combines RFID, vision, BLE, GPS, and environmental data into structured events that represent both movement and condition in real time.
ConditionGuard
Monitors and enforces environmental thresholds.
Track temperature, shock, light, humidity, and other conditions, triggering alerts and workflows when thresholds are exceeded.
FlowState
Aligns execution with intended workflows.
Tracks process progression, identifies breakdowns, and ensures operations are performing as designed across facilities and teams.
Human Assist
Supports operators with real-time guidance.
Provides context-aware prompts, validation, and next-step recommendations to reduce errors and improve execution on the floor.
ActionBridge
Connects edge intelligence to enterprise systems.
Delivers clean, structured data into WMS, ERP, analytics platforms, or AI agents, ensuring edge activity is immediately usable upstream.
Built to connect. Designed for extensibility. Let’s get started.
Midmo’s architecture is intentionally designed to support all types of connected deployments. Edge Intelligence Modules act as building blocks, enabling our customers and solution providers to tailor outcomes without rebuilding infrastructure for every new project.
This aligns with MotionView’s role as the connective layer between edge technologies and enterprise systems, simplifying integration while expanding capability. Deploy Edge Intelligence Modules as part of your MotionView environment and begin turning real-time signals into operational outcomes.