Smarter Infrastructure Starts Here — How Wi-Fi HaLow™, Distributed AI & Digital Twins Work Together

marleen75
Sep 26
3 min read

Updated: Oct 14

AI, Digital Twin and secure long-range connectivity are topics that are more and more frequent in the industrial world every day.

Distributed AI brings data processing, outcome predicting and decision making based on pre-trained models across multiple devices and nodes. Each part of the system collaborates and is involved in local decision making, which optimizes performance in real-time.
Digital Twin creates a virtual representation of a physical system or object which follows real-time system condition, data, performance and behavior. Information is utilized to analyze anomalies in behavior, predict scenarios and failures, optimize processes and much more.
Wi-Fi HaLow™ provides long-range, low-power and highly secure connectivity with signal that can penetrate through materials even in challenging environments.

What happens when you combine these three advanced digital technologies, not only in a single cloud, but across every layer of operation? Then you get the future of smart systems, which is a powerful three-tier architecture that distributes intelligence where it's most needed.

This concept can be used in many different applications. To explain possibilities and benefits that this concept provides, it will be illustrated through a real-world example of large water supply network that consists of hundreds of industrial pumps across wide area.

Tier 1: The Edge Device — The Pump Itself

Each pump becomes a smart unit in a system, equipped with a microcontroller connected to a set of various sensors for following critical parameters, such as pressure, flow, power usage and vibration. Steps that ensure seamless operation are:

Constant real-time sensor readings — reduced time in reacting to a sudden changes in critical parameters
Local data processing — AI model collects data and processes it directly on the device without adding delay for data transfer to main brain of the system
Anomaly detection — models are trained to react to unusual operating patterns, predict potential failures and trigger the alert for action before it occurs.

Tier 2: The Edge Gateway — Data Aggregator

Edge gateway, an industrial computer placed in locations with a cluster of pumps, collects the summary data and alerts from all the nearby devices. This part of system:

Aggregates alerts and data — all nearby devices send data to Edge Gateway for more advanced processing
Uses stronger AI model — analyzes long-term trends that AI in smaller device might miss
Shifts maintenance from reactive to predictive — focuses less on real-time emergencies and more on predictive maintenance and optimization to save repair costs in case of failures and system downtime
Prevents failure spreading — sends alert if error that occurred on one Edge Device might cause failure on other Edge Devices
Optimizes local operations — calculates the most power efficient operation mode for expected output (for example, running two pumps to the same spot at half power might consume less energy that running only one pump at full power)

Tier 3: The Cloud — The Digital Twin

The highest level of intelligence is Digital Twin. A virtual replica of the entire system is created for running the most powerful and complex AI model for:

Collecting data from all Edge Gateways — gathers all of the data from a vast area in one place
Identifies macro trends — important step for detecting possible problems which cannot be detected on local level (for example, specific pumps or sensor models might be failing more frequently)

This tier also provides strategic capabilities such as:

Predictive planning — creates a long-term plan for replacing all of the models with the risk of failing to prevent overall downtime
System-wide efficiency — analyzes water consumption patterns across the city and adjust the water delivering schedules of all pumps to reduce energy costs during peak hours.
Simulation and scenario testing — simulates changes of new infrastructure to see its performances and impact on the entire network before physical deployment

Why This Architecture is the Future

This three-tier approach offers the best of all worlds:

The Edge Device provides speed and autonomy for crucial immediate decisions
The Edge Gateway provides predictive insights and local resilience
The Cloud provides global oversight and strategic optimization

Combined together, they create smart system for smart infrastructures that adapts to changes, prevents failures and makes decisions over a large area.

This is not just evolution—it’s revolution.

Smarter Infrastructure Starts Here — How Wi-Fi HaLow™, Distributed AI & Digital Twins Work Together

Distributed AI brings data processing, outcome predicting and decision making based on pre-trained models across multiple devices and nodes. Each part of the system collaborates and is involved in local decision making, which optimizes performance in real-time.

Digital Twin creates a virtual representation of a physical system or object which follows real-time system condition, data, performance and behavior. Information is utilized to analyze anomalies in behavior, predict scenarios and failures, optimize processes and much more.

Wi-Fi HaLow™ provides long-range, low-power and highly secure connectivity with signal that can penetrate through materials even in challenging environments.

Tier 1: The Edge Device — The Pump Itself

Constant real-time sensor readings — reduced time in reacting to a sudden changes in critical parameters

Local data processing — AI model collects data and processes it directly on the device without adding delay for data transfer to main brain of the system

Anomaly detection — models are trained to react to unusual operating patterns, predict potential failures and trigger the alert for action before it occurs.

Tier 2: The Edge Gateway — Data Aggregator

Aggregates alerts and data — all nearby devices send data to Edge Gateway for more advanced processing

Uses stronger AI model — analyzes long-term trends that AI in smaller device might miss

Prevents failure spreading — sends alert if error that occurred on one Edge Device might cause failure on other Edge Devices

Optimizes local operations — calculates the most power efficient operation mode for expected output (for example, running two pumps to the same spot at half power might consume less energy that running only one pump at full power)

Tier 3: The Cloud — The Digital Twin

Collecting data from all Edge Gateways — gathers all of the data from a vast area in one place

Identifies macro trends — important step for detecting possible problems which cannot be detected on local level (for example, specific pumps or sensor models might be failing more frequently)

Predictive planning — creates a long-term plan for replacing all of the models with the risk of failing to prevent overall downtime

System-wide efficiency — analyzes water consumption patterns across the city and adjust the water delivering schedules of all pumps to reduce energy costs during peak hours.

Simulation and scenario testing — simulates changes of new infrastructure to see its performances and impact on the entire network before physical deployment

Why This Architecture is the Future

Related Posts