Construction sites are places where construction equipment moves around.
Materials progress through delivery processes.
And, most importantly for this article: sensors can collect information about these moving parts and changes in the physical environment. The challenge is synthesizing that data into information actionable for a construction site's personnel.
This is where applying AIoT - yes, that's Artificial Intelligence of Things - can be helpful.
Instead of looking at AI and Internet of Things as separate things, AIoT considers connected physical objects and the application of analytics and artificial intelligence to extract value from that information
The Data Foundations: Physical Layer of an AIoT Architecture
IoT enables connecting objects and processes
A single construction operations system may include different technologies, each serving their specific purpose. For example:
RFID for tagging and identifying assets or materials
GPS/GNSS for location tracking of equipment and assets in open environments
BLE for indoor location and positioning
UWB for high precision positioning in appropriate environments
Sensors for collecting condition data
And more
These are not interchangeable technologies. Each has its strengths in different applications, and choosing one technology over another depends on the specific needs of a construction use case.
Perhaps in one scenario, GPS is perfectly acceptable for tracking a concrete truck's movement; in another, the precision offered by UWB would be preferable.
The engineering challenge may not always be in collecting additional data - it can be in selecting and connecting the most relevant data streams
Concrete Truck Example: Turning Disconnected Signals into Insights
Let's examine the example of a concrete truck delivery. An operations center has one data source showing when the delivery is supposed to happen; another source provides the truck's current location; and a third process identifies that the delivery has arrived at the jobsite. It's challenging to take these individual signals and derive meaning from them. With connected systems, this information can be pulled together:
Physical objects → sensors, tracking → connectivity → data → analytics → insights
Having access to these insights enables the potential for applying AIoT principles in construction. It is not that AI should be applied to every situation - in fact, any analytical process must begin with determining the question that needs to be answered. This example considers the question: When the truck arrives to deliver concrete, is the destination the correct location?
Turning the Data Volume into Value: What Can AI Enable?
IoT is great at collecting and sending data, but sometimes the sheer volume and variety of incoming information requires additional processing to identify trends or anomalies. This is where an AI layer - or an analytical layer - can be implemented to separate signal from the noise.
Use cases for an AI layer can include:
Equipment and asset scoring
Asset utilization analysis
Insights into material visibility and inventory management
Unusual operations scenarios
Correlation of information across different data sources
With that said, data is only as good as the information and context behind it. For developers and engineers working on IoT-connected construction sites, creating the proper data architecture is essential. It is one matter to identify where sensors or tracking devices should go, but building the infrastructure layer - sensors, gateways, connectivity, cloud data storage, API gateways, data science and AI models - that integrates and activates that data is what makes an AIoT system come together.
Location Tracking: The Right Answer to the Right Question
One common pitfall that teams looking at connected devices make is determining the purpose of a certain category of data. Instead of looking at an AIoT architecture and determining what data it could provide, construction personnel should ask what information would be needed to make a specific operational decision.
Does it matter if the excavator is at a specific location? Does it matter if it is being utilized? Does it matter if a concrete delivery is going to the correct place on the site? Does it matter if the equipment is beginning to exhibit abnormal conditions?
By knowing what question needs to be answered, the appropriate technology can be selected. There isn't any single technology that provides all the answers; in the article, we examine how RFID, GPS, BLE and UWB technologies support different aspects of an AIoT system.
The most valuable construction AIoT applications leverage existing resources: the connections and relationships between data sources, location tracking of assets, and applying logic and analysis from an AI layer to help construction professionals make better decisions.
As an experienced technology development firm, CommCon AI has extensive insight into the application of AI, IoT and related technologies to construction, manufacturing and logistics industries. For additional information on this subject, please visit https://commconai.com/.
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