Systems integration in commercial construction remains a challenge.
While a technology landscape may include BIM, ERP, CMMS, project controls, field systems, and connected devices; despite the fact each may operate perfectly independently; data from one cannot easily be used by another without significant effort. AIoT can be seen as a means of addressing this challenge through connection between physical signals from the job site to systems that are already in existence:
The Architecture Begins With Context
An organization’s connected job site environment may appear structurally like this:
1. Physical Layer
This describes where data originates from. This could be:
Equipment
Materials
Assets
People
Facilities
Sensors
Connected devices
This layer provides the basic signals; such as activity, location, status, and other on the ground intelligence.
2. Data Layer
Once these raw physical signals are collected, organizing them is the first difficulty; otherwise you will only wind up with another isolated data store. In this layer, the AIoT system must first attempt to build useful relationships to the entity they describe.
3. Systems Layer
Construction organizations will likely already have their own various systems containing existing context:
BIM
ERP
CMMS
Project controls
Project management systems
Integration here provides access to that context so physical data can be considered amongst it.
4. Intelligence Layer
Once the data is connected to systems the organization already owns, various analytics or AI functions can potentially aid in identifying the trends, relationships and conditional information that would be otherwise difficult for an organization to derive from individual sources. It’s not about having intelligence for the sake of intelligence. The context derived from intelligence, is what’s valuable.
Connectivity is More Complicated Than Data Collection
When trying to apply technology, much of the complexity lies not within collecting the signals, but the determination of their meaning. A signal indicating location at the job site might appear to project managers to be information useful to know; however without further context it's only useful to understand equipment's whereabouts as it is, and not its role: is equipment at the location of active work, is equipment not at the site because it's offline or has needed a repair, does equipment at that location serve some specific purpose that's relevant to on-site productivity etc? This can only be achieved by consideration to both the technical and information architecture.
BIM provides a Contextual Wrapper
BIM can be seen as giving digital context to the physical environment. When any jobsite data can be correctly associated to appropriate portions or locations of the project, location/activity data can yield powerful information. Similar principles apply to information within ER, CMMS, and Project controls systems that are to be linked to the physical jobsite data.
ERP data provide business context, CMMS provide maintenance and upkeep, and project controls provide schedule context that relates to how the signal potentially effects the job schedule.
A smart connection of these disparate points provides context.
A Plausible Integration Architecture
The architecture should intuitively read as follows, though is customizable to each organization:
``text
Physical Jobsite
Connected Signals
Data & Entity Context
BIM / ERP / CMMS / Project Controls
Operational Intelligence
Decision & Action
``
The specific, technical architectural needs of each case will vary by job, project, or technology architecture; however the architectural logic of needing to translate physical data through contextual information is a sound approach for most applications. This way the signal from a piece of equipment does more for the organization than provide a point in time physical record.
Asking Questions First
A purely systems-centric implementation could quickly get out of control. The appropriate answer begins not with the implementation method, but rather the decision that a user/process wants to achieve a certain outcome. "I'm seeing too many down machines," "We don't know if we have capacity for the next two job phases" are excellent starting points that give organizations a clear decision process and a logical target.
With that target the relevant questions can begin: "where in the organization will this data be provided to me?"
"where in the organization does the data relating to my question reside currently?" "what field signals could be added to provide more accurate intelligence regarding the question I'm trying to resolve?" The answers will inevitably require connecting multiple information sources from a connected job site system.
Progress toward Jobsite Intelligence
A highly connected system can achieve many different things for a project beyond simply collecting data in one location. In many cases the idea of becoming wholly integrated through Aiot on a job site and creating a universal construction database is not entirely practical or needed. What can be more realistic and pragmatic for organizations is to create relationships between systems that allow for specific decisions to be made.
The signal context, leads to a decision/action.
For teams currently in the process of exploring what an Aiot strategy would look like, additional guidance for the systems integration process for BIM, ER, CMMS and project controls along with job site intelligence is available at commercial construction aiot systems integration It can likely only become more important moving forward that the intelligence of an organization not come from the largest number of connected devices, yet how much those devices integrate into business context. For more info visit: commconAI.com
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