Build it as a distributed system, not a cloud dashboard with sensors attached. Connected devices sense and pre-process. Edge infrastructure on or near the site handles local, time-sensitive decisions. Cloud services take on storage, model training and orchestration. For each function, choose the layer by its latency, privacy, bandwidth, compute, interoperability, security and operations needs. Then link live system data to construction information through agreed data models and clearly defined properties.
The sources behind this guide are international standards and industry guidance, not construction case studies. They set out architecture principles and requirements. They do not give a commercial-construction bill of materials, and none of them validates a particular project design. The sections below separate what those sources establish from the project decisions you still have to make.
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What “AIoT architecture” means here
AIoT combines artificial intelligence with Internet of Things systems. ITU-T Recommendation Y.4618 (June 2026) is the most current formal reference. It describes AI, data and IoT functions distributed across devices, edge and cloud, and it allows those functions to be placed in a centralized or a distributed arrangement. The recommendation is titled Artificial intelligence of things: Reference model and requirements (ITU publication page).
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For a commercial construction project, this has a practical consequence. Cloud-only processing is one possible placement, not the default. A site can lose its uplink, and some decisions cannot wait for a round trip. Much of the design effort goes into deciding which functions stay close to the work and which move to shared infrastructure.
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Step 1: Define the jobs before choosing components
List what the system must do: sensing, monitoring, prediction, alerting, control and reporting. For each use case, write down four things:
- Who uses the output: site crew, superintendent, project engineer, owner’s representative, or an automated system.
- How quickly it is needed: immediately on site, within a shift, or in a periodic report.
- What happens if connectivity fails: keep operating locally, degrade, queue data, or stop.
- Whether a person must approve the action: automatic response, recommendation only, or human sign-off.
A simple worksheet makes the later placement decision much easier. The rows below are illustrative examples of how to fill it in, not a recommended scope.
| Illustrative use case | Who acts | Time sensitivity | If the uplink drops | Human approval |
|---|---|---|---|---|
| Alert when an equipment sensor reading crosses a limit | Site supervisor | Seconds to minutes | Alert must still fire locally | Person decides the response |
| Trend analysis of environmental readings across floors | Project engineer | Hours to days | Buffer readings and sync later | Not needed for analysis |
| Weekly progress and condition reporting to the owner | Owner’s representative | Periodic | Delay is tolerable | Review before release |
Your own list will differ. The point is that every row ends up with an explicit answer about latency, dependence on connectivity and authority to act.
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Step 2: Place functions across device, edge and cloud
Y.4618 describes a division of roles across the three environments. The table summarizes it.
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| Layer | Functions described in ITU-T Y.4618 | Typical fit in a construction deployment |
|---|---|---|
| Device | Lightweight AI, preprocessing, local inference | Filtering, thresholding and simple detection at the sensor or controller, so raw streams need not leave it |
| Edge | Contextual inference, coordination, management | Combining several devices’ data, applying site context, local decisions, managing the device fleet |
| Cloud | Storage, training, orchestration, model lifecycle | Long-term history, model training and versioning, cross-project analysis |
The third column is an interpretation, not wording from the standard. The standard defines the roles. Mapping them to a site is your design work.
How to decide where a function belongs
Device and edge processing can support local or time-sensitive decisions and reduce the amount of data transferred. Cloud services offer large-scale storage and computing. The trade-offs run along four axes:
- Latency: if the response must be quick or must survive a lost connection, move it toward the device or edge.
- Privacy: if data is sensitive, process it locally and send only what the cloud needs.
- Bandwidth: if streams are heavy and the site uplink is limited, summarize before sending.
- Computing capacity: if a model needs more compute than local hardware offers, or needs retraining on pooled data, keep that function in the cloud.
Most real systems will be hybrid, with inference near the work and training and archival in the cloud. That is a common outcome of the criteria above, not a rule from the standard. Y.4618 treats both centralized and distributed deployments as valid.
Step 3: Make data exchange explicit
A temperature value on its own tells a project team little. To combine live readings with construction and building information, each value needs a stable meaning, a unit, an identifier, and a relationship to the asset or space it describes. If these are left implicit, every integration becomes a one-off translation job.
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Two sources address this from different angles:
- AIOTI guidance (23 September 2022): its report on integrating IoT and edge computing in data spaces recommends a common language and common data models. It also covers the data lifecycle, curation, sovereignty and governance (AIOTI report page).
- ISO 23386:2020: this standard gives a construction-specific methodology for describing, authoring and maintaining properties in interconnected data dictionaries (ISO catalogue entry). It matters when sensor-derived properties must line up with the property definitions used in BIM and other digital construction processes.
In practice, this means agreeing early on a property naming and definition scheme and on identifiers for assets and spaces. Assign someone to maintain them as the project changes. Choosing a data format does not settle who owns the data, who may use it, or who is responsible for keeping definitions current. Those are governance questions, and AIOTI’s emphasis on sovereignty and governance points the same way.
Step 4: Build in security, privacy and operations
Y.4618 treats trust as a requirement of the architecture, not an add-on. Its text states: “AIoT systems are required to ensure end-to-end data security, trust, and privacy across devices, edge, and cloud.” The recommendation also covers:
- passwords, hardware and software integrity, and network resilience;
- model integrity, validation, versioning and auditability;
- secure updates;
- remote monitoring and diagnostics;
- service continuity.
The standard states requirements. Your project has to turn them into controls with named owners. A workable way to do that is to assign each requirement to a layer and to a responsible party:
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|---|---|
| Device integrity and credentials | How are devices provisioned, how are default passwords eliminated, and how is a replaced or lost device removed from the network? |
| Network resilience | What does each site function do on a degraded or lost connection, and how does it recover? |
| Model integrity and governance | Which model version is running where, who validated it, and can its decisions be audited afterward? |
| Secure updates | Who approves and deploys firmware and model updates, and how is a bad update rolled back? |
| Monitoring and diagnostics | Who sees device and edge health, who is on call, and what is the escalation path? |
| Privacy and data movement | What stays local, what is sent to the cloud, and who is permitted to see it? |
Construction adds an ownership problem. Devices may be installed by one contractor, the network supplied by another, and the platform run by a third party. If no one owns a layer, no one patches it. Settle the operational ownership of each layer in the contracts and handover documents, not after the first incident.
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Comparing architecture options on consistent axes
When you weigh alternatives, such as a cloud-centric, an edge-centric or a distributed design, score them on the same criteria. The sources describe alternatives and requirements. They do not name a winner, and none is universally best. The table frames the questions rather than answering them.
| Axis | Cloud-centric | Edge-centric | Distributed (device + edge + cloud) |
|---|---|---|---|
| Processing location | Mostly cloud | Mostly site-local | Split by function |
| Latency and connectivity dependence | Cloud round trips; depends on the uplink | Local decisions can continue during disconnection | Local for time-critical tasks; cloud for the rest |
| Privacy and data movement | More data leaves the site | Less data leaves the site | Designed per data type |
| Interoperability | Integration is centralized, but still needs shared data models | Local integration must map into shared models | Needs the clearest shared models across layers |
| Security and lifecycle | Fewer on-site assets to update | More on-site hardware to secure, update and monitor | Largest surface; needs end-to-end controls |
| Operational ownership | Concentrated with the platform operator | Falls to whoever runs the site infrastructure | Shared; must be assigned explicitly |
These cells are qualitative reasoning from the architecture principles above, not measured results.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Where physical edge hardware fits
The edge layer needs a physical home. An industrial IoT gateway is one product category to investigate for it. The ITU architecture supports an edge layer but does not name a gateway model, and it does not establish that any product suits a construction site. Treat a specific product as something to evaluate, not as part of the standard.
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- Protocols and interfaces: does it speak the protocols your sensors and equipment actually use, and can it forward data to your platform?
- Compute and storage: can it run the local inference you assigned to the edge and buffer data during an outage?
- Secure update and management: can you patch it remotely, verify what is running on it, and monitor its health?
- Environmental rating: is it rated for dust, moisture, temperature range and vibration where it will sit, and for power conditions on site?
- Connectivity: what uplink options does it support, and how does it behave when they fail?
- Compatibility: does it work with your devices, your data model and your platform without custom glue that nobody will maintain?
What the evidence does and does not establish
The three sources establish a layered reference model, a set of trust and operations requirements, and the importance of shared data models and construction property definitions. They do not supply performance figures. No market-size, cost-saving, productivity, safety or energy-saving number appears in them, and this article gives none. If a vendor quotes one, ask for the original publisher and the conditions of measurement.
The standards also do not tell you which use cases will pay off on your project. That judgment comes from the worksheet in Step 1, tested against your site’s connectivity, contracts and team.
A reasonable order of work follows from the above. Define the use cases, assign each function a layer, agree the data definitions, set the security and operational controls with named owners, and only then select hardware and platforms.
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