Using real-time computer vision
to decrease concrete pour delays

On a busy construction site, the gap between one concrete truck finishing and the next arriving is a window where work stops and
costs accumulate. A large construction company deployed AltaML's computer vision system to track every truck through every stage of
its cycle — so schedulers could call the next truck at exactly the right moment, without having to rely on rough estimates and "best guesses".

CLIENT

One of Canada's largest general contracting companies

PROJECT

Computer vision system for real-time concrete truck tracking and cycle time optimization

WHAT WE DID

Computer vision, machine learning model development, and on-site workflow integration

IMPACT

Real-time visibility into every truck's pour stage, tighter scheduling between arrivals, and reduced downtime on active sites

THE CHALLENGE

Concrete pours don't wait. Once work begins, the sequence of truck arrivals, pours, and turnarounds needs to run tightly. A truck arriving too early sits idle and blocks the site, a truck arriving too late means the crew stops working while the site waits. For our client, a leading North American construction company managing high-volume pours, truck cycle times had become a persistent source of operational drag.

Scheduling decisions were based on estimates rather than real-time visibility into where each truck was in its workflow. Without knowing whether a truck was still pouring, waiting for washout, or clear of the site, coordinators were calling trucks on guesswork, and the company was forced to absorb the delays that came with it. Idle crews, extended equipment rentals, and compounding schedule pressure all traced back to the same root cause: no reliable way to see what was happening on the site in real time.

THE SOLUTION

AltaML deployed a machine learning computer vision system designed specifically to identify, track, and monitor concrete trucks across every stage of their on-site workflow.

The system uses the cameras that are already present on a worksite to detect trucks as they enter, follow them through each stage — entering, pouring, and washout/completion — and provide schedulers with a real-time picture of where every truck stands in its cycle.

With that visibility, the coordination logic changes. Instead of calling the next truck based on an estimated finish time, schedulers can see when a truck is approaching completion and call the next arrival, eliminating idle time between pours and ensuring that no trucks stack up on site.

An added bonus? The system also contributes to site safety. Knowing the precise location and status of heavy vehicles on an active worksite reduces the coordination burden on ground crews and creates a clearer record of site activity throughout the pour.

Less downtime between pours Coordinators call trucks based on what's actually happening, not what's estimated, closing the gap between one truck clearing and the next arriving.

More efficient scheduling With accurate stage data, pour sequencing becomes a logistics problem rather than a guesswork problem. Coordinators can plan the next arrival precisely, reducing both idle time and site congestion.

Improved site safety

Real-time visibility into heavy vehicle position and status gives ground teams better situational awareness on an active pour site.

WHY IT MATTERS

Construction sites generate constant activity that is rarely fully visible to the people coordinating it. Most scheduling decisions are made on estimates, experience, and radio check-ins that are good enough for the company to function, but not tight enough to eliminate waste. Computer vision changes that. It gives the coordinator the information they're missing, in real time, so the decisions they're already making can be made with confidence rather than approximation.

Concrete truck cycle time is one application. The same underlying capability — to identify, track, monitor, and report on physical assets moving through defined workflow stages — applies across any high-activity construction environment where visibility translates directly into efficiency.

Using real-time computer vision
to decrease concrete pour delays

THE CHALLENGE

THE SOLUTION

WHY IT MATTERS

THIS IS WHAT PRODUCTION AI BUILT FOR CONSTRUCTION LOOKS LIKE.

Elevating human potential
with Agentic AI solutions

Using real-time computer visionto decrease concrete pour delays

THE CHALLENGE

THE SOLUTION

WHY IT MATTERS

THIS IS WHAT PRODUCTION AI BUILT FOR CONSTRUCTION LOOKS LIKE.

Elevating human potentialwith Agentic AI solutions

Using real-time computer vision
to decrease concrete pour delays

Elevating human potential
with Agentic AI solutions