NeoBramPlan an AI project
    Industrial AI solution

    Construction Safety AI Computer Vision For EPC & Construction Sites

    Real-time AI detection of PPE non-compliance, fall risk, plant-pedestrian proximity, hazard zones and unsafe working-at-height across active construction and EPC sites.

    Plan the use case Explore ROI tools
    Construction site with AI safety monitoring cameras

    Acceptance before scale

    Baseline, representative test set, failure conditions and a named human owner are defined before production approval.

    Direct answer

    NeoBram delivers AI safety monitoring for construction and EPC sites - PPE and harness detection, plant-pedestrian proximity, fall-from-height risk, exclusion-zone intrusion and working-at-height monitoring - using rugged solar-powered edge cameras with cellular backhaul, integrated with your HSE management system.

    Private deployment available

    Why evaluate it

    Construction Is The Most Dangerous Industry.

    The decision is whether this capability improves a defined workflow safely not whether an AI demo looks impressive.

    Construction accounts for one in five workplace fatalities globally. Falls from height, plant-pedestrian incidents and struck-by events dominate the statistics - and most are preventable with earlier detection and intervention.

    We deploy rugged solar-powered edge cameras with cellular backhaul that go up in a day and move with the work front. Detections run on the camera (no cloud video upload), with alerts to site supervisors and structured incidents pushed to your HSE platform (SAP EHS, Enablon, Donesafe).

    Uncited universal benchmarks from the legacy page were withheld. Define the baseline and acceptance threshold from customer evidence or a reviewable primary source.

    Candidate capabilities

    What a production solution may need to do.

    Each capability is validated against representative data and the customer's workflow. Product or model names describe possible components, not partnerships, certifications or guaranteed compatibility.

    PPE & harness compliance

    Helmet, hi-vis, glasses, gloves, boots and harness detection across the active work-front. Harness-connected detection for working-at-height zones.

    • Helmet, hi-vis, glasses, gloves, boots detection
    • Harness-clipped detection at edge / working-at-height
    • Zone-specific PPE rules per work package
    • Contractor / subcontractor compliance breakdown

    Plant-pedestrian & exclusion zones

    Real-time proximity alerts between people and mobile plant (excavators, cranes, telehandlers, mobile elevating work platforms), and intrusion into exclusion zones around lifts and energised work.

    • Person-plant proximity sub-second alerts
    • Crane swing-radius exclusion zones
    • Energised-work and confined-space zones
    • Pedestrian-route compliance

    Fall-from-height & unsafe access

    Detect work-at-height without edge protection, unsafe ladder use, scaffolding access violations and roof-edge proximity - the top fatality cause on construction sites.

    • Working at height without harness clipped
    • Roof / edge proximity without barrier
    • Unsafe ladder angle and three-point contact
    • Scaffolding access without complete handrails

    HSE workflow & leading indicators

    Alerts to site supervisors via WhatsApp / Teams within seconds; structured incidents into SAP EHS or Enablon for investigation; leading-indicator dashboards for project, regional and corporate HSE.

    • Sub-30-second supervisor notification
    • Structured incident push to HSE platform
    • Project / regional / corporate dashboards
    • Trending across contractors and work packages

    Architecture context

    Select components after the boundary and test are clear.

    The list is a design vocabulary. Final selection depends on licences, data location, latency, security, existing systems and customer approval.

    Edge cameras

    • Solar + LTE rugged camera units

      Deploy without site power or network

    • PTZ for wide coverage

      Plant and access road monitoring

    • Fixed 4K for work-face

      PPE and proximity

    • Thermal for night and fire risk

      Overnight site security

    Detection models

    • YOLO v11 (custom-trained)

      PPE, plant, person detection

    • Pose estimation

      Working-at-height posture

    • Tracking (ByteTrack)

      Proximity over time

    • Geofencing per zone

      Exclusion zone logic

    Edge compute

    • NVIDIA Jetson Orin Nano / NX

      On-camera inference

    • DeepStream SDK

      Multi-stream pipelines

    • MQTT over LTE

      Event-only backhaul

    HSE integration

    • SAP EHS / Enablon / Donesafe

      Structured incident push

    • Procore / Autodesk Build

      Project context

    • WhatsApp / Teams

      Supervisor alerts

    • Power BI dashboards

      Leading-indicator KPIs

    Planning ranges

    A standard path from decision to operation.

    01

    Discovery and qualification

    1-2 weeks

    Named workflow, owner, baseline, risks and go/no-go questions.

    02

    Readiness assessment

    2-4 weeks

    Data, integration, security, value and operating-readiness findings.

    03

    Technical proof of value

    4-6 weeks

    A bounded test on representative data with documented limitations.

    04

    Production pilot

    8-12 weeks

    One controlled workflow, integrated and evaluated with real users.

    05

    Enterprise or multi-site rollout

    3-6+ months

    Phased scale-out, monitoring, support and change management.

    06

    AI capability or CoE programme

    3-6+ months

    Governance, delivery methods, reusable assets and team enablement.

    These are planning ranges, not guarantees. Readiness, validation, hardware, integration, access and change management affect the schedule.

    Production safeguards

    Private deployment is one control, not the whole control system.

    Data boundary

    • Select offline, edge, on-premises or private-cloud deployment from the real operating constraints.
    • Document data flows, storage, deletion, backups and support access before production.
    • The customer approves every interface and any permitted external connection.

    Model and application controls

    • Evaluate representative cases, uncertainty and harmful failure modes before use.
    • Use suitable access control, input handling and output guardrails for the selected risk.
    • Treat grounding and citations as testable behaviours, not as a promise of perfect answers.

    Traceability and operation

    • Define identity, roles, logs, monitoring, updates, backup and incident handling.
    • Keep the evidence needed to investigate outputs and reproduce important decisions.
    • Assign a named business and technical owner for production operation.

    Human authority

    • Domain, quality, safety and regulatory owners retain decision authority.
    • Compliance depends on the implemented system and the customer's validated controls.
    • Escalation and safe fallback are part of the acceptance criteria.

    Limitations to plan for

    Performance can change with data quality, equipment, process, product mix, documents, users or operating conditions. Third-party model and software licences still apply. AI output does not replace the responsible engineer, operator, quality owner, safety professional, legal adviser or regulator.

    Buyer questions

    Direct answers before you plan a pilot.

    How quickly can cameras be deployed on an active site?+
    A focused production pilot is commonly planned over 8 12 weeks after scope, representative data, owners and acceptance tests are ready. Discovery or a technical proof of value may be shorter; integration, validation, hardware, site access and change management can extend the plan. This is a planning range, not a delivery guarantee.
    Does this work at night and in dust / rain?+
    Yes. Cameras are IP66 / IP67 rated with IR illumination for night, and we add thermal cameras for fire-risk areas and overnight security. Models are trained on rainy, dusty and low-light footage so detection accuracy holds up in real site conditions, not just clean test data.
    How do you handle worker privacy and subcontractor concerns?+
    Faces are blurred by default in stored snapshots. The system reports compliance behaviour, not identities. We do not run facial recognition. Detection scope is agreed with the project HSE lead and communicated to the workforce as part of site induction. A DPIA is provided.
    How does this integrate with our HSE platform (SAP EHS, Enablon, Donesafe)?+
    Detections are pushed as structured events via REST API to SAP EHS, Enablon, Donesafe or your platform of choice, with category, location, snapshot URL and timestamp. The HSE platform remains your system of record; we feed the leading-indicator data into it.
    What ROI have EPC and construction clients seen?+
    There is no responsible universal ROI figure. Build the case from the selected workflow's baseline, error or downtime exposure, detectable opportunity, adoption, false-alert cost and full operating cost. NeoBram's calculators are illustrative planning tools; replace every assumption with customer evidence before an investment decision.
    What's the pilot model?+
    This legacy draft included a quantitative benchmark that has not been published with a reviewable source or customer evidence. NeoBram now treats it as an open validation question and defines the baseline, test method, acceptance threshold and limitations during discovery.

    Bring one workflow

    Define the evidence, boundary and acceptance test together.

    Your team supplies process authority. NeoBram supplies AI architecture, engineering, evaluation and operating handover.

    Plan the first project