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  • Achieving 10x Faster Solar Construction Monitoring With Drone-Based GeoAI and Snowflake Dashboards

    Achieving 10x Faster Solar Construction Monitoring With Drone-Based GeoAI and Snowflake Dashboards

Client

The client is one of the largest renewable energy providers in the Middle East. It focuses on utility-scale solar infrastructure and full-spectrum engineering, procurement, and construction (EPC) operations. Managing multiple large-scale solar farms across the region, the organization is pivotal in advancing national clean energy goals.

With increasing pressure to meet aggressive sustainability targets and expand capacity, the client required a more intelligent and scalable way to monitor construction progress across remote project sites. One that could reduce manual effort, enhance traceability, and deliver real-time insights at scale.

Market Trends in Utility-Scale Solar Infrastructure

The Middle East is emerging as a global leader in solar energy, driven by government-backed sustainability targets and some of the world’s most ambitious utility-scale projects. Large-scale deployments across desert terrains demand smarter construction, monitoring, and compliance approaches.

Solar developers increasingly turn to advanced technologies such as drone-based monitoring, AI-driven analytics, and cloud-based dashboards to maintain efficiency and meet delivery milestones. These innovations help address persistent challenges, from labor-intensive inspections and inconsistent reporting to site accessibility and audit readiness, while enabling faster, data-informed decision-making.


Market Trends in Utility-Scale Solar Infrastructure

Challenges

  • Manual monitoring slowed project velocity
    Construction progress relied on physical site visits and manual audits, which consumed up to 10 person-days per cycle. This delayed reporting and created bottlenecks such as delayed resource allocation, postponed quality inspections, and hold-ups in contractor approvals during critical execution phases.
  • Lack of real-time project visibility across sites
    Data such as pile counts, module installation progress, and inverter station status from multiple solar farms were collected and reported inconsistently, making it difficult for decision-makers to track progress or identify delays confidently.
  • Inconsistent quality checks and high subjectivity
    On-ground inspections lacked standardization and varied by inspector, leading to discrepancies such as miscounted installations, undocumented anomalies, and missed defect flags, which resulted in rework and compliance risks.
  • Delayed reporting and fragmented data
    Progress updates were difficult to consolidate across geographically dispersed fields, limiting timely insights such as site readiness or deviation from plans, and slowing the escalation of issues like installation errors or missed milestones.
  • Limited traceability for audits and compliance
    Without a centralized system to log construction milestones and inspection data, the client faced challenges meeting documentation requirements such as audit trails, timestamped validations, and progress certification for regulatory review.

LTIMindtree Solution

LTIMindtree deployed a drone-integrated, GeoAI-powered Smart Construction Monitoring platform tailored for solar infrastructure projects. The platform is designed to automate progress audits, enhance visibility, and drive consistency across large-scale project sites.

 
AI-based object detection trained for solar construction

AI-based object detection trained for solar construction

Computer vision models were developed to detect solar-specific components such as pile foundations, PV module structures, inverter stations, and mounting systems. This enables the automated tracking of construction milestones with high accuracy.

Drone-based orthophotos for spatially accurate monitoring

Drone-based orthophotos for spatially accurate monitoring

High-resolution drone imagery was used to create orthomosaic maps of construction sites, offering centimeter-level accuracy and eliminating the need for frequent on-ground inspections.

Digital KPIs mapped to engineering drawings

Digital KPIs mapped to engineering drawings

Progress metrics were computed by comparing AI-detected features against digital engineering layouts, ensuring alignment between planned and actual progress across all solar zones.

Standardized classification of construction status

Standardized classification of construction status

Automated tagging of construction stages (e.g., completed, in-progress, pending) helped enforce a uniform inspection process, reducing subjectivity and improving traceability.

Interactive web dashboards for real-time visibility

Interactive web dashboards for real-time visibility

For faster decision-making, project stakeholders such as EPC heads and engineering leads could remotely monitor multiple sites through an integrated dashboard with intuitive visualizations, issue flags, and trend-based alerts.

Automated data storage and compliance-ready reporting

Automated data storage and compliance-ready reporting

Project snapshots were archived securely in the cloud via Snowflake, enabling historical comparisons, audit tracking, and compliance validation without manual effort.

Business Benefits

 
10x faster construction progress tracking

10x faster construction progress tracking

Manual audits that previously required up to 10 person-days per site were completed in under 30 minutes using automated drone and AI workflows, dramatically improving project velocity and reducing time-to-insight for site managers.

35,000+ features detected with more then 85% accuracy

35,000+ features detected with more then 85% accuracy

AI-powered detection models delivered high-confidence insights into pile counts, module installations, and inverter placements, ensuring dependable, data-driven progress validation with minimal human error.

Real-time operational visibility across remote sites

Real-time operational visibility across remote sites

Interactive dashboards gave stakeholders such as project managers, engineering leads, and EPC heads centralized access to construction status across multiple solar farms. This enhanced coordination and reduced onsite dependencies for inspections, reporting, and approvals.

Standardization inspections and reduced subjectivity

Standardization inspections and reduced subjectivity

Automated classification of construction stages established a uniform inspection protocol, minimizing rework, disputes, and communication gaps, which resulted in smoother project execution and improved contractor accountability.

Improved compliance and audit readiness

Improved compliance and audit readiness

Cloud-based archival of site imagery and detection results created an automated, time-stamped audit trail, streamlining regulatory reporting and third-party validations of construction milestones and quality benchmarks.

Scalability across geographies and terrains

Scalability across geographies and terrains

The solution was successfully deployed across multiple remote sites in Saudi Arabia’s desert regions, demonstrating its flexibility and replicability for large-scale solar rollouts in varied environments.

Conclusion

By integrating drones, GeoAI, and cloud-powered dashboards into a single intelligent platform, LTIMindtree enabled the client to transform manual solar construction audits into a fast, standardized, and highly scalable process.

The solution delivered a measurable impact, accelerating progress tracking by 10x, improving accuracy, and providing real-time visibility across remote project sites.

With enhanced traceability, audit readiness, and automation built into the inspection lifecycle, the client can scale operations efficiently, confidently, and controllably to meet expanding sustainability goals.

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