Prowesstics
AI for Safer Construction Sites by Prowesstics

AI for Safer Construction Sites: Monitoring Worker Activity to Reduce Risk and Downtime

Overview

A leading construction firm faced recurring issues with manual supervision - leading to inconsistent time logs, productivity gaps, and inefficient resource allocation. To solve this, Prowesstics deployed AI-based video analytics for real-time worker monitoring and performance tracking across different operational zones.

Problem Statement

Traditional labor monitoring in large-scale construction projects is labor-intensive, leads to human error, and lacks actionable insights.

  • Manual tracking of activities causing inefficiencies
  • Lack of real-time visibility into workforce allocation
  • No reliable system to measure productivity by task or zone
  • Need for a system that can automate this process and provide insight on the number of workers and hours spent on each activity

There was a clear need for an automated system to monitor the number of workers, the type of activity, and the time spent per task, enabling better workforce management and operational efficiency.

Solution

An AI-enabled video analytics system was developed to automate worker tracking in high-priority zones. The system leverages CCTV feeds and computer vision models to:

  • Detect and count the number of workers in each operational area
  • Monitor specific tasks such as rebaring, caging, and molding
  • Record the start and end times of each worker’s activity
  • Generate actionable insights on labor hours and task-wise productivity
  • Improve workforce planning and resource optimization

Operational Flow

Capture ➝ Prepare ➝ Train & Deploy ➝ Validate ➝ Analyze & Report

  • Footage Capture: Identify CCTV zones and collect video via RTSP.
  • Data Preparation: Extract images, annotate, and build a training dataset.
  • AI Model Training & Deployment: Train and deploy object detection models for real-time activity tracking.
  • Validation & Data Processing: Validate detected activities and convert data into structured formats.
  • Analytics & Reporting: Analyze performance metrics and generate efficiency reports.

Conclusion

By integrating AI video analytics into construction site operations, the company transitioned from manual tracking to a data-driven workforce monitoring system. The solution provided accurate, real-time insights into worker engagement and time spent per task, reducing productivity losses and enabling better project management. This approach sets a new standard for smart infrastructure project monitoring, leading the way for scalable, efficient labor management.