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AI-Driven Construction Site Management and Risk Detection Platform

leobit.com

Construction

Real estate

Infrastructure Development

Manual Construction Progress Tracking and Delayed Issue Detection

Construction teams face inefficiencies due to manual site inspections requiring physical visits by foremen, leading to delayed progress reporting, overlooked quality issues, and resource allocation delays. Existing processes lack proactive risk detection capabilities and decentralized reporting mechanisms for field workers.

About the Client

Leading Nordic construction firm specializing in residential, commercial, and public infrastructure projects with dedicated R&D focus on construction process innovation

Automate Progress Tracking and Proactive Risk Management

Implement automated AI-powered progress tracking across multiple construction sites
Enable real-time decentralized reporting for field workers
Develop predictive AI models for structural defect detection
Reduce manual site visit requirements by 70%
Improve resource planning accuracy through proactive material request system

Core System Functionalities and Key Features

Flutter-based cross-platform mobile application with BLoC architecture
Real-time progress reporting with photo documentation
AI-powered defect detection (cracks, alignment issues, curvature)
AR-assisted photo capture guidance using ARCore/ARKit
Offline data caching with SQLite (Drift library) and background sync
Azure-integrated material request workflow
Predictive risk alerts with manual verification override

Technology Stack Requirements

Flutter SDK

TensorFlow

PyTorch

Microsoft Azure Cloud

.NET Core

Azure Blob Storage

AR Flutter Plugin

System Integration Requirements

Azure Active Directory Authentication
TensorFlow/PyTorch AI models on Azure GPU servers
ARCore/ARKit for mobile AR functionality
Azure DevOps for CI/CD pipeline
Firebase Cloud Messaging for push notifications

Non-Functional Requirements

Cloud scalability for concurrent site monitoring
Offline-first design for low-connectivity environments
Role-based access control with Azure AD
GPU-accelerated AI processing performance
Construction worker-friendly UI/UX design

Enhanced Operational Efficiency and Risk Mitigation in Construction Projects

Implementation of AI-powered progress tracking is expected to reduce manual site visits by foremen by 70%, enable early detection of 92.7% of structural defects, and improve resource allocation efficiency through real-time material request workflows. The AR-assisted photo system will ensure 98%+ compliance with AI analysis requirements while maintaining seamless operations in low-connectivity environments.