Overview

Horizon Energy, a Saudi oil and gas operator company has faced rising efficiency and safety challenges as its operations expanded across remote and harsh environments. To modernize monitoring and reduce manual intervention, the company adopted AI, IoT and computer vision solutions to enhance the overall operations by providing real-time asset tracking, proactive maintenance alerts, and automated safety compliance across onshore and offshore sites.

Technical Stack

  • Computer Vision Model
  • Machine Learning
  • IoT Integration
  • Apache Spark

    • Industry

    Oil & Gas

  • region

    • Region

    Saudi Arabia

  • project-size

    • Project Size

    Non- Disclosable

Highlights

Automated leak detection, reducing detection time by 80%.

20% improvement in equipment maintenance schedules, minimizing unexpected downtimes.

Increased worker safety compliance by 40% through real-time safety monitoring.

Enhanced environmental monitoring with automated emission tracking.

Reduced operational costs by 25% by automating repetitive and error-prone tasks.

Achieved 95% accuracy in asset monitoring across both onshore and offshore sites.

Challenges & Solutions

Frequent manual inspections of pipelines were time-consuming and prone to human error.

  • Solution: We deployed advanced computer vision models integrated with drone and CCTV feeds to automatically detect leaks, irregularities and safety threats in real time. This enabled our client to eliminate manual dependencies and become proactive.

The company struggled to monitor equipment integrity across various sites, leading to unplanned downtimes and affecting productivity.

  • Solution: Leveraging IoT sensors and predictive maintenance algorithms, we delivered a real-time monitoring system capable of forecasting equipment issues before failure. The solution helped to eliminate unplanned outages, improving operational continuity and significantly extending the life of critical assets.

Ensuring all safety regulations were met in real time was difficult, especially with vast onshore and offshore facilities.

  • Solution: We deployed an AI-driven system to monitors workers’ safety gear compliance. The system detects real-time safety violations and immediately notifies supervisors to ensure rapid corrective action.

Core Features

  • Real-Time Anomaly Detection
  • Predictive Maintenance Alerts
  • Safety Compliance Monitoring
  • Automated Environmental Monitoring
  • no.-of-resources

    • No. of Developers

    04

  • time-frame

    • Time Frame

    August 2024 - February 2025

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