The Problem
iRise operates large construction machinery, including cranes and rollers, with fuel costs being a major operational expense. However, tracking actual fuel usage vs. pilferage was nearly impossible. The company needed an intelligent system to monitor fuel input, consumption, and machinery efficiency in real time.
The Solution
AnySource Data Combiner
Integrated fuel level sensors, GPS trackers, and machine operation logs, providing real-time insights into:
- Fuel consumption per hour (CPH) & fuel efficiency (L/hr, km/L)
- Total run-time vs. idle-time tracking
- Refueling & de-fueling event detection
- Overspeeding, unauthorized detours, and geo-fencing breaches
Data Reason Builder
Leveraged Machine Learning models to:
- Predict daily/monthly fuel requirements based on historical usage patterns.
- Correlate fuel efficiency with equipment make, model, and operational conditions for precise fuel forecasting.
- Detect anomalies in fuel usage, flagging pilferage and leakages for immediate action.
A custom-built AI-driven analytics dashboard provided iRise with data-backed insights, enabling strategic decision-making for cost control and operations planning.
The Result
- Fuel pilferage reduced—Pinpointed fuel loss incidents by location and timeframe, enabling targeted security measures.
- Optimized fleet efficiency—AI-based insights ensured better fuel allocation across operations, preventing overuse and underutilization.
- Operational cost savings—The system’s accuracy enabled iRise to cut unnecessary fuel expenses, achieving ROI in under six months.
- Smarter equipment management—Predictive analytics provided insights into maintenance schedules, improving equipment uptime.
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