Problem Statement
Energy systems in industries and utilities lack granular visibility and intelligence.
Without detailed monitoring, inefficiencies, energy losses, peak demand issues, and abnormal consumption patterns go unnoticed.
Ground Reality
Typical challenges observed in energy systems:
- Energy data available only at aggregate level
- No real-time visibility at equipment or feeder level
- Inability to detect abnormal consumption patterns
- Lack of actionable insights for optimization
- Manual audits instead of continuous monitoring
Key Insight: True energy intelligence requires combining current, voltage, and power to understand actual consumption behavior.
Solution Approach
Hexitronics proposes a 3-sensor IoT-based energy intelligence system integrating:
- Current Sensor: Measures load current and equipment activity
- Voltage Sensor: Captures supply conditions and fluctuations
- Power Measurement: Calculates real-time power consumption (kW, kWh)
The system continuously analyzes electrical parameters and transmits data securely to the cloud for intelligent monitoring and optimization.
Sensor Intelligence (Core Logic)
- High current + High power → Normal heavy load operation
- High current + Low power → Inefficiency or power factor issue
- Voltage drop + High load → Supply stress condition
- Sudden spikes in power → Abnormal equipment behavior
- Idle current + No production → Energy wastage
System Architecture
[ Architecture Diagram Placeholder ]
IoT Device → Current + Voltage + Power Measurement → 4G → Cloud → Analytics Engine → Dashboard
Key Features
- Real-time energy monitoring at equipment level
- Power and energy consumption tracking
- Peak demand analysis
- Battery / mains powered deployment
- Secure and scalable cloud integration
Future Dashboard & Analytics
Advanced analytics include:
- Energy consumption trends and reports
- Load profiling and peak demand analysis
- Energy efficiency insights
- Cost optimization recommendations
- AI-driven energy forecasting (future upgrade)
Benefits
- Reduced energy costs
- Improved operational efficiency
- Better demand management
- Early detection of inefficiencies
- Data-driven energy optimization
Deployment Strategy
Step 1: Install at critical equipment or feeders
Step 2: Establish baseline energy patterns
Step 3: Enable intelligent analytics and alerts
Step 4: Scale across facility or network