Energy Management System

Technology Highlights Minion Energy Analytics
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Technology

Minion is a Plug & Play device which doesn’t need any device level sensors, plugins or any software installations required. Minion uses single/three split core current transformer sensors which collects more than 4 Million energy consumption parameters per second and fed to our machine learning algorithms which can accurately determine the appliances that are being used inside the building.

Highlights

  • Save energy costs for you and your clients up to 30% in Commercial Buildings and up to 45% in Industries
  • Quick, Easy Installation and Low Maintenance
  • Tailored Cloud Dashboard with Real-Time and Historical data powered by more than 5 AI practices
  • Detect Appliances and Devices activity with the power of NILM
  • Find and Benchmark energy guzzling and stand by power appliances and devices
  • Predict the energy usage and cost in advance
  • Automate your building by adding Minion Smart Switches to the Minion EMS
  • Verify the impact of energy-saving measures
  • Compare your building with similar sites and get carbon ranked
  • Protects your data and your privacy
  • Interoperable with IoT Products
  • Modular, Flexible, Future-Proof solution

Minion Energy Analytics

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Descriptive Analytics

Monitors Energy Consumption Data and shows Analytics Instantly

Machine Learning Phase

Detects Appliances, Devices, Tools Turning ON/OFF with its Energy Consumption at Real Time.

Diagnostic Analytics

  • Early Fault Detection
  • Asset Health Monitoring
  • Detect Power Guzzling Activities
  • Detect Power Pilferages
  • Monitor Productivity based on Equipment Downtime

Predictive Analytics

Minion predicts energy costs and asset efficiency.

Prescriptive Analytics

  • User can create one or more Policies and get notifications if someone access certain equipmen or area or after duty time
  • Get real time energy consumption and recommendation notifications and insights through web/mobile apps

Artificial Intelligence

Minion runs various probabilities and decision analysis among available solutions and produces list of best recommendations/ action points to save energy cost.