yvnalvworks

Volto : Real-time Energy Monitoring

Machine LearningIoTDashboard
Volto Energy Monitoring System

Background

Industrial facilities often lack visibility into real-time electricity consumption. This results in higher operational costs, unexpected power surges, and difficulty identifying inefficiencies. Volto was designed to empower energy-conscious businesses with live monitoring, predictive insights, and actionable alerts.

The Problems

  • No centralized dashboard for energy usage across devices
  • Lack of forecasting to predict peak hours or abnormal usage
  • Manual meter readings prone to delays and errors
  • Limited data access for different teams (engineers, managers, QA)

Our Approach

Volto was architected as a modular system using .NET (ASP.NET, SignalR), SQL Server, and modern frontend frameworks. We implemented secure APIs for data ingestion, a real-time WebSocket-based chart dashboard, and role-based access control tailored to different user personas.

Project Showcase

Screenshot 1

Swipe to preview Volto’s real-time dashboard and forecasting features.

Methodology & Key Features

  • ESP32 devices send voltage, current, power factor data over MQTT
  • Backend API ingests and stores data securely with JWT authentication
  • Real-time dashboards using SignalR and responsive chart updates
  • Forecasting using ML models to predict kWh and cost trends
  • Anomaly detection to catch unusual power spikes automatically
  • Role-based UI: admins, QA, engineers, and guests

Results

After deploying Volto, our industrial client was able to cut electricity costs by over 25% in the first quarter alone. Engineering teams detected faulty equipment early, and management gained real-time visibility into energy use patterns.

Benefits

  • Reduce energy costs and carbon footprint
  • Enable data-driven maintenance schedules
  • Prevent production disruptions from overloads
  • Empower teams with live, historical, and predictive insights