Mission 1

Creating Digital Twins of Household Appliances for Smarter Demand

Problem Statement

Develop an AI-powered tool to analyze behind-the-meter (BTM) energy consumption patterns and create digital twins of appliances.

To address this challenge, We are building the VoltBrew BTM+ AI Suite, tightly integrated with our Indian-made BTM gateway hardware and compatible APIs which will help in:

Solution No. 1

Collect high-resolution data from individual appliances (up to 72 current channels)

Solution No. 2

Enable real-time sensing of current, voltage, and power factor

Solution No. 3

Create AI-powered digital twins using NILM and neural symbolic learning

Solution No. 4

Simulate appliance behavior in the cloud for predictive forecasting

Solution No. 5

Offer demand-side optimization tools including user recommendations and DISCOM-level dashboards

Solution No. 5

Run load-shifting simulations, visualize savings, and provide TOU advisory

Solution No. 7

Detect behind-the-meter EV charging patterns using ML for better infrastructure planning

Outcomes Of The Mission

Outcomes Of The Mission

Scalable creation of digital twins for consumer household devices

Outcomes Of The Mission

Early identification of faulty or inefficient appliances

Outcomes Of The Mission

Empowerment of consumers with smart upgrade choices

Outcomes Of The Mission

DISCOMs enabled to manage demand with AI precision

Outcomes Of The Mission

Reduced guesswork in infrastructure planning and upgrades

Outcomes Of The Mission

A new layer of consumer engagement, awareness, and control

Outcomes Of The Mission

Unlocking residential demand flexibility at scale

Outcomes Of The Mission

Deployment-ready trained AI models for appliance-level insights