Sense is advancing residential energy intelligence by applying high-resolution electrical signal analysis and machine learning to deliver real-time, device-level visibility into household electricity consumption. The company’s home energy platform transforms aggregate power data from a single connection point into actionable insights, enabling homeowners and utilities to understand better, optimize, and manage residential energy usage.
Sense’s technology is based on a continuous monitoring system that captures voltage and current waveforms from the home’s electrical mains. These measurements are sampled at high frequency, allowing the platform to observe transient events, such as inrush currents, steady-state loads, and switching behaviors, that occur when appliances turn on, turn off, or change operating modes. By analyzing these electrical characteristics, Sense builds detailed power profiles of individual loads within the home.
Advanced Load Disaggregation Using Machine Learning
Sense employs proprietary machine learning models to perform non-intrusive load monitoring (NILM). Rather than relying on individual sub-meters or smart plugs, the system identifies appliances based on their unique electrical “fingerprints,” which include power magnitude, harmonic content, phase behavior, and temporal usage patterns. As the system observes repeated appliance behavior over time, its confidence and accuracy in device recognition improve, enabling persistent tracking of both major and always-on loads.
This approach allows Sense to disaggregate total household energy consumption into identifiable devices such as HVAC compressors, water heaters, cooking appliances, laundry equipment, consumer electronics, and EV chargers. The resulting device-level insights are presented in real time through the Sense app, giving users immediate visibility into what is consuming power at any moment.
Real-Time Monitoring and Behavioral Insights
Beyond static energy reporting, Sense’s platform emphasizes continuous awareness. The real-time power meter updates dynamically as loads change, helping users detect abnormal spikes, phantom loads, or unexpected usage. Historical views enable comparison across hours, days, and months, supporting deeper analysis of seasonal demand, appliance duty cycles, and standby consumption.
By correlating power behavior with time-of-use patterns, Sense helps users identify opportunities to shift discretionary loads, reduce peak demand, and improve overall energy efficiency. Alerts and notifications further enhance the system’s intelligence by signaling when devices operate outside normal parameters, potentially indicating equipment degradation or faults.
Integration with Distributed Energy Resources
Sense’s technology is designed to operate within increasingly complex residential energy ecosystems. The platform supports integration with rooftop solar photovoltaic systems, enabling net consumption and production tracking in real time. This capability is particularly valuable for households seeking to optimize self-consumption, manage export limits, or understand the interaction between solar generation and household loads.
As electrification accelerates, driven by EV adoption, heat pumps, and electric appliances, Sense’s ability to provide granular load intelligence makes it a foundational layer for grid-interactive homes. The platform’s analytics can support demand response programs, dynamic pricing models, and future coordination with home batteries and smart energy management systems.
Transition Toward Utility-Scale Deployment
While Sense initially entered the market through panel-installed home energy monitors, the company is expanding its reach by embedding its analytics software directly into utility smart meters. This shift enables utilities to offer advanced energy intelligence services without requiring additional customer hardware, thereby significantly lowering deployment barriers. Through smart meter integration, Sense delivers high-resolution consumption data, device-level insights, and customer engagement tools at scale. This enables broader utility objectives around load forecasting, peak demand reduction, and customer-side energy optimization, making Sense’s technology increasingly relevant to both consumers and grid operators.
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About Sense
Founded in 2013, Sense develops software-driven energy intelligence solutions that combine high-frequency electrical data acquisition with advanced machine learning. The company’s mission is to improve energy efficiency and reduce carbon emissions by making energy usage visible and understandable at the device level. Sense’s platform is used by homeowners, utilities, and energy partners to enable smarter residential energy management and support the transition toward a data-driven power grid.
