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—A home-based intelligent energy conservation system needs to know what appliances (or loads) are being used in the home and when they are being used in order to provide intelligent feedback or to make intelligent decisions. This analysis task is known as load disaggregation or non-intrusive load monitoring (NILM). The datasets used for NILM research(More)
The smart meter is often heralded as the key component supporting energy displays that can notify home occupants of their energy usage. But, a smart meter is only a digital power meter with enhanced communications capabilities - it is not actually smart. We need to look beyond the smart meter and define what intelligence is needed to actually make a meter(More)
—Nonintrusive load monitoring (NILM) is a process of discerning what appliances are running within a house from processing the power or current signal of a smart meter. Since appliance states are not observed directly, hidden Markov models (HMM) are a natural choice for modelling NILM appliances. However, because the number of HMM states grows rapidly with(More)
As people become more concerned with the need to conserve their power consumption we need to find ways to inform them of how electricity is being consumed within the home. There are a number of devices that have been designed using different forms, sizes, and technologies. We are interested in large ambient displays that can be read at a glance and from a(More)
Smart homes of the future will have a number of different types of sensors. What types of sensors and how they will be used depends on the behaviour needed from the smart home. Using the sensors to automatically determine if a home is occupied can lead to a wide range of benefits. For example, it could trigger a change in the thermostat setting to save(More)
Nonintrusive load monitoring (NILM), sometimes referred to as load disaggregation, is the process of determining what loads or appliances are running in a house from analysis of the power signal of the whole-house power meter. As the popularity of NILM grows, we find there is no consistent way researchers are measuring and reporting accuracies. In this(More)
—Understanding how appliances in a house consume power is important when making intelligent and informed decisions about conserving energy. Appliances can turn ON and OFF either by the actions of occupants or by automatic sensing and actuation (e.g., thermostat). It is, also, difficult to understand how much a load consumes at any given operational state.(More)
With the cost of consuming resources increasing (both economically and ecologically), homeowners need to find ways to curb consumption. The Almanac of Minutely Power dataset Version 2 (AMPds2) has been released to help computational sustainability researchers, power and energy engineers, building scientists and technologists, utility companies, and(More)