Pattern Recognition and Smart Metering

This Electronics Weekly article says:

University of Oxford spin out Intelligent Sustainable Energy (ISE) is to make electricity meters so smart that they can recognise which domestic appliance is operating at any time...Instead, the firm's intellectual property covers algorithms that interpret mains voltage and current waveforms. "It is artificial intelligence - pattern recognition," said Donaldson, who would not go into any more detail.

This implies that each device in a house has a characteristic pattern of electricity usage that ISE's algorithms can identify. The ISE webpage  says

The core of the ISE solution is the intelligent energy monitor which connects to the energy supply at a single point. Using patented artifical intelligence and signal processing techniques developed over a number of years at Oxford University, the system analyses the electricity supply and calculates the power consumption of each appliance without the need for any other sensors. This information can then be communicated to the consumer through a variety of methods including local in-home displays, web portals and itemised billing services.

There is some more information in this story.

Intelligent Appliances
MIT's Project Oxygen has the notion of Intelligent Spaces

Space-centered computation embedded in ordinary environments defines intelligent spaces populated by cameras, microphones, displays, sound output systems, radar systems, wireless networks, and controls for physical entities such as curtains, lighting, door locks, soda dispensers, toll gates, and automobiles. People interact in intelligent spaces naturally, using speech, gesture, drawing, and movement, without necessarily being aware that computation is present.

Environmental devices, together called an E21, provide a local-area computational and communication back-plane for an intelligent space. E21s are connected to nearby sensors, actuators, and appliances, suitably encapsulated in physical objects. They communicate with each other and with nearby handheld devices (H21s) through dynamically configured networks (N21s). E21s provide sufficient computational power throughout the environment

Related Papers
Current Sensor Based Non-Instrusive Appliance Recognition (copy protected PDF) by Saito et al explains one way of finding the current usage patterns of electrical devices. They use Nearest Neighbor classification.

Exploration on Load Signatures

Estimation of Variable-Speed-Drive Power Consumption From Harmonic Content  paper proposes a VSD power estimation method based on observed correlations between fundamental and higher harmonic spectral content in current. The technique can be generalized to any load with signature correlations in harmonic content, including many power electronic and electromechanical loads.

Update,  21 October 2009
I am putting together some proposals for products based on HANs and pattern recognition. If anyone has similar interests please contact me on peter.williams.97@gmail.com to discuss collaboration opportunities.