Heating Ventilation and Air
Conditioning (HVAC) systems typically operate at 30 to 45 percent below their
efficiency rating, wasting hundreds of combined Gigawatt hours of energy in the
Clothes dryers, refrigerators and dishwashers, to name a few other appliances
are also known to waste significant amounts of energy due to inefficient usage
Technical Staff Member,
Smarter Energy Group,
IBM Research - India
statistics prompted scientists at IBM Research –
seriously look at reducing energy wastage, and so developed SocketWatch, an
autonomous appliance monitoring system. According to Tanuja
researcher for the project, “A significant amount of energy is wasted by
electrical appliances when they operate inefficiently due to anomalies,
incorrect usage or idling. It is important that this waste be minimized because
in the coming years, appliance usage is projected to sharply increase. SocketWatch
is attempting to address this problem.”
What is SocketWatch?
SocketWatch is a smart plug that is
positioned between a wall socket and an attached appliance, like a
refrigerator, a water heater or any industrial appliance. It learns the characteristics of the
attached appliance by analyzing its active and reactive power consumption
patterns. These patterns accurately represent the appliance’s normal operations.
Any significant shift in these patterns would indicate inefficiencies in the
appliance usage. Using machine learning algorithms embedded in the device, it
monitors power consumption characteristics to spot energy leaked by
malfunctioning or idling electrical appliances.
SocketWatch is inexpensive and easy to use;
it neither requires enhancement to the appliances, nor to the power sockets or
any communication infrastructure. Moreover, this decentralized approach avoids
communication latency and costs, and preserves data privacy.
example, a refrigerator with a door gasket that’s dry and cracked will consume
approximately 50 percent more electricity than its rated consumption. And an
efficient air conditioner that is operating in a room with an open door (or
leaky walls) would consume more than when it is operating in suitable
of the available products in the market don’t identify external factors that
impact appliance efficiency that warrant a communication network and a
computing device like a smart phone for interfacing with users. This lack of knowledge
results in substantial ownership costs and installation complexity,” Tanuja
SocketWatch is designed to operate in a
decentralized fashion, with all aspects of sensing, analytics, actuation and
notification performed at the device. It
has a learning phase and a monitoring phase. During the learning phase, SocketWatch
senses the electrical parameters (voltage, current, frequency and phase angle)
to measure the power consumption patterns of the attached appliance. It then analyzes
these measurements using resource-efficient machine learning algorithms to
build a behavioral model of the appliance. This would include the different
unique power levels of operation, durations and frequencies of those states, and
transitions from one state to another.
|SocketWatch (sPlug) learns the normal behavioral model of appliance by using active & reactive power consumption data.|
the monitoring phase, it compares the appliance consumption patterns against
the learned model. The deviations are used to spot malfunctions and energy
leakage. SocketWatch would then take appropriate corrective actions (such as
turning off idling appliances) or alert the users.
is estimated that each of us can potentially save around 30 percent of the electricity
we use while at work and at home,” Tanuja said.
SocketWatch is ready to be licensed, IBM has not set a date on its
availability. Watch this space for updates.
This work is conducted by IBM Research, India
in collaboration with Universiti Brunei
Darussalam, Brunei. Following researchers have
contributed to this work - Tanuja Ganu, Deva P. Seetharam, Dwi Rahayu (intern
at IBM Research, India), Rajesh Kunnath (Radio Studio, India), Ashok Pon Kumar,
Vijay Arya, Saiful A. Husain (Universiti Brunei Darussalam, Brunei) and
Labels: ibm research - india, smarter energy research center, socketwatch