IEEE Technology and Society Magazine - Fall 2014 - 79

Table I
Installation and Maintenance Costs Associated with the Energy Monitoring Infrastructure
Item

Volumes per Dwelling

Cost (£) per Item

Total Cost (£) for 100 Dwellings per Year

Equipment Installation
Equipment
Maintenance
Battery Replacement
Cost
Battery Replacement
Maintenance Cost

1
1

100
50

10,000
5,000

400

1,000

Other Costs
The analysis so far has provided a
broader perspective on the energy
footprint and operating costs of
the energy-monitoring infrastructure. We now compare these costs
against those related to installation and maintenance of the components of the infrastructure. In
particular, there are two items to
consider. The first is the services of
a qualified electrician for installation and maintenance, and the second is battery replacement costs.
Table I attempts to capture
these costs per year. The installation costs are the fees charged by
the electrician to install equipment
in each dwelling at the beginning
of the pilot study. Similarly, the
maintenance costs are the fees
charged by the electrician for any
subsequent maintenance related
to the visit. Based on the data collected on each dwelling, there has
not been any more than one maintenance visit per dwelling since the
pilot started in January 2012. Also,
not all dwellings have required a
follow up visit. It is assumed that
each dwelling had one maintenance
visit, which, in this case happens to
be a worst-case estimate.
There are four battery-operated
devices in each dwelling. These
devices include the current monitor, temperature/humidity monitor, pulse monitor, and the Zigbee
gateway. The batteries used in each
of these devices have a lifespan
of 3 years. The cost depicted, per
year, is a third of that incurred every
3 years. If we assume a cost of

£3 (U.S. $5) per battery, this translates
to £12 (U.S. $20) per dwelling every
three years (or £4 (U.S. $6.80) per
dwelling per year). The demographics of the inhabitants of the dwellings considered in the pilot study
are diverse. While some of them are
comfortable with technology, there
are others who struggle with basic
tasks such as replacing a battery (e.g.,
people who are under care/observation due to long-term conditions).
In such cases, a visit to the dwelling may be necessary to replace the
battery. In the context of this study,
it is assumed that every dwelling
will require this service (worst-case
estimate). However, in practice, one
can optimize for this cost parameter
by identifying a small subset of the
population which will actually need
this service and notify the others when
their batteries are due for replacement.
As mentioned earlier, since batteries
need to be replaced every 3 years, the
cost shown here has been spread out
on a yearly basis.
We observe that all of these
costs are substantially higher
than the cost of energy required
for operating the monitoring elements. These costs are attributed
to the fact that some devices in
the deployment, such as the smart
meters, need to be wired in the
existing circuitry in the dwelling. This cannot be accomplished,
given health and safety regulations, without using the services of
a qualified electrician. As a result,
opportunities arise for designing non-invasive and user-friendly
smart metering products that could

IEEE TECHNOLOGY AND SOCIETY MAGAZINE

FALL 2014

potentially help to mitigate the
aforementioned costs. Similarly, if
the energy efficiency of the products and the batteries themselves
could be improved (which could
facilitate extension of the battery
lifetime by a few more years), this
could help further reduce installation/maintenance costs.

Energy Savings
Can Be Achieved
This article provides an overview of
the 3e-Houses project which trialled
the application of fine-grained energy
consumption monitoring and ICT
interventions, with an overall goal
of reducing household energy use.
This was accomplished through a
pilot deployment in social houses, in
two different locations in the city of
Bristol, U.K. The aim of this pilot was
to collect fine-grained data to gather
insights into the consumption patterns
of consumers and empower them with
information by making them aware of
their usage. The findings of the data
collected have the potential to trigger
behavior changes that could result in
a decrease in the overall consumption
of energy. The following are some of
the lessons learned from this study.
■■

We observed that for a subset of
dwellings (10-20% of the sample
size), both statistically and economically significant savings
(around 10-20%) were achieved.
The results are promising. We also
found that the overhead, resulting from the monitoring (energy
consumed by the monitoring
infrastructure itself) amounts to
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Table of Contents for the Digital Edition of IEEE Technology and Society Magazine - Fall 2014