Domestic energy and housing sensors
predicting refurbishment needs for council owned housing
The Problem
The housing stock owned by the Southampton
City Council and falling under the ‘liveable cities
project’ needed assessment to see if cost effective
investment in heating and lighting is needed. This
problem has lots of data coming from lots of
houses, lots of sensors and lots of people behaving
in different ways. The data being gathered is
similar to that produced by many smart metering
projects, but here the sensors are fine grained and
diverse. Our challenge was to innovate with the
existing sensors, deploy our hubs and work with
the University of Southampton using the real time
data and applying sophisticated algorithms
developed to deliver a detailed refurbishment
model. The objective for sensor data is to easily
allow the building owner to determine, with a
good degree of confidence where, when and how
investment in the properties is needed to improve
lives.
Sensors Used
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nquiringminds’ QBlox IOT sensor hub
Nquire Toolbox
CO2 sensor to estimate room occupancy
Temperature and Humidity sensors in
living areas
AC clamp for inductive sensors of mains
electricity supply
Boiler activity sensors
PIR sensors
Window and door latch sensors
Scenario
The LiveableCities project has led to two hundred
houses in the Southampton area provisioned with
a comprehensive sensor suite. We were brought
into the project to add sensor expertise and to
apply our algorithms and assessment of the
diverse data.
The sensors we designed and built analyse over
different seasons both the thermodynamic
behaviour of the house and the behaviour of the
residents. The sensors gather data at regular
intervals producing a very fine grained model
across many data points.
The data being gathered is similar to that
produced by many smart metering projects, but
much more detailed and including more diverse
sensors. Using this data and applying sophisticated
algorithms developed with the University of
Southampton we made it possible to produce a
detailed refurbishment model, where for example
the building owner can determine, with a good
degree of confidence whether loft insulation,
replacement of doors and windows, replacement
of boiler or servicing of heating system, will
provide the best long term investment both in
terms of cost saving and CO2 reductions.
The deployment of these sensors have a very clear
prioritised return on investment. Being able to
predict future cost savings very accurately. Where
the current housing owner is holding the liability of
leaky, inefficient housing stock, such a solution is
invaluable.
The sensors deployed are nquiringminds’ QBlox
IOT sensor hub. QBlox has been integrated on to
a number of well proven, commercial sensors,
using the IOT Open source driver model. This
allows us to keep the cost of deployment down
with maximum confidence in the reliability of the
equipment. The QBlox architecture is highly robust
to the range of real world IOT problems. Such as
coping with power and network outages. Data is
held on the QBlox IOT hub, pre-processed and
transmitted efficiently over a GSM bearer, when
there is a reliable network connection.
The QBlox IOT hubs transmit their encrypted data
to the Trusted Data Exchange (TDX) where data is
held securely under a tight permissioning system.
Where each resident is the owner of their own
data. Mobile and desktop visualisation of this data
can be rapidly generated from within the Nquire
Toolbox. The sophisticated analytics required to
generate the refurb model is held as an algorithm
within the Toolbox.
From the TDX it is possible to dynamically update
the code on the local QBlox hub allowing both
data pre-processing and data upload schedules to
be updated after the devices have been deployed.
Outcome
Working with the Council and the University of
Southampton we were able to deploy our secure
platform and sensor technologies and visualisation
tools to make Southampton City Council better at
capturing, securing and using data from its
housing stock. This project is ongoing.
Professor AbuBakr S Bahaj head of ECCD and
Chief Scientific Officer for Southampton City
Council “NquiringMinds sensor suite and data
analytics platform has been key in allowing us
to estimate the energy saving that can be
attained in buildings, assisted in the validation
of our city-wide modelling approaches and the
planning strategies for housing refurbishment”
Gamma House, Enterprise Road
Southampton Science Park
Chilworth Hampshire SO16 7NS
UK
www.nqminds.com
[email protected]
@nqminds
+44(0) 2381 159 585