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

  • 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”

 

 

 

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