Description

Sensing of conditions is an important element of ensuring that interior environments are comfortable and healthy and that the systems that support them are functioning properly. Interior environments covers any environment that is artificially maintained and can include buildings; cars; trains aircraft, even spacecraft.

We gather information about the quality of these "artificial environments" using a variety of fixed sensors that measure things like dry bulb temperature, carbon dioxide levels, light levels, noise levels, etc. However, there tend to be only a few sensors giving us a very limited view of conditions in a space, potentially missing issues that could affect health and wellbeing such as high or low temperatures, noisy conditions, contaminated air, glare, etc.

This project will investigate alternatives to fixed sensors, assessing whether the information collected by many "smart" devices that we use every can be accessed and used with or instead of conditions data collected by conventional means.

Key Objectives Project objectives are:

(1) review a range of everyday smart devices and identify those which have environment sensing capabilities or which could be used to infer conditions also review positional information

(2) review the feasibility of data collection from smart devices and the best mechanisms to access data (e.g. a dedicated App?)

(3) test the quality of sensed information from smart devices and explore means by which that data could be calibrated and quality assured

(4) review and develop a means to relay sensed conditions from multiple devices back to an end-user, this could be tested using real or synthetic data