Towards intelligent IoT infrastructure and sensors for continuous monitoring of building performance (thesis, or thesis + internship)
Research Groups TEBE (http://www.tebe.polito.it/)
Description Experimental thesis aimed to test and integrate IoT decentralised sensors for the continuous monitoring of building envelope performance (thermal and daylight mainly).
This work is particularly important to enable the implementation and use of intelligent and smart systems in buildings (such as adaptive and dynamic facades).
It will start with a literature survey and market study, to (i) understand type of sensors needed (adopted in outdoor test cells, living labs and real building) to monitor performance of building envelope, and their use; (ii) identify state of the art monitoring architectures; (iii) identify and evaluate low cost IoT monitoring architecture and sensors.
Parallel to this the student will develop knowledge about calibration of specific sensors and use of monitoring systems and apparatuses.
This activity is followed by the adoption and test of the most promising candidates for monitoring system / architecture and related IoT sensors, in real testing environment (outdoor test cells for testing advanced facade elements on the roof of Politecnico di Torino), which include programming of the sensors, calibration, experiment set-up, data acquisition and post-processing. The test is aimed to compare the selected monitoring architecture and sensors, with the ones currently in use in the built environment, to evaluate in a comparative way different aspects, such us disrumption to occupants, accuracy and granularity of measurements, costs and reliability of the systems / sensors.
Required skills Knowledge of Building Physics fundamentals and advanced concepts including thermal and daylight comfort (at least 2 building physics courses completed during the BSc and MSc degree); willingness and attitude for literature review and field work (including the use and programming of sensors and monitoring systems); Excellent Excel skills; elements of Python or Matlab programming (or willingness to learn some).
Deadline 05/01/2023 PROPONI LA TUA CANDIDATURA