Energy assessment of AI Shading – A Smart Blind technology

The green building movement within building designs has put a spotlight on the application of green technologies to reduce the energy consumption and overall carbon footprint of residential and commercial buildings. In general, approximately half of a building’s total energy usage goes towards heating, cooling, and lighting requirements [1]. According to a recent report from the Attachments Energy Rating Council (AERC), fenestration products such as windows account for up to 30% of residential heating and cooling energy needs [9]. The application of smart blind systems such as AI Shading aim to minimize a building’s total energy consumption by reducing the heating and cooling load contributions from windows. Through the automated adjustment of blind configuration, smart blind systems reduce the indoor solar energy gain during the cooling season and limit indoor conductive energy losses during the heating season. This study works to quantitatively assess the energy-saving potential of AI Shading for application in residential and commercial buildings within Canadian climate zones. A computer-generated energy simulation model and prototype field study will be used to assess and verify the performance of AI Shading during both the Canadian heating and cooling seasons.

Faculty Supervisor:

Lexuan Zhong

Student:

Partner:

26 Celsius;AI Shading

Discipline:

Engineering

Sector:

Information and cultural industries; Manufacturing; Professional, scientific and technical services

University:

University of Alberta

Program: