IEEE Electrification Magazine - June 2018 - 72

receivers, and touch interfaces, which act as sensors.
since smart devices apply machine learning and emotionrecognition technologies, they can be used by the Bems to
collect data on human physical conditions. smart devices
sense human conditions and transmit the collected data
to the Bems over the building's internet. a Bems classifies
human performances in terms of their moods and environmental conditions; accordingly, individual employees
would fill out a daily inquiry that would determine their
physiological status. the data might then be automatically
collected through the iot's biological sensors, with optimal conditions for each iP calculated and provided by a
Bems (figure 5).

Final Words
energy consumption in metropolitan regions will continue
to rise as the world's population, urbanization, thermal
energy usage, and global warming continue to escalate. in
this arena, smart devices that use electricity and provide
credible data on human conditions are more commonly
used for solving alarming sociopolitical and socioeconomic problems in urban areas. optimizing building energy
usage in urban areas is a good start for energy management because a significant level of the world's energy is
consumed by buildings. today's large buildings have
numerous energy-consuming units and sensors whose
data transmission and processing could disrupt the proper functionality of a Bems. moreover, various types of services in complex buildings and their interactions could
enmesh the Bems operation due to interoperability issues.
as a result, we propose the deployment of an iot infrastructure to enhance Bems applications as the quantity
and quality of data are an increasing concern. the implementation of the iot will introduce new opportunities in
Bems applications that can satisfy complementary objectives as Bems targets. conventional Bems models can
save energy satisfactorily, but they are not adaptively controlled by building occupants' behavior to increase productivity and comfort. however, the proposed Bems
framework can help mitigate this deficiency, lower energy
consumption, reduce environmental pollution, and maximize building occupants' performances. the static Bems
implementation is converted into a dynamic Bems controller that continuously adjusts physical set points as a
user's status changes. the proposed Bems model embeds
a combination of the iot and an hitLcPs in which
humans play a sensory role, and their situational awareness promotes the adaptability of the Bems controller. the
required framework for the massive data transmission is
prepared by the iot considering occupants' physical and
physiological states that is handled by the hitLcPs.
the proposed Bems offers the following features.
xx
a Bems is a multiagent control system that adjusts
device settings in an automated fashion and utilizes the
iot to receive and provide control signals to building
occupants and decision makers through an hitLcPs.

I EEE E l e c t r i f i c a t i on M a gaz ine / j un e 2018

xx
a Bmes can arrange various levels of building services,

provide accurate control settings for building devices,
send alarm signals in critical conditions, and resolve
any malfunctions remotely according to organizational responsibilities and human functionalities.
xx
a Bmes can offer proper set points to human operators by monitoring the behavior of building occupants
by continuously comparing the building level efficiency with the individuals' satisfaction level for maximizing the operation conditions. in essence, a Bems will
make credible information available to decision makers as to the types of necessary reinforcements and
upgrades the building would require to accomplish
certain objectives pertaining to large-scale economics,
security, sustainability, reliability, and resilience.

For Further Reading
m. sorgato, a. melo, and r. Lamberts, "the effect of window
opening ventilation control on residential building energy
consumption," Energy Buildings, vol. 133, pp. 1-13, Dec. 2016.
P. Kumar, c. martani, L. morawska, L. norford, r. choudhary, m. Bell, and m. Leach, "indoor air quality and energy
management through real-time sensing in commercial buildings," Energy Buildings, vol. 111, pp. 145-153, Jan. 2016.
m. manic, K. amarasinghe, J. J. rodriguez-andina, and
c. rieger, "intelligent buildings of the future: cyberaware,
deep learning powered, and human interacting," IEEE Ind.
Electron. Mag., vol. 10, no. 4, pp. 32-49, 2016.
m. manic, D. Wijayasekara, K. amarasinghe, and J. J. rodriguez-andina, "Building energy management systems: the
age of intelligent and adaptive buildings," IEEE Ind. Electron.
Mag., vol. 10, no. 1, pp. 25-39, 2016.
t. gerrish, K. ruikar, m. cook, m. Johnson, m. Phillip, and
c. Lowry, "Bim application to building energy performance
visualisation and management: challenges and potential,"
Energy Buildings, vol. 144, pp. 218-228, June 2017.

Biographies
Mona Bisadi (bisadi.mona@wtiau.ac.ir) is with the art and
architecture Department, West tehran Branch, islamic
azad university, tehran, iran.
Alireza Akrami (alireza.akrami@ut.ac.ir) is with the
school of electrical and computer engineering, college of
engineering, university of tehran, iran.
Saeed Teimourzadeh (teimourzadeh@ut.ac.ir) is with
the school of electrical and computer engineering, college
of engineering, university of tehran, iran.
Farrokh Aminifar (faminifar@ut.ac.ir) is with the
school of electrical and computer engineering, college of
engineering, university of tehran, iran.
Mehdi Kargahi (kargahi@ut.ac.ir) is with the school of
electrical and computer engineering, college of engineering, university of tehran, iran.
Mohammad Shahidehpour (ms@iit.edu) is the professor and director of the robert W. galvin center for electricity innovation at the illinois institute of technology,
chicago.

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