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Ventilation Monitoring and Control System for
High Rise Historical Buildings
Abhishek Singh, Student Member, IEEE, Yadvendra Pandey, Ashok Kumar, Manoj Kumar Singh,
Anuj Kumar , Senior Member, IEEE, and Subhas Chandra Mukhopadhyay, Fellow, IEEE
Abstract— Adequate ventilation system and difficulty in operating/maintain ventilators at higher levels in temples and high
rise historical buildings is a major problem. In this regard,
a wireless sensor actuator network-based ventilation monitoring
and control system is developed for temples and high rise
historical buildings. Sensor array modules are implemented
successfully. ZigBee communication module for transmitting
real-time data to the control room is being used. Machine-tomachine communication of the exhaust fans and the control
applications with personal computer was successfully carried
out. Developed system is capable of online monitoring of exhaust
fans running information parameters, such as air flow, vibration,
revolutions per minute, and load. The system is also capable
of ventilation control for good indoor air quality based on
real-time monitoring of environmental parameters like as CO2 ,
temperature, and relative humidity. A graphical user interface for
monitoring and control ventilation with the exhaust system was
developed. Exhaust fans real-time information and environmental
parameters values are displayed on the GUI developed using
Visual Studio C# language. Calibration of the sensor module
and exhaust system has been implemented successfully and they
assure that the desired accuracy is sustained after a time interval.
Developed system is of low cost, energy efficient, and easy to
operate with high accuracy.
Index Terms— Environment monitoring, sensor system application, wireless sensor network, buildings.
ENTILATION is a necessity for buildings to maintain
indoor air quality and removing indoor contaminants.
Adequate ventilation in temples, historical building, and monuments which are more than 10m high is a problem in terms
of health and safety [1]. CO2 level, temperature and relative
humidity inside the buildings is very high because the no
proper ventilation in the buildings. With increase in crowd
indoor environment and air quality becomes worse. Also there
is no guidelines or standard specifically related to indoor
environment and air quality of such buildings. Many incidents
such as breathlessness, eye irritations, fainting and so on were
reported suggesting towards poor indoor environment and air
quality because of poor ventilation system.
Manuscript received August 19, 2017; accepted September 21, 2017. Date
of publication September 26, 2017; date of current version October 24, 2017.
The associate editor coordinating the review of this paper and approving it for
publication was Prof. Danilo Demarchi. (Corresponding author: Anuj Kumar.)
A. Singh, Y. Pandey, A. Kumar, and A. Kumar are with the Efficiency of Building, Council of Scientific and Industrial Research-Central
Building Research Institute Roorkee, Roorkee 247667, India (e-mail:
M. K. Singh is with the Department of Human and Social Systems, Institute
of Industrial Science, University of Tokyo, Tokyo 153-8505, Japan (e-mail:
S. C. Mukhopadhyay is with Macquarie University, Sydney, NSW 2109,
Australia (e-mail:
Digital Object Identifier 10.1109/JSEN.2017.2756978
Unavailability of standards to deal with such buildings,
in this study nearest ASHRAE standards such as 55 and
62.1 are considered to fix the indoor thermal and air quality
parameters while designing the ventilation system. This study
also makes the management of these buildings aware about
the health issues and tries to put forth following two main
suggestions. First is to control the number of persons at a
time in the temples or high rise historical buildings or monuments and second is monitor and control the ventilation
within the high rise historical buildings, monuments, and
Similarly, on few cases the exhaust fans are used for removing indoor contaminants [2]–[5]. But there is always a necessity to develop a ventilation monitoring system using wireless
sensor network to fight the warm and damp environments, and
to control the thermal comfort in historical buildings. Simple
process of ventilation is the exhaust using electrical equipment
such as high capacity fans. Indoor air quality can be monitored
using sensors, communication technology and graphical user
interface applications.
Presently, researchers have worked on ventilation monitoring and control (VMC) systems to avoid malfunctioning
and failure of exhaust fans in buildings. Temples, high rise
historical buildings, and monuments have ventilation problem,
persistent high temperature and relative humidity as stated
by temple management and same is shown by high CO2
concentration, persistence of high temperature and relative
humidity in long term monitoring work. Real problem of
Shree Jagannath Temple is the lack of monitoring and control
system of exhaust fans. Four-exhaust fans provided at the top
of the Temple are approximately 61m high above the Garba
griha (Sanctum sanctorum) as shown in Figure 1. To solve
the issues related to ventilation it was considered to study
in this research. A wireless sensor network for high-rise
historical buildings, temples, and monuments in the context of
ventilation monitoring system is developed with an emphasis
on the energy efficiency and low cost. Control strategy is based
on real-time monitoring of environmental parameters such as
relative humidity, CO2 , and temperature.
Hence, the research study is organized as follows. Section II
discusses the previous work. Section III discusses the development of system architecture. Section IV covers the real
time testing. Finally, the results of research are covered in
Section V.
This section discusses the previous work on ventilation
monitoring and criteria of the control of ventilation parameters.
1558-1748 © 2017 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.
See for more information.
Fig. 1.
Ventilation system in Shree Jagannath Temple, Puri, India.
To bring forth the gap in research and issues to be solved a
comprehensive literature review is carried out and is discussed
here in [2]–[11].
A. Natural Ventilation
Hao et al. [2] proposed the approach of transactive control
of heating, cooling, and ventilation for commercial buildings
and they pronounce system model is based on collected data
of selected commercial buildings. They are performed the
different building case study to control the heating, cooling,
and ventilation through virtual test bed and also calibrated
the energy plus model. Kalogirou et al. [3] proposed a
neural network based model for natural ventilation by using
environmental parameters like wind velocity with direction
and outside air temperature. Measures the indoor parameters
such as air pressure, and air velocity with direction across the
openings and the measured data are applied to the proposed
model for natural ventilation. Luo et al. [4] developed a model
for appraise the ventilation in homes. Real characteristic of
natural ventilation based on constant indoor air temperature.
And also integrated the air quality with adapted thermal
comfort for natural ventilation. Massanes et al. [5] presented
the ventilation design for underground mines and used the
geographic information data for underground infrastructure.
They suggested the controlling of underground conditions
and also suggested the ventilation circuit based on building
conditions. These studies are very useful for present research
in the context of high rise historical buildings, and temples.
B. Ventilation System and Control Module
Fuzi et al. [6] developed air ventilation system for server
room and used gas detectors to monitor the fire and exhaust
fan for fresh air in the server room. Xu et al. [7] presented
a ventilation control model for multi zone and optimized the
indoor air quality, energy consumption, and thermal comfort.
The inherent algorithm is used for optimization of temperature of particular zone. Wu et al. [8] studied the automatic
switching system for coal mine fan and ventilation unit.
Authors proposed Programmable Logic Control (PLC) based
device to control and analyse the air flow rate in ventilation
system. Shilei et al. [9] proposed a ventilation monitoring
system (VMS) for tunnel construction based on the WiFi and
Bluetooth technology. Authors used dust, air velocity, temperature, and gas sensors to monitor the ventilation status of tunnel.
Kievit [10] developed a cabin air filter for real life conditions.
The developed filters are experimentally tested for food fume,
smoke, and other chemicals. Blaschke et al. [11] developed
an air quality gas sensor array for car cabin. The odor are
discriminated experimentally for the three different cases such
as bio-effluents (flatulence), fast-food odor, cigarette smoke,
and manure.
Comprehensive literature review shows that the existing
ventilation system for monitoring fan rpm and control is based
on the electro-mechanical components. In the existing system,
multichannel long range real-time monitoring and control of
exhaust fan functioning information such as switched on-off,
jamming, measurement of air flow through forced and natural
draft and ventilation control strategy for temples and high rise
historical buildings is not present.
A wireless sensor network based air ventilation monitoring
and control (VMC) system is designed with the integration of
environmental parameters. The exhaust fan’s running information and control of the ventilation for good indoor air quality
has been successfully developed. The developed system is
capable of monitoring the status of exhaust fan based on
real-time parameters such as air flow, vibration, revolutions
per minute (rpm), and current consumption with the help
of wireless sensor-actuator network and visual studio based
GUI application. This system is also capable of ventilation
control in high rise historical temples considering real-time
monitoring of outdoor and indoor environmental parameters
such as relative humidity, CO2 , and temperature. The block
diagram of the developed ventilation monitoring and control
system is shown in Figure 2.
The developed system consists of the multi-channel sensor array with signal conditioning, ZigBee communication,
actuators, and graphical user interface. The running status of
exhaust fan based on air speed, vibration, current, and rpm
parameters are measured in real-time and displayed. The control strategy of the ventilation system based on real-time monitoring of environmental parameters such as CO2 level, relative
humidity and temperature has been developed. The Arduino
Uno board is working as a processing unit and connected to
the ZigBee wireless module. The real-time parameters of the
exhaust fan are transmitted via ZigBee communication to and
from the ZigBee control center. The visual C# app is using
for display and control the exhaust fan installed at the top of
the Shree Jagannath Temple. The photograph of the developed
ventilation monitoring and control system (VMCS) is shown
in Figure 3.
A. Sensor Array
A sensor array is a cluster of sensors such as air flow, rpm,
vibration, current, CO2 , temperature, and relative humidity.
Fig. 2.
Block diagram of the Temple ventilation monitoring and control
Fig. 3. Photograph of the prototype ventilation monitoring and control system
for the Temple (test bed set-up).
The selection of the sensors for real-time monitoring of
exhaust fans running information and ventilation control based
on sensor characteristics and performance is based on the three
main parameters such as power, cost, and accuracy for VMC
system. The developed sensor module specifications are given
in Table I and other components are discussed herein. The
development techniques of sensor and actuator was reported
in [12]–[24] and [30].
1) Air Speed Measurement: In the present research,
the authors have used the Omron D6F-V sensor for measuring the air speed of the exhaust fans. The air speed is a
measurement of the mass of air flowing through the specific
area per unit time. An air speed sensor measures massflow and converts into the air velocity. The air speed sensor
characteristics, advantage, and disadvantage is reported in [25].
The air speed of exhaust fans is calculated within the range
of 0.5 to 2V. The response time and power consumption of the
developed air speed sensor module is observed as 5 seconds
and 15mW, respectively.
2) Vibration Measurement: The Minisense-100 vibration
sensors are used in the measurement of vibration of exhaust
fans. The vibration sensor behaves electrically as an active
capacitor. When the sensor is mounted horizontally and the
acceleration in the vertical plane produces a piezoelectric
response in term of output voltage across the sensor electrodes.
The sensor is used to detect on-line vibration [14], [15].
A high-pass filter is formed from resistance and sensor
capacitive response to calculate the frequency. The impedance
of the sensor is approximately 650M at 1Hz frequency [26].
The advantages, disadvantages and application were reported
in [26]. The vibration of exhaust fans is calculated within
the range of 0.65 to 6.5Hz. The response time and power
consumption of the developed vibration sensor module is
found to be 2 seconds and 10mW, respectively.
3) Optical RPM Measurement: The revolution per
minute (rpm) is an amount of the number of rotations around
a fixed axis in one minute. Optical technique based sensor
is used to measure rpm of exhaust fan. The simple rpm
measurement of a rotating shaft is based on velocity feedback
technique in which a DC generator is connected to the
rotating shaft. The induced voltage across the terminals of the
generator is proportional to the speed of the shaft [16]–[18].
Nowadays, optical rpm measurement device is in use which
has no physical contact to the rotating shaft. The physical
contact is avoided by using an optical detection method that
consists of an infrared light emitting diode and a photo
detecting diode. The infrared light emitting diode transmits
an infrared light towards the rotating fan blade and the photo
detecting diode collects the reflected light beam. The arrangement of optical infrared sensors is placed at about 100mm
away and facing towards the rotating fan blade. A small spot
of white shinning color is painted to the rotating fan blade to
reflect the incident infrared light when it passes in front of the
sensor, which occurs once per rotation. The rpm measurement
of exhaust fans is calculated within the range of 1 to 3000rpm.
The response time and power consumption of the developed
optical rpm sensor module is found to be 60 seconds and
150mW, respectively.
4) Current Measurement: The load measurement of the
exhaust fan in active mode or de-active mode is the main
task in exhaust fan’s running information and ACS712 hall
current sensor is used for load measurement. The current flow
in a wire is measured from the current sensing device. There
are five commonly used technologies for current sensing and
these are: Hall-Effect, fluxgate transformer, fibre optic, and
current clamp meter. Meticulous sensible like as usage, life
time, advantages, and disadvantages of the used technologies
are reported in [19] and [27].
The load of exhaust fans is calculated within the range of
−2A to +2A. The response time and power consumption of
the developed current sensor module is observed as 60 seconds
and 70mW, respectively.
5) CO2 Electrochemical Gas Sensor: The CO2 electrochemical gas senor module is developed to measure the
indoor and outdoor CO2 gas concentration. In this system,
the CO2 module consists of a CO2 electrochemical sensor,
signal conditioning, and unity gain operational amplifier. The
CO2 sensor is unified with one reference electrode and one
working electrode. The instrumentation amplifier (AD620)
is used for signal conditioning of the CO2 electrochemical
sensor [21], [29].
The overall voltage gain of the circuit is obtained using the
Equation 1.
G =1+
49.4K RG
Where, RG is the gain resistance in and G is the overall
voltage gain of the circuit.
The concentration of CO2 is calculated using output voltage
of CO2 sensor by the Equation 2.
CC O2 ( ppm) = K × VOU T −C O2
Where, Vout−CO2 is the output voltage of CO2 sensor in volt,
CCO2 is the concentration of CO2 in ppm, and K is the
proportionality factor (K = 350).
The concentration of CO2 is calculated within the range
of 50ppm to 1500ppm. The response time and power consumption of CO2 electrochemical sensor module is analyzed
as 3 minute and 1.5mW, respectively.
6) Temperature and Humidity Sensor: The temperature sensor (LM35CZ) and humidity sensor (HIH4000) are used to
measure the indoor and outdoor environmental parameters of
the Temple. The developed humidity and temperature modules
range from 0% to 100%, and 15°C to 70°C, respectively. The
response time and power consumption of the humidity sensor
module is observed as 15 seconds and 1.0mW, respectively.
The response time and power consumption of the developed
temperature sensor module is observed as 2 seconds and 2mW,
In this work, Arduino Uno board is used as a processing
unit. The processing unit and high power exhaust fans circuit was integrated through MCT2E (Opto Coupler) IC and
the MCT2E work as an isolator [28]. It means the isolator
exchange the signals between processing unit and exhaust fans.
The application, advantage, and disadvantage of the Arduino
Uno board is reported in [29] and [30].
B. Control Mechanism and Ventilation System
Currently, the Temple ventilation control system is either
working continuously or controlled manually by switching it
on before the Morning Prayer time and switch it off after
of the evening prayer. It means that the exhaust fans operate
continuously at same rpm (revolution per minute) throughout
the day and thus consume more power. In present operation
mode it is quite possible that the exhaust fans are in operation
when it might not be needed, so interventions are required to
improve its operation efficiency. Therefore, a self-sensing fan
based airtight room ventilation control has been investigated
and a highly sensitive pressure sensor is used and the indoor
and outdoor pressure is measured. And based on the pressure
differential the fan is controlled [14].
Zhang et al. [31] developed a home energy management
model for controlling the heating, cooling, and ventilation. The
authors used the machine learning demand response strategy
for the control of power consumption in home. The simulation
results showed the real-time energy demand and responses.
Sun et al. [32] proposed the model for reduction of the
daily used energy. The authors used the integrated strategies
for shading blinds and natural ventilation in the buildings.
Wang et al. [33] proposed the CO2 predictive model to forecast
the indoor CO2 . They used the particle swarm optimization
and fuzzy techniques for the indoor CO2 prediction model.
They also applied the simulation results in different situation
and different input parameters. The literature also shows that
despite some gorgeous solutions; very few are executed and
tried in real-world creating the presence of a gap between
theory and real world applications at scientifically accepted
precession level.
In this section, the control mechanism and development of
the temple ventilation system based on ASHRAE 62 standards
is presented and ventilation control strategy based on environmental parameters like as CO2 , temperature, and relative
humidity is discussed. Measurement of real-time environmental parameters is dependent on two main approach. First is
the sensor node development and their location and second
is actuator control strategy. In the proposed system, two
sensor nodes have been developed for measuring indoor and
outdoor real-time environmental parameters. The photograph
of the developed wireless sensor node is shown in Figure 4,
respectively. The first sensor node is situated inside the Temple
and set at a height of 1.1 meters above the ground surface.
The second sensor node is situated outside the Temple and
set at a height of approximately 8 meters. Both the sensor
nodes transmit the signal to the developed actuator through
ZigBee communication. The actuator receives the signal of the
sensor node 1 and sensor node 2. The actuator processing unit
works as a decision maker and follows the developed control
mechanism. The decision maker compiles the received data
every 10 minutes’ intervals.
The ventilation control mechanism is based on the differential gas concentration, differential temperature, and differential
relative humidity based on the mathematical relation as shown
in Equation 3.
C = C I − C O ; C I = C O +
Where, C is the differential concentration in ppm range,
CI is the CO2 concentration level inside the Temple in ppm
Fig. 4.
Photograph of the developed sensor node.
Fig. 5.
Developed multi-channel actuator.
range, CO is the CO2 concentration level outside the Temple
in ppm range, N is CO2 generation rate per person, and VO is
the outdoor airflow rate per person. The control mechanism
of the ventilation system is divided into two possibilities.
The first possibility is; the CO2 concentration level exceeds
the threshold value i.e. the exhaust fans 1 to 4 are active.
The second possibility is the difference between inside and
outside the real-time measuring environmental parameters.
It means the inside parameters values are more to the outside
environmental parameters values i.e. the exhaust fans 1 to 4 is
active otherwise de-active. For testing purpose, the threshold
values of CO2 sensor are fixed at 1000 ppm. Hence the
prototype ventilation monitoring and control system is tested
in 303 Efficiency of Building Laboratory, in Central Building
Research Institute Roorkee. Figure 5 represents the developed
multi-channel actuator for high rise historical buildings and
C. Machine-to-Machine Communication
The data communication between devices is known
as Machine-to-Machine communication. The Machine-toMachine (M2M) communication is the vital technology for
quicker and secure data transfer between remote sensor and
control unit without manual supporting buildings, smart grids
etc. There are many protocols for communication between
devices like UDP, TCP/IP, and wireless network. The M2M
communication approaches are reported in [22]–[24].
1) Wireless Communication: A building automation, security and management system exploitation using Internet-ofThings (IoT) and wireless technology is outcome of human
being. The developed system is using efficient implementation
of wireless technology for monitoring and controlling the
ventilation in buildings [8]. A wireless sensor network (WSN)
consists of the transceiver module integrated with sensors to
transmit data over the long distance. A WSN system also
includes a gateway that delivers wireless connectivity to the
wired zone and distributed sensor nodes [9]. The advantage,
disadvantage, and applications are reported in [12]. The main
advantage of ZigBee communication is low cost and low
power consumption. Based on these characteristics, the ZigBee
communication is used for the development of ventilation
monitoring and control system.
The signal strength testing was done through X-CTU and it
was tested on the vertical transmission distance of 60m with
no error in data transmission and after 60m the successful
transmissions decrease rapidly. Initial −58 dB signal strength
was measured at a 10m transmission distance, after which
the signal strength decays exponentially to a value of −92dB,
where the successful transmissions start decreasing.
The range test was done to verify a successful vertical
transmission distance of 60m and an error rate of less than
4%, with a maximum transmission period of 2 seconds. The
X-CTU software range test sent a data packet consisting
of 32 bytes. The software waited for the data to be sent back
from the indoor module within a certain time period. This time
period was specified as 1 second. If no packet was received,
then the transmission was indicated as a failure. A transmission
success rate of 100% was achieved up to 60 m (vertical).
The results of test through 1 walls and distance 60 m vertical
2) Graphical User Interface: The users are interacting with
electronics devices through visual indicators and graphical
icons known as Graphical User Interface (GUI). Currently,
Graphical User Interface based instrument is operated easily
and the users monitor and control the measuring parameters
simply through visual icons. The exhaust fans real-time data
is received at the control center. The control center has
the feature of Microsoft Integrated Development Environment (MIDE), in which Microsoft Visual Studio is used to
develop GUI computer apps, web apps, and mobile apps.
The GUI app is used to interact with microelectronic devices
through graphical signs and visual gauges, instead of script
based interfaces [10], [11]. Figure 6 represents the GUI apps
during testing of overall ventilation system. The real-time
air flow, vibration, rpm (revolution per minute), and current
data of ventilation system is tested in the laboratory. The
GUI app consists of individual panel for each exhaust fan.
Each panel contains fan visual status, rpm, current, air flow
dialog, and vibration plot. In the panel, rpm dialog and current
dialog shows the 1332 rpm and 340.29mA respectively. The
air flow dialog describes the level of air flow (low, medium,
Fig. 6.
Fig. 7.
Developed GUI App for the ventilation monitoring and control
Real-time data measurement of the CO2 sensor.
and high) and velocity. In the developed ventilation monitoring
and control system, the level of air flow is high at 3.06m/s
velocity. The overall system response time and data rate is
around 100ms and 250Kbit/s respectively based on hardware
interrupts handling.
D. Calibration of the Sensor Module
The calibration is the most important part in a system
design. It is essential to calibrate the system after a time
interval for achieving the desired accuracy and reliability of the
system. The re-calibration of the gas sensor after integration
is very important and based on literature; two methods are
available such as static and dynamic chamber methods. In the
proposed study, a static chamber method facility is developed
in CSIR-CBRI laboratory.
Firstly, the zero and span values of the developed modules
have been defined and then the pure nitrogen is used to calibrate the zero value (standby voltage) of the developed sensor
module. The static chamber method required targeting gas
with known gas concentrations such as 200ppm to 1500ppm,
etc. (set the pressure valve approximately 30 liters/hour flow
into the gas inlet and after 2 minutes a stable signal appears).
The CO2 electrochemical sensor module accuracy is based on
standard CO2 data logger Trak Plus Q-8552 & 8554 is ±3%.
The temperature and humidity sensor modules calibration
is based on the standard instruments such as HOBO H8 temperature & humidity data logger and finally an accuracy
of the developed modules achieved is ±0.6% and ±0.8%,
Wireless sensor network based ventilation monitoring and
control system was developed successfully. Air flow, vibration, rpm (revolution per minute), current, CO2 , temperature,
and relative humidity sensors were successfully implemented.
Two-sensor nodes with ZigBee communication were developed. In the experimental study first sensor node was kept
inside the laboratory and the second was kept outside the laboratory. Both sensor nodes were tested successfully. Actuator
node has been developed based on ZigBee communication.
Control mechanism was successfully implemented through the
Fig. 8.
Real-time data measurement of the temperature and humidity.
performance of exhaust fans 1 to 4. C# based GUI app was also
developed successfully. Calibration process was completed and
the developed sensor modules were successfully tested in the
laboratory. Figure 7 shows the real-time data measurement of
the CO2 gas concentration of 24-hour duration in the laboratory. Measured minimum and maximum CO2 concentration
values are 410ppm and 450ppm, respectively. Figure 8 shows
real-time data measurement by temperature and humidity
sensors. Figure 9 shows the real-time measurement of the
current and optical RPM sensor module. In Figure 9, we have
proposed the load current and rpm data if exhaust fan is
ON or running condition. We have received some spike in
different time interval, this is basically depending upon the
response of acs712 current sensor. The acs712 current sensor
sense the load current based on the principle of hall-effect
with high sensitivity (66-185mV/A). Due to the ability of
the current sensor to sense current flow precisely in mA
range current fluctuating range is 340.29mA to 366.44mA
(approximately 0-26.15mA) in Figure 9. The fluctuations in
current is less (in mA range) and these current fluctuation is
not affecting the exhaust fan speed curve in Figure 9.
Results obtained from real-time vibration and air flow
sensor modules are shown in Figure 10. Table II represents
the developed sensor module range, power consumption, and
response time.
Power consumption of the developed indoor and outdoor
sensor modules are observed both are same value 180mW.
Fig. 9. The real-time plot of current and optical RPM measurement module.
Fig. 10.
The real-time plot of vibration and air flow module.
fans running information module has also been implemented.
Developed sensor nodes for real-time indoor and outdoor
monitoring of environmental parameters have been tested in
CSIR-CBRI laboratory. Controlling of actuator devices based
on proposed control strategy was tested. Visual C# based GUI
app for ventilation monitoring and control (VMC) system was
developed and executed in the laboratory. Calibration process
was done to achieve the desired accuracy of the developed
sensor node with integrated devices. Impressive features of
the developed system are low cost, fast response, low power
consumption and wide zone for handling problems of real-time
ventilation system in Shree Jagannath Temple, Puri, India. The
developed system is installed in the Temple and feedback from
the users shall be considered in further improvement of the
ventilation system.
The developed VMC system is consuming 3.38KWh
power per day whereas the commercial available ventilation systems consume power from 73.38KWh/day to
744.8KWh/day [33], [34]. The comparative study shows
that the power consumption is high of the existing ventilation system in the comparison of developed VMC system. The cost of the developed system is approximately
US$ 400.
Accuracy of the developed CO2 , temperature, and relative
humidity module is ±3%, ±0.6% and ±0.8%, respectively.
Based on the developed module accuracy, the performance of
the developed VMC system is scientifically acceptable.
Similarly, the future research will focus on the design of
enabled Internet of Things (IoT) for world-wide decisionmaking. There is also need to study the wireless signal
characterization in high rise tunnel type buildings, monuments,
and Temples.
Power consumption of the developed ventilation module and
control center are observed as 415mW and 120mW, respectively. Total power consumption of the developed ventilation
monitoring and control system is 895mW without exhaust fans
and 281W with four exhaust fans.
In this study ventilation monitoring and control (VMC)
system for historical buildings, monuments, and temples has
been developed. Sensor node for real-time monitoring of
the environmental parameters such as CO2 , temperature, and
relative humidity has been implemented successfully. Exhaust
[1] Ventilation for Acceptable Indoor Air Quality. ASHRAE, Atlanta, GA,
USA, 2007.
[2] H. Hao, Y. Lin, A. S. Kowli, P. Barooah, and S. Meyn, “Ancillary
service to the grid through control of fans in commercial building
HVAC systems,” IEEE Trans. Smart Grid, vol. 5, no. 4, pp. 2066–2074,
Jul. 2014.
[3] S. Kalogirou, M. Eftekhari, and L. Marjanovic, “Predicting the pressure
coefficients in a naturally ventilated test room using artificial neural
networks,” Building Environ., vol. 38, pp. 399–407, Mar. 2003.
[4] Z. Luo, J. Zhao, J. Gao, and L. He, “Estimating natural-ventilation
potential considering both thermal comfort and IAQ issues,” Building
Environ., vol. 42, no. 6, pp. 2289–2298, 2007.
[5] M. B. Massanes, L. S. Pera, and J. O. Moncunil, “Ventilation management system for underground environments,” J. Tunneling Underground
Space Technol., vol. 50, pp. 522–561, Aug. 2015.
[6] M. F. M. Fuzi, M. N. F. Jamaluddin, and M. S. N. Abdulah, “Air
ventilation system for server room security using arduino,” in Proc. IEEE
5th Control Syst. Graduate Res. Colloquium, Shah Alam, Malaysia,
Aug. 2014, pp. 65–68.
[7] X. Xu, S. Wang, Z. Sun, and F. Xiao, “A model-based optimal ventilation
control strategy of multi-zone VAV air-conditioning systems,” Appl.
Thermal Eng., vol. 29, pp. 91–104, Jan. 2009.
[8] X. Wu, X. Ma, and Z. Ren, “Study on key technologies of coal
mine main fan automatic switchover with ventilation unceasing,” in
Proc. IEEE Chin. Control Decision Conf., Xuzhou, China, May 2010,
pp. 3199–3203.
[9] L. Shilei, W. Dong, C. Lizhi, and B. Xuhui, “Tunnel construction
ventilation monitoring system based on fieldbus technology,” in Proc.
Int. Conf,. Ind. Inf.-Comput. Technol., Intell. Technol., Ind. Inf. Integr.,
Wuhan, China, Dec. 2016, pp. 61–64.
[10] O. Kievit, “Cabin air filter loading under real-life conditions,” in Proc.
Adv. Filtration Separat. Technol., vol. 11. 1998, pp. 187–192.
[11] M. Blaschke, T. Tille, P. Robertson, S. Mair, U. Weimar, and H.
Ulmer, “MEMS gas-sensor array for monitoring the perceived carcabin air quality,” IEEE Sensors J., vol. 6, no. 5, pp. 1298–1305,
Oct. 2006.
[12] A. Kumar, V. Srivastava, M. K. Singh, and G. P. Hancke, “Current status
of the IEEE 1451 standard-based sensor applications,” IEEE Sensors J.,
vol. 15, no. 5, pp. 2505–2513, May 2015.
[13] N. Ahuja, C. W. Rego, S. Ahuja, S. Zhou, and S. Shrivastava, “Real
time monitoring and availability of server airflow for efficient data center
cooling,” in Proc. IEEE Symp. Semiconductor Thermal Meas. Manage.,
Mar. 2013, pp. 243–247.
[14] Y. Kurihara, T. Kaburagi, and K. Watanabe, “Room ventilation control
by a self-sensing fan,” IEEE Sensors J., vol. 16, no. 7, pp. 2094–2099,
Apr. 2016.
[15] T. Deng, D. Chen, J. Wang, J. Chen, and W. He, “A MEMS
based electrochemical vibration sensor for seismic motion monitoring,” IEEE J. Microelectromech. Syst., vol. 23, no. 1, pp. 92–99,
Feb. 2014.
[16] P. Cheng, Y. Yang, and B. Oelmann, “Stator-free RPM sensor
using accelerometers—A statistical performance simulation by Monte
Carlo method,” IEEE Sensors J., vol. 11, no. 12, pp. 3368–3376,
Dec. 2011.
[17] P. Cheng, M. S. M. Mustafa, and B. Oelmann, “Contactless rotor RPM
measurement using laser mouse sensors,” IEEE Trans. Instrum. Meas.,
vol. 61, no. 3, pp. 740–748, Mar. 2012.
[18] L. Wang, Y. Yan, Y. Hu, and X. Qian, “Rotational speed measurement
through electrostatic sensing and correlation signal processing,” IEEE
Trans. Instrum. Meas., vol. 63, no. 5, pp. 1190–1199, May 2014.
[19] P. Gao, S. Lin, and W. Xu, “A novel current sensor for home energy
use monitoring,” IEEE Trans. Smart Grid, vol. 5, no. 4, pp. 2021–2028,
Jul. 2014.
[20] P. Corke, T. Wark, R. Jurdak, W. Hu, P. Valencia, and D. Moore,
“Environmental wireless sensor networks,” Proc. IEEE, vol. 98, no. 11,
pp. 1903–1917, Nov. 2010.
[21] M. Li and H. J. Lin, “Design and implementation of smart home
control systems based on wireless sensor networks and power
line communications,” IEEE Trans. Ind. Electron., vol. 62, no. 7,
pp. 4430–4442, Jul. 2015.
[22] A. Singh, A. Kumar, and A. Kumar, “Network controlled distributed
energy management system for smart cities,” in Proc. IEEE 2nd
Int. Conf. Commun. Control Intell. Syst., Mathura, India, Nov. 2016,
pp. 235–238.
[23] A. Kumar, H. Kim, and G. P. Hancke, “Environmental monitoring
systems: A review,” IEEE Sensors J., vol. 13, no. 4, pp. 1329–1339,
Apr. 2013.
[24] Z. Fan, R. J. Haines, and P. Kulkarni, “M2M communications for Ehealth and smart grid: An industry and standard perspective,” IEEE
Wireless Commun., vol. 21, no. 1, pp. 62–69, Feb. 2014.
[25] OMRON. (Jan. 15, 2017). MEMS Flow Sensors, D6F-V03A1. [Online].
[26] (Feb. 25, 2017). MiniSense 100 Vibration Sensor. [Online]. Available:
[27] (Mar. 13, 2017). ACS712 Current Sensor. [Online]. Available: http://
[28] AlphaSense. CO2-D1 Sensor. Accessed: Jan. 10, 2011. [Online]. Available:
[29] (Jun. 15, 2015). Arduino Uno Board With ZigBee. [Online]. Available:
[30] J. Brito et al., “An intelligent home automation control system based on
a novel heat pump and wireless sensor networks,” in Proc. IEEE Int.
Symp. Ind. Electron. (ISIE), Jun. 2014, pp. 1448–1453.
[31] D. Zhang, S. Li, M. Sun, and Z. O’Neill, “An optimal and learningbased demand response and home energy management system,” IEEE
Trans. Smart Grid, vol. 7, no. 4, pp. 1790–1801, Jul. 2016.
[32] B. Sun, P. B. Luh, Q.-S. Jia, Z. Jiang, F. Wang, and C. Song, “Building
energy management: Integrated control of active and passive heating,
cooling, lighting, shading, and ventilation systems,” IEEE Trans. Autom.
Sci. Eng., vol. 10, no. 3, pp. 588–602, Jul. 2013.
[33] Z. Wang and L. Wang, “Intelligent control of ventilation system for
energy-efficient buildings with CO2 predictive model,” IEEE Trans.
Smart Grid, vol. 4, no. 2, pp. 686–693, Jul. 2013.
[34] A. Chatterjee, X. Xia, and L. Zhang, “Optimisation of mine ventilation
fan speeds on demand,” in Proc. IEEE Int. Conf. Ind. Commercial
Energy (ICUE), Cape Town, South Africa, Aug. 2014, pp. 1–7.
Abhishek Singh (S’16) received the M.E. degree
in electronics and communication from Panjab University, Chandigarh, India, in 2013. He is currently
pursuing the Ph.D. degree with the Council of
Scientific and Industrial Research-Central Building
Research Institute (CSIR-CBRI), Roorkee, India,
and Uttarakhand Technical University, Dehradun,
India. He is a Senior Research Fellow with the
Division of Energy Efficiency, CSIR-CBRI. His
research interest includes intelligent buildings,
wireless sensor-network, sensor fusion, and instrumentation and measurement.
Yadvendra Pandey is currently a Chief Scientist with the Council of Scientific and Industrial
Research-Central Building Research Institute, Roorkee, India. His field interests include historical buildings/monuments and landslides aspects based on
instrumentation and measurements.
Ashok Kumar received the degree (Hons.) in architecture from Jawaharlal Nehru Technological University, Hyderabad, in 1989, the MURP (Hons.)
in 1998, and the Ph.D. degree from IIT Roorkee,
Roorkee, India, in 2016. He was with the Council of
Scientific and Industrial Research-Central Building
Research Institute as a Scientist ’B’ during 1990.
He is currently a Senior Principal Scientist and the
Group Leader/Head of the Architecture and Planning
and Efficiency of Building.
He has made significant contributions in handling
multitasks. Some of these are: he had an opportunity to nurture young
talents while teaching at IIT Roorkee as a Visiting Faculty for about
15 years (1998–2012) and guided about 30 UG, PG, and Ph.D. students
for their dissertation and internships as well as Professor AcSIR; developed
guidelines, byelaws and code of practice on use of glass for buildings;
published 81 papers in international and national journals, conferences, and
delivered over 80 keynote and invited lectures on different themes to engineers
and architects. He also contributed to several National Committees of the
Bureau of Indian Standards and National Building Code, Energy Conservation
Building Code and Resource Person to many organizations as a Member
Expert. Hence, during a span of 28 years of professional, research, and
teaching carrier, the excellent application-oriented research and development
contributions, have paved the way for the advancement of research by
partnering with frontline institutions both national and international in the
area of energy efficiency in buildings and smart cities by completing over
85 research and development projects.
The outstanding achievements have directed toward the furtherance of
pioneering research in the area of energy efficiency, green buildings and
retrofits. The expertise attained has culminated into winning two international
projects and one national project, leading to self-financing research and
development through external funding of about INR 1590.20 lakhs during
the last one and half year. He is currently contributing as a member of the
ISO Working Group Committee on Solar Heat Gain Coefficient Measurement.
Manoj Kumar Singh received the M.Tech. degree
in energy technology from Tezpur University, and
the Ph.D. degree in built-environment design and
instrumentation from the Indian Institute of Technology Delhi. He is a JSPS Post-Doctoral Fellow
with the Department of Human and Social Systems, Institute of Industrial Science, The University
of Tokyo, Tokyo, Japan. His research interest is
smart building, indoor environment quality, building
energy simulation, and performance and industrial
design. He is a member of ASHRAE, International
Solar Energy Society and a Life Member of the Indian Solar Energy Society.
Anuj Kumar (M’11–SM’16) received the M.Phil.
degree in instrumentation from the Indian Institute of Technology Roorkee, Roorkee, India,
in 2000, the M.Tech. degree in instrumentation from
the National Institute of Technology Kurukshetra,
Haryana, India, in 2004, and the Ph.D. degree in
embedded systems from the Indian Institute of Technology Delhi, India, in 2011.
He is currently a Ramanujan Fellow and an Assistant Professor (AcSIR Faculty) with the Department of Energy Efficiency, Council of Scientific and
Industrial Research-Central Building Research Institute Roorkee, India. He
was a Post-Doctoral Fellow with the University of Seoul, Seoul, South Korea,
University of Pretoria, Pretoria, and the National University of Singapore,
Singapore, from 2011 to 2015. His research interests include intelligent
systems, sensor-actuator development for smart city and smart buildings, and
wireless sensor network. He is a Senior Member of the IEEE Societies of IES,
Sensors, and Instrumentation and Measurement. He is an Associate Editor of
Subhas Chandra Mukhopadhyay (M’97–SM’02–
F’11) is currently a Professor of Mechanical
and Electronics Engineering with the School of
Engineering, Macquarie University, Sydney, NSW,
Australia. He has authored/co-authored over
400 papers in different international journals,
conferences, and book chapter. His fields of
interest include sensors and sensing technology,
instrumentation, wireless sensor networks, Internet
of Things, mechatronics, and robotics.
He has edited 15 conference proceedings. He has
also edited 17 special issues of international journals as a Guest Editor and
30 books. He is a Fellow of IET (U.K.), and IETE (India). He is a Topical
Editor of the IEEE S ENSORS J OURNAL, and Associate Editor of the IEEE
Founding Chair of the IEEE Instrumentation and Measurement Society New
South Wales, Australia Chapter. He is a Distinguished Lecturer of the IEEE
Sensors Council (2017–2019).
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