Internet of Things for Water Quality
Monitoring and Assessment:
A Comprehensive Review
Joshua O. Ighalo, Adewale George Adeniyi, and Goncalo Marques
Abstract The implementation of urbanisation and industrialisation plans lead to
the proliferation of contaminants in water resources which is a severe public chal-
lenge. These have led to calls for innovative means of water quality monitoring and
mitigation, as highlighted in the sustainable development goals. Environmental engi-
neering researchers are now seeking more intricate techniques conducting real-time
monitoring and assessing of the quality of surface and groundwater that is assessable
to the human population across various locations. Numerous recent technologies
now utilise the Internet of Things (IoT) as a platform in water quality monitoring
and assessment. Wireless sensor network and IoT environments are currently being
used more frequently in contemporary times. In this paper, the recent technologies
harnessing the potentials and possibilities in the IoT for water quality monitoring
and assessment is comprehensively discussed. The main contribution of this paper is
to present the research progress, highlight recent innovations and identify interesting
and challenging areas that can be explored in future studies.
Keywords Actuators ·Environment ·Internet of things ·Sensors ·Sustainable
development ·Water quality
J. O. Ighalo ·A. G. Adeniyi
Department of Chemical Engineering, University of Ilorin, P. M. B. 1515, Ilorin, Nigeria
A. G. Adeniyi
G. Marques (B)
Instituto de Telecomunicações, Universidade da Beira Interior, 6200-001 Covilhã, Portugal
© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer
Nature Switzerland AG 2021
A. E. Hassanien et al. (eds.), Artiﬁcial Intelligence for Sustainable Development: Theory,
Practice and Future Applications, Studies in Computational Intelligence 912,
246 J. O. Ighalo et al.
Water is one of the most abundant natural resources in the biosphere and one that
is important for the sustenance of life on earth . The implementation of urbani-
sation and industrialisation plans lead to the proliferation of contaminants in water
resources which is a severe public challenge [2–4]. About 250 million cases of
diseases infections are annually reported world-wide due to water pollution-related
causes . Therefore, innovative means of monitoring and mitigation water pollution
are required [6–8] so that environmental sustainability can be achieved as highlighted
in the sustainable development goals (SDGs). Environmental engineering researchers
are now developing more intricate techniques for conducting real-time monitoring
and assessing of the quality of surface and groundwater that is assessable to the human
population across various locations [9,10]. The internet has powered a lot of tech-
nologies and applications which make possible in our time. The Internet of Things
(IoT) is an integration of many newly developed digital/information technologies
The IoT now has applications in diverse anthropogenic activities both in the
domestic and industrial domain . These include transportation and logistics,
healthcare, smart homes and ofﬁces , water quality assessment , tourism,
sports, climatology , aquaculture  and a host of others . More discussion
on the IoT can be found elsewhere [18,19]. Numerous recent technologies now
utilise the IoT as a platform in water quality monitoring and assessment . Wire-
less sensor network and IoT environments are currently being used more frequently
in contemporary times. The intricacies of the system require that aspects such as
software programming, hardware conﬁguration, data communication and automated
data storage be catered for .
IoT-enabled AI for Water Quality Monitoring is quite relevant for sustainable
development purposes. The presence of clean water to humans is a fundamental
part of the sixth (6th) sustainable development goal. It would be difﬁcult to assess
which water body and sources is actually clean enough to drink without water quality
monitoring. Furthermore, the utilisation of IoT-enabled AI means that any potential
water pollution arising from a point or non-point source is quickly identiﬁed and
mitigated. For 14th sustainable development which emphasises the need to protect
life below water, IoT-enabled AI for Water Quality Monitoring would ensure that
the quality of water do not go below threshold detrimental to the survival of aquatic
ﬂora and fauna.
Within the scope of the authors’ exhaustive search, the last detailed review on the
subject was published over 15 years ago by Glasgow et al. . In that time frame,
a lot has changed in the technology as much advancements and breakthroughs have
been made. It would not be out of place to revisit the topic and evaluate recent
In this chapter, the recent technologies harnessing the potentials and possibil-
ities in the IoT for water quality monitoring and assessment is comprehensively
discussed. The main contribution of this paper is to present the research progress,
Internet of Things for Water Quality Monitoring … 247
highlight recent innovations and identify interesting and challenging areas that can
be explored in future studies. After the introduction, the ﬁrst section discusses the
fundamental reasons behind water quality assessment and deﬁnes the fundamental
indices involved. The next section discusses the importance of IoT in water quality
monitoring and assessment. The hardware and software designs for IoT enabled water
quality monitoring and assessment for a smart city was discussed in the foregoing
section. This is succeeded by an empirical evaluation on the subject matter based on
published literature in the past decade and concluded by discussions on knowledge
gap and future perspectives.
2 Water Quality Assessment in Environmental Technology
Water quality refers to the physical, chemical and biological characteristics of water
. Assessment and monitoring of water quality are essential because it helps in
timely identiﬁcation of potential environmental problems due to the proliferation of
pollutants (from anthropogenic activities) . These are usually done both in the
short and long term . Monitoring and assessment are also fundamental so that
potential regulation offenders can be identiﬁed and punished . Technical details
as regards the methods for environmental monitoring is discussed by McDonald .
There are speciﬁc indices used in water quality. A water quality index (WQI) is
a dimensionless number used in expressing the overall quality of a water sample
based on measurable parameters . Many indices have been developed (as much
as 30), but only about seven (7) are quite popular in contemporary times . In all
these, the foundational information about the water is gotten from the measurable
parameters . The important measurable parameters of water quality are deﬁned
1. Chemical oxygen demand (COD): This is the equivalent amount of oxygen
consumed (measured in mg/l) in the chemical oxidation of all organic and
oxidisable inorganic matter contained in a water sample.
2. Biochemical oxygen demand (BOD): This is the oxygen requirement of all the
organic content in water during the stabilisation of organic matter usually over
a 3 or 5 day.
3. pH: This is the measure of the acidity or alkalinity of water. It is neutral (at 7)
for clean water and ranges from 1 to 14.
4. Dissolved oxygen (DO): This is the amount of oxygen dissolved in a water
sample (measured in mg/l).
5. Turbidity: This is the scattering of light in water caused by the presence of
suspended solids. It can also be referred to as the extent of cloudiness in water
measured in nephelometric turbidity units (NTU).
6. Electrical conductivity (EC): This is the amount of electricity that can ﬂow
through water (measured in Siemens), and it is used to determine the extent of
soluble salts in the water.
248 J. O. Ighalo et al.
7. Temperature: The is the degree of hotness or coldness of the water and usually
measured in degrees Celsius (°C) or Kelvin (K).
8. Oxidation-reduction potential (ORP): This is the potential required to transfer
electrons from the oxidant to the reductant, and it is used as a qualitative measure
of the state of oxidation in water.
9. Salinity: This is the salt content of the water (measured in parts per million).
10. Total Nitrogen (TN): This is the total amount of nitrogen in the water (in mg/l)
and is a measure of its potential to sustain and eutrophication or algal bloom.
11. Total phosphorus (TP): This is the total amount of phosphorus in the water (in
mg/l) and is a measure of its potential to sustain and eutrophication or algal
3 Internet of Things in Water Quality Assessment
Environmental engineering researchers are now seeking more intricate techniques
for conducting real-time monitoring and assessing of the quality of surface and
groundwater that is assessable to the human population across various locations.
Digital communication technologies are now the bedrock of modern society 
and IoT enabled water quality monitoring and assessment is a vital aspect of that.
The traditional method of water quality monitoring requires human personnel taking
the readings by instruments and logging the data  is considered inefﬁcient, slow
and expensive . In this section, the importance of IoT in water quality monitoring
and assessment is itemised in light of its advantages over the traditional methods of
water sampling and analysis utilised by environmental engineers and scientists when
conducting water quality monitoring.
1. The most signiﬁcant advantage of IoT in water quality monitoring and assess-
ment is the possibility of real-time monitoring. Here, the status of the water
quality (based on the different indices) can be obtained at any given time. This
is facilitated by the speed of internet communications where data can be trans-
mitted from the sensors in fractions of a second. These incredible speeds are not
achievable in traditional water quality monitoring.
2. IoT in water quality monitoring and assessment can be automated. This means
that it does not require the presence of human personnel to take readings and
log data . Moreover, these IoT systems would require less human resources
and eliminate human errors in data logging and computations. Automation is the
foundational concept of smart cities and its associated technologies.
3. Alongside the advantage of automation, IoT has led to the use of adaptive and
responsive systems in water quality monitoring. These smart-systems can alert
authorities or personnel regarding impending danger (such as high water level of
an impending ﬂood) or non-optimal conditions (such as in aquaponic systems)
Internet of Things for Water Quality Monitoring … 249
4. IoT in water quality monitoring and assessment is cheaper than hands-on
personnel conducting the monitoring and assessment. The cost of human
resources is minimised, and an IoT based system would not require.
4 Water Quality Monitoring Systems
IoT aims to provide a continuous presence of distinct cyber-physical systems which
incorporate and intelligence capabilities [33,34]. On the one hand, IoT has changed
people daily routine and is today included in most social activities and in particular
regarding smart city concept . On the other hand, IoT is a relevant architecture
for the design and development of intelligent monitoring systems for water quality
IoT is currently applied in different kinds of monitoring activities such as thermal
comfort [36–40], acoustic comfort  and air quality [42,43]. Moreover, IoT is
also applied in agricultural environments such as aquaponics and hydroponics [44–
47]. Water quality is crucial in agricultural activities and signiﬁcantly affect the
productivity and efﬁciency of agricultural ecosystems. IoT systems for enhanced
water quality allow to store and compare the water quality data to support the decision
making of agricultural plant managers.
The smart city concept associated with multiple strategies which aim to address the
most relevant cities challenges using computer science technologies . Currently,
cities face crucial challenges regarding their socio-economic goals and the best
approaches to meet them and at the same time, improve public health . Water
resources are an integral element of cities and are also a crucial challenge regarding
their management and quality assessment . Water contamination signiﬁcantly
affects the health and well-being of citizens, and real-time supervisor systems can
be used to detect possible contamination scenarios for enhanced public health early.
IoT systems can be located in multiple places and provide a continuous stream
of real-time water quality data to various municipal authorities to improve water
resources management. The data collected can also be used to plan interventions for
enhanced public safety .
The technologies used in the design and development of IoT systems in the water
management domain are presented in Sect. 4.1.
4.1 Hardware and Software Design
Currently, multiple technologies are available for the design and development of IoT
systems. On the one hand, numerous open-source platforms for IoT development such
as Arduino, Raspberry Pi, ESP8266 and BeagleBone . These platforms support
various short-range communication technologies such as Bluetooth and Wi-Fi but
also long-range such as GPRS, UMTS, 3G/4G and LoRA that are efﬁcient methods
250 J. O. Ighalo et al.
Fig. 1 IoT architecture
for data transmission. Moreover, IoT platforms also support multiple identiﬁcation
technologies, such as NFC and RFID identiﬁcation technologies .
At the hardware level, IoT cyber-physical system can be divided into three
elements: microcontroller, sensor and communication (Fig. 1). Commonly, an IoT
system is composed by the processing unit, the sensing unit and the communica-
tion unit. The processing unit is the microcontroller which is responsible for the
interface with the sensor part and can have integrated communication unit or be
connected to the communication module for data transmission. The sensor unit is
responsible for the physical data collection and is connected to the microcontroller
using several interfaces such as analogue input, digital input and I2C. The communi-
cation unit is related to the communication technologies used for data transmission.
These technologies can be wireless such as Wi-Fi or cabled such as Ethernet.
The data collected using the sensor unit is processed and transmitted to the Internet.
These activities are handled using the microcontroller. The analysis, visualization and
mineralization of the collected data are conducted using online services and carried
by backend services which include more powerful processing units. Multiple low-
cost sensors are available with different interface communication and support for
numerous microcontrollers which can be applied in the water management domain
4.2 Smart Water Quality Monitoring Solutions
Water quality assessment also plays a signiﬁcant role in multiple agricultural domains
such as hydroponics, aquaponics and aquaculture. In these environments water
quality must be monitored; however, the main applications involve high priced solu-
tions which cannot be incorporated in the developing countries. Therefore, the cost
of water quality monitoring system is a relevant factor for their implementation.
Internet of Things for Water Quality Monitoring … 251
On the one hand, hydroponic applications the nutrients in the water are a crucial
factor to be monitored in real-time to provide high-quality products and avoid prob-
lems related to contaminations . Therefore, water quality monitoring systems
must be incorporated as long with advanced techniques of energy consumption
monitoring since hydroponics is associated with high energy consumptions [58,59].
Moreover, real-time monitoring is essential also in aquaponics since this approach
combines the conventional aquaculture methods in the symbiotic environment of
plants and depends on nutrient-generators. In aquaponic environments, the excre-
ment produced by animals is used as nitrates that are used nutrient by plants .
On the other hand, smart cities require efﬁcient and effective management of water
Currently, the availability of low-cost sensors promotes the development of contin-
uous monitoring systems for water monitoring . Furthermore, numerous connec-
tivity methods are available for data transmission of the collected data using wireless
technologies . Bluetooth and Zigbee communication technologies can be used
to interface multiple IoT units to create short-range networks and be combined with
Wi-Fi and mobile networks for Internet connection [64,65].
Furthermore, smartphones currently have high computational capabilities and
support NFC and Bluetooth, which can be used to interface external components
such as IoT . In particular, Bluetooth technologies can be used to conﬁgure and
parametrize IoT water quality monitoring systems and retrieve the collected data in
locations where Internet access are not available. On the one hand, mobile devices
enable numerous daily activities and provide a high number of solutions associated
with data visualization and analytics . On the other hand, people commonly
prefer to use their smartphones when compared with personal computers [68,69].
The current water quality monitoring systems are high cost and do not support data
consulting features in real-time. The data collected by these systems are limited since
it is not related to the date of data collection and location. The professional solutions
available in the literature can be compact and portable. However, that equipment
does not provide a continuous data collection and sharing in real-time. Most of these
systems only provide a display for data consulting or provide a memory card for data
storage. Therefore, the user must extract the information and analyses the results
using third-party software.
TDS and conductivity pens are quickly found in the market and are also widely
used for water assessment. However, these portable devices do not incorporate data
storage or data-sharing features. The user can only check the results using an LCD
existent on the equipment. Moreover, this equipment commonly does not have any
data storage method.
The development of smart water quality solutions using up to date technologies
which provide real-time data access is crucial for the management of water resources
(Fig. 2). It is necessary to design architectures which are portable, modular, scalable,
and which can be easily installed by the user. The real-time notiﬁcations are also a
relevant part of this kind of solutions. The real-time notiﬁcation feature can enable
intervention in useful time and consequently address the contamination scenarios in
an early phase of development.
252 J. O. Ighalo et al.
Fig. 2 Smart water monitoring system
5 An Empirical Evaluation of IoT Applications in Water
In this section, a brief chronological evaluation is made of some of the interesting
empirical investigations where IoT enabled technology was utilised in water quality
monitoring and assessment. The focus will be not just on studies where an IoT-
enabled system was designed for water quality monitoring and assessment but for
studies where this technology was applied to speciﬁc water bodies within the past
Wang et al.  monitored the water quality in the scenic river, Xinglin Bay
in Xiamen, China. Their system was divided into three subsystems. There was
the data acquisition subsystem, the digital data transmission subsystem and data
processing subsystem. The indices monitored were pH, dissolved oxygen (DO),
turbidity, conductivity, oxidation-reduction potential (ORP), chlorophyll, temper-
ature, salinity, chemical oxygen demand (COD), NH4+, total phosphorus (TP) and
total nitrogen (TN). The results of the study were positive as the design was adequate
in achieving the set objectives. Furthermore, the water quality was of a good standard
as the water had a powerful self-puriﬁcation ability.
Shaﬁ et al.  investigated the pH, turbidity and temperature of surface water
across 11 locations in Pakistan, using an IoT enabled system that in-cooperated
machine learning algorithms. The four algorithms considered were Support Vector
Machine (SVM), k Nearest Neighbour (kNN), single-layer neural network and deep
neural network. It was observed from the learning process on the 667 lines of data
that deep neural network had the highest accuracy (at about 93%). The model could
accurately predict water quality in the future six months.
Saravanan et al.  monitored the turbidity, temperature and colour at water
pumping in Tamilnadu, India using a Supervisory Control and Data Acquisition
Internet of Things for Water Quality Monitoring … 253
(SCADA) system that is enabled by IoT. The technology was usable in real-time and
employed a GSM module for wireless data transfer.
In a quite interesting study, Esakki et al.  designed an unmanned amphibious
vehicle for pH, DO, EC, temperature, and turbidity of water bodies. The device could
function both in air and in water. Part of the mechanical design considerations was
in its power requirements, propulsion, hull and skirt material, hovercraft design and
overall weight. It was designed for military and civil applications with a mission of
time of 25 min, a maximum payload of 7 kg and utilised an IoT based technology.
Liu et al.  monitored the drinking water quality at a water pumping station
along the Yangtze river in Yangzhou, China. The technology was IoT enabled but
incorporated a Long Short-Term Memory (LSTM) deep learning neural network.
The parameters assessed were Temperature, pH, DO, Conductivity, Turbidity, COD
Zin et al.  utilised wireless sensor network enabled by IoT for the monitoring
of water quality in real-time. The system they utilised consisted of Zigbee wireless
communication, protocol, Field Programmable Gate Array (FPGA) and a personal
computer. They utilised the technology to monitor the pH, turbidity, temperature,
water level and carbon dioxide on the surface of the water at Curtin Lake, northern
Sarawak in the Borneo island. The system was able to minimise cost and had lesser
power requirements. Empirical investigations of IoT applications in water quality
monitoring and assessment is summarised in Table 1.
Due to the nature of the sensors, parameters like TDS, turbidity, electrical conduc-
tivity, pH and water level are the more popularly studied indices. This was quite
apparent from Table 1. It would require a major breakthrough in sensor technology
to have portable and cheap sensors that can detect other parameters like heavy metals
and other ions. The future of research in this area is likely to be investigations on
alternative sensor technologies to determine the wide range of parameters that can
adequately describe the quality of water. If this is achievable, then water quality
monitoring and assessment would be able to apply correlations of Water Quality
Index (WQI) to get quick-WQI values. This would enable rapid determination of the
suitability of water sources for drinking.
The current water quality monitoring systems are relatively expensive and do not
support data consulting features in real-time. It is predicted that researchers will
gradually shift focus from portability in design to affordability. Furthermore, the
development of smart water quality solutions using up to date technologies which
provide real-time data access is crucial for the management of water resources. It is
necessary to design architectures which are portable, modular, scalable, and which
can be easily installed by the user. Researchers in the future will likely delve into
better real-time monitoring technologies that would incorporate notiﬁcations and
social media alerts.
254 J. O. Ighalo et al.
Tabl e 1 Summary of IoT applications in water quality monitoring and assessment
Year Location Parameters monitored Ref
2019 Curtin Lake, Borneo island pH, turbidity, temperature, water level and
2019 Pumping station, Yangtze river,
Temperature, pH, DO, EC, turbidity, COD
2019 Unspeciﬁed location in
pH, turbidity, ORP and temperature 
2018 Pumping station, Tamilnadu,
Turbidity, temperature and colour 
2018 Unspeciﬁed location pH, DO, EC, temperature, and turbidity 
2018 11 locations in Pakistan pH, turbidity and temperature 
2018 Unspeciﬁed location in India pH, water level, temperature and CO2
2017 Lab setup, India pH and EC 
2017 Aquaponics system, Manchay,
near Lima, Peru
pH, DO and temperature 
2017 Aquaponic system, Chennai,
pH, water level, temperature and ammonia 
2017 Unspeciﬁed location in India pH, turbidity and EC 
2017 Unspeciﬁed location in India pH, turbidity and water level 
2017 Nibong Tebal, Malaysia pH and temperature 
2015 Unspeciﬁed location in Malaysia Wat e r level 
2013 Scenic river, Xiamen, China pH, DO, turbidity, EC, ORP, chlorophyll,
temperature, salinity, COD, NH4+,TPand
2006 7 locations in South Africa Unspeciﬁed 
2002 Tagus estuary, near Lisbon,
pH, turbidity and temperature 
Urbanisation and industrialisation plans have led to the proliferation of contaminants
in water resources which is now a severe environmental challenge. These have led to
calls for innovative means of water quality monitoring and mitigation, as highlighted
in the SDGs. The recent technologies harnessing the potentials and possibilities in
the IoT for water quality monitoring and assessment is comprehensively discussed
in this paper. Advantages of IoT in water quality monitoring and assessment are in
the possibility of real-time monitoring, automation for smart solutions, adaptive and
responsive systems and in a reduction of water quality monitoring costs. A brief
chronological evaluation is made of some of the interesting empirical investigations
where IoT enabled technology was utilised in water quality monitoring and assess-
ment in the last decade. It was observed that IoT in water quality monitoring and
assessment had not been applied to some more sophisticated parameters like heavy
Internet of Things for Water Quality Monitoring … 255
metals and other ions. The future of research in this area is likely to be investigations
on alternative sensor technologies to determine the wide range of parameters that
can adequately describe the quality of water. Cost considerations in the design and
real-time data management are also areas of future research interest on the subject
matter. The paper was successfully able to present the research progress, highlight
recent innovations and identify interesting and challenging areas that can be explored
in future studies.
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