9.1 Introduction

Life, as we are aware, could not exist without fresh water. Water gives oil for living cells, the very structure squares of life. Water circulates through living creatures, moving materials, for example, supplements to our organs, encouraging the synthetic responses that drive life’s capacities, and eliminating waste materials [5]. Water performs comparative capacities for whole biological systems as it accomplishes for person creatures. It circles far and wide, moving supplements and building materials to environments, encouraging the substance correspondence between biological systems, and also purifying biological systems so they can keep up ideal execution. In addition, the solid arrangement of great water for human employments relies upon the sound working of environments, especially freshwater biological systems. Water and rock appear and transform into different structures as an element of the sceptical material science of the Universe.

9.2 Water Management Using IoT

IoT in water treatment utilizes the idea of reasonable sensors put in at various focuses inside the water framework. These sensors gather data and send it back to the perception frameworks. This information may incorporate, water quality, temperature changes, pressure changes, water spill location, and synthetic break discovery. In the Figure 9.1 shows the water quality factors and main structure, IoT in water treatment lies a dependable correspondence innovation that is acclimated send information from actual articles over a remote channel to a PC with shrewd investigating programming. Cell phones and tablets will have applications that interface with the cloud or be incorporated with an EAM CMMS framework to get to the IoT detecting component information continuously [2]. This innovation can encourage experts, designers, and elective office the board labourers to ask experiences where they are or places designs ordinarily cannot reach.

An IoT-empowered reasonable water sensor can follow quality, weight, and temperature of water. Indeed, a sensor goal can live fluid stream and may be used by a water service organization to follow the stream over the whole treatment plant. This could even be a convenient instrument to incorporate with an EAM CMMS subsequently you will follow all the information for the plant in one clear arrangement. Specialists would then be able to get to this information, decipher the information, and make recommendations and ship off the force supervisor. IoT can even play an occupation in break location and send an on the spot receptive to a distant dashboard. These notices are prompt any place as though an architect needed to look at the sum by hand or by walking it could take hours for a retardant to be recognized. IoT has a few edges and can expand the efficiency of staff, keep them out of danger, and decrease supererogatory costs for office the executives.

9.3 IoT Characteristics and Measurement Parameters

IoT is a term indicates the inter connection of more than one heterogeneous physical components such as computing devices (processors), hardware units like sensors, relays, software modules, and any internet elements. This kind of IoT is considered as completely heterogeneous networks with multiple functionalities. IoT framework has been designed and developed based on the solutions we need for real-time problems.

This chapter needs an efficient solution for finding the quality of various water samples collected from different residential places. This effort helps the people to consume good quality water in future days [8]. At the same time, the IoT-based water quality management system can be implemented at any house itself. Therefore, the water consumers are able to check their water quality daily to take care of their health. This IoT framework saves the individuals from suffering with water related diseases.

Water contains many minerals or chemicals. In addition, water has several types of characteristics such as tastiness, appearance (color), odor, and the ingredients with it. Based on the characteristics, a few water types are consumable directly for daily life. Water cannot be identified in completely pure state but it contains more chemical and biological substances. Among these substances, a few are not harmful for health but others are toxic to living beings.

Water is collected from various resource units. All water resources are gradually polluted due to sewage water, dusts, and other industrial junks. Pollution control authorities use various water quality measurement techniques as follow.

• Physical measurement validations
• Chemical quantity validations
• Bio measurement validations

Among these techniques, physical test reveals the sensed contents of water sample collected from particular resource. It delivers the physically observed water characteristics such as color, odor, temperature, conductivity, and dissolved substances. Particularly, physical testing or any other water quality monitoring technique needs valid sample measurement threshold values for checking the quality of water [12].

Chemical test reveals the water contaminants such as pH levels, potassium, sodium, chlorine, and other chemical contents that affect the quality of water. In the same manner, biological particles are identified using various bio-instruments. However, most of the tests are conducted at specialized scientific labs. This kind of water substance analysis is useful for giving suggestions to improve the water quality. At the same time, IoT devices such as sensor and other water quality detecting devices help the common people to ensure the quality of daily water.

IoT elements and the architecture can be designed with appropriate functions that to be activated with in the computation devices (processors). The following devices and sensors are advised to create IoT-based water quality management system.

• Processor or controller units
• Water quality measuring sensors
• Relays and indicators
• Power units
• Quality fixing algorithms
• Reports and analytical results

This IoT system uses to create sequence of water substance measurements in daily basis. This helps to detect the water quality improvement or degradation.

Figure 9.2 illustrates the standard framework of IoT-based water quality management system. In this framework, tiny processor or controller units, power sources and water quality sensor modules are incorporated [15]. These sensors are developed by various manufacturers such as Yosemite, Myron, Aquas, Van Walt, and others. In the same way, IoT-based prototypes are mainly developed using notable hardware units like, Arduino, Raspberry Pi, NodeMCU, and other platforms.

In the scenario, various water samples are taken for quality measurements. These samples are evaluated with the help of quality analysis algorithms or data analysis algorithms. Each water sample has its unique chemical and physical characteristics. The sensors used in IoT architecture extracts the quality measurements of different water samples that are collected from multiple water resources.

Water quality sensors, hardware platforms, and the technical specifications are described with proper comparison. This analysis helps to build efficient water quality management system [17].

The water quality management systems are expected to produce minimal errors in the detection of water quality characteristics at any cost. This is attained with the help of necessary evaluation procedures and the suitable sensors. In addition, the water quality evaluation algorithms give more accurate results than manual predictions. These computations are carried out in the IoT processor units or controller units. In IoT platform, both microcontrollers and microprocessor are frequently used based on the hardware requirements.

9.4 Platforms and Configurations

Arduino is a free and license-free platform for developing IoT environments used to create any applications. Arduino has many controller versions and programming packages that are useful for various device management activities such as sensor readings, actuators’ output manipulation, generic input management, generic observation management, and supporting for project oriented library packages [4]. A real-time water quality management system can be developed using the Arduino hardware and software packages. Arduino hardware modules (controller) are enabled with many General Purpose Input and Output (GPIO) pins for managing I/O activities. At the same time, tiny controllers and memory units are giving sensor data manipulation facilities.

Table 9.1 gives the comparison of various Arduino versions and the characteristics. There are multiple Arduino versions are available other than these versions such as micro, flora, and menta [1]. However, these denoted versions are mostly suggested by many IoT developers.

In each version, different board types are released with notable features for supporting various IoT applications. Analyzing the needs for water quality measurements and data validations, Arduino Due shall be identified for handling multiple sensor data inputs. At the same time, Arduino helps to develop tiny prototypes with limited constraints [21]. In this case, the other IoT platform provides more vibrant water quality management solutions with inbuilt processor units and Linux-based operating system services. These hardware and software solutions are provided by Raspberry Pi modules.

Raspberry Pi boards and inbuilt applications are more flexible and faster than any Arduino boards. In this comparison, Raspberry Pi boards are equipped with multiple processor cores and efficient memory modules. In addition, they are having Linux-based Raspbian operating system services. These board editions are more suitable for real-time sensor data analysis processes than Arduino-based microcontrollers.

Generally, Arduino controllers are used to develop project prototypes rather than real implementations. For implementing IoT-based water quality management system, the need for more memory and high processor speed is inevitable at any cost. In this regard, various Raspbian operating system versions and board models are invented. Most of the Raspberry Pi boards offer more sophisticated software environments for installing additional package. This kind of facility helps to build sensor dependent data analysis programs and algorithms inside the IoT computation units (processors).

In addition, Raspbian operating system supports for program interface and hardware interface operations. In this environment, water quality measurement sensors can be installed and operated easily.

Comparably, Raspbian Pi is highly proficient to handle real-time sensor events and process the events with the help of preconfigured data analysis algorithms. In addition, most of the Raspbian Pi modules are enabled with camera input slots that are helpful to detect water qualities based on image analysis (physical test). At the same time, these modules are having more resilient transmitter blocks for transferring the water quality results from one place to another place. This helps to implement remote quality monitoring tasks.

According to these hardware and software environments, water quality sensors are identified to detect the water particles and the physical conditions. In the same way, chemical qualities can be detected with the help of appropriate sensor units [23].

Water quality sensors are manufactured by multiple companies and they are marketed by various shops (online and offline) [3]. Table 9.2 gives the details of Raspberry Pi and Arduino specifications for water quality sensors. For example, the following sensors are needed to generate daily data on successful water quality observations. The appropriate sensor values help to extract the correct water contents and characteristics. This work advises for implementing intelligent algorithms (Machine Learning and Deep Learning) for classifying accurate water characteristics based on physical, chemical and biological measurements. In this regard, the sensors need to be selected and planted on input pins of processor units.

9.5 Water Quality Measuring Sensors and Data Analysis

Many sensor manufacturing companies are available to produce different types of water quality measurement sensors that are adaptable to IoT environment. However, the following sensors are identified to provide multidimensional data from integrated sensor equipment.

Aqua-400 Probe (Six in One)

• Water conductivity, resistivity, liquefied solids, and actual salinity
• Total rate of disbanded oxygen content
• Rate of oxidation reduction potentiality
• Range of pH
• Water temperature (Fahrenheit and Celsius)
• Water pressure/level

Aqua-400 Probe is a kind of multi-sensor panel that can be inserted into any water type. This holds totally six sensors used to measure physical qualities and chemical qualities as listed above. This sensor unit has active and inactive modes of operations with accessories such as cables and user interface tools. In this units, sensor replacement slots are available that are covered by stainless steel planes. The water quality sensors shall be permanent or plug-in type. The later one is more reliable to deal with more frequent water quality measurement analysis tasks. For connecting purpose, this sensor unit has RS-232 and Modbus components are provided. In addition, this module gives 36V (Variable DC) power source. This kind of sensor units is really reactive and cost effective to check the quality of any type of water that is collected from various resources.

In the same way, the extensible version of aqua quality sensor is aqua 500 model. This sensor unit has multiple sensors to check both physical and chemical characteristics of water. At the same time, this has mobile application supported software and telemetry unit to transmit the sensor data to various locations. This sensor unit support for remote monitoring processes that is more reliable than on location monitoring tasks. Even though these sensor units help to measure the quality of water contents, there is need to improve the quality of results [7]. Nowadays, ML and DL techniques are widely used in decision making systems that are implemented for various applications.

This chapter suggests for the development for supervised and unsupervised classification techniques for analyzing the continuously producing water quality measurements. These ML and DL techniques increase the accuracy rate of water quality-based sensor data. There are notable techniques such as Support Vector Machine (SVM), Random Forest (RF), Deep Neural Networks (DNN), Recurrent Neural Networks (RNN), and other techniques [9]. These techniques are usable for analyzing the sensor data with trained datasets (standard water quality measurements). This produces home-based intelligent IoT-based water quality management systems that can be used by anyone. The basic block diagram of Intelligent IoT system for checking the quality of water contents is given below in Figure 9.3.

This kind of extensive data analysis algorithms is implemented and can be imported in to any IoT processors, controllers, or operating system services. This ML approaches minimizes the quality detection error rates that are happen due to manual analysis [18].

Water quality measurement frameworks are developed using various architectures and multiple components [6]. Among the various frameworks, IoT-based water quality analysis model gives more simple and effective real-time solutions. This model can be updated and modified using various water quality sensors and integrated sensor units. In addition, the IoT environment is supporting for both software components and hardware-based assistance. In this regard, ML and DL techniques are encouraged to analyse the real timer water sensor data patterns.

The analysis on these values provides flawless water quality ratings compared to any other manual techniques. In addition, these analyzed results can be processed for providing more statistical range of water quality databases. This helps for any person or any government that needs for improving water quality ratings [10]. This continuous practice supports for healthy life of any living beings getting water from various resources.

9.6 Wastewater and Storm Water Monitoring Using IoT

9.6.3 Information Modeling

For the storm water and wastewater management, the city and urban areas are properly maintained and well-designed water flow structure to be followed. In the city limit wastewater are collected and it should be reprocessing and reusable in the different ways [13]. If city have good control and, maintaining system for the wastewater flow and drainage system means there is no way to contiguous spreading disease to water. Figure 9.4 illustrates information modeling of smart wastewater management.

• Most of the cities do not have strong water flow, monitoring system to maintain a good water reservoir in the earth. Due to that, many of the natural resources are wasted and so much water to be polluted unknowingly.
• In the information modeling, we can place sensors to be the monitoring device to control the wastewater and storm water decentralized. Many places plotting sensor and getting information building infrastructure is very tricky task for to maintain the quality and monitoring the water resource.
• In the system consist of many databases like DB time series, object repository, and message database. How it is connected to the HTTP server via some events like think write, think even, and triggers based on the signal passed through it. RegEntity is connected between the object repository and message broker of the system [16]. N number of devices we can connect through the GPRS signal and it will have passed through the wireless sensor.
• The various contaminants like chloromethane, trichloroethylene, Tetrachloroethylene, and dichloromethane are more important of the water particles and if it is affected by the pollutants then it will become as unusable stage.
• The path loss analysis is also important for water management using IoT, and it will be calculated by the mathematical term like propagation medium of layer, free space loss, and dispersion of supress layers of the soil [20].
• The model may have evaluated by the thickness of the soil layer, asphalt layer, frequency, noise floor, soil moisture, and asphalt temperature.

9.7 Sensing and Sampling of Water Treatment Using IoT

As of late, perhaps the greatest test confronting mankind is guaranteeing an adequate flexibly of value water. From food creation to living space rebuilding, drinking water to sterilization, clean water is the most searched after resource of the human populace. Table 9.3 shows the different sensors and it company for maintaining the water quality.

The blast of our populace as of late has squeezed this significant resource. Adequate, top notch water is basic for human, creature, vegetal, and financial life, and observing water is the initial step to overseeing it. The different contaminants in need of sensing are shown in Figure 9.5.