ABSTRACT
Nowadays Internet of Things (IoT) and Remote Sensing (RS) techniques are used in different area of research for monitoring, collecting and analysis data from remote locations. Due to the vast increase in global industrial output, rural to urban drift and the over-utilization of land and sea resources, the quality of water available to people has deteriorated greatly. The high use of fertilizers in farms and also other chemicals in sectors such as mining and construction have contributed immensely to the overall reduction of water quality globally. Water is an essential need for human survival and therefore there must be mechanisms put in place to vigorously test the quality of water that made available for drinking in town and city articulated supplies and as well as the rivers, creeks and shoreline that surround our towns and cities. The availability of good quality water is paramount in preventing outbreaks of water-borne diseases as well as improving the quality of life. The development of a surface water monitoring network is a critical element in the assessment and protection of water quality. We developed a prototype of easy to install technology by which the different surface water (e.g. rivers, lakes) quality indicators can be measured. This paper presents a smart water quality monitoring system.
INTRODUCTION
Water is used in various activities, such as consumption, agriculture and travel, which may affect water quality. Therefore, the water quality monitoring is necessary which includes several chemical parameters. Some of these are: pH, redox potential, conductivity, dissolved oxygen, ammonium and chloride ion amount.
There is need to improve existing system for monitoring water bodies, given that laboratory methods are too slow to develop an operational response and does not provide a level of public health protection in real time. Improve and expand monitoring and assessment tools to ensure a statistically robust and comprehensive picture of the status of the aquatic environment for the purpose of further planning
The water quality problems of surface water bodies are predominately caused by organic and nutrient material loads. More than 90% of the River Basin Management Plans (RBMP) assessed indicated that agriculture is a significant pressure in the basin, including diffuse or point source pollution by organic matter, nutrients, pesticides and hydro-morphological impacts.
Nowadays Internet of Things (IoT) and Remote Sensing (RS) techniques are used in different area of research for monitoring, collecting and analysis data from remote locations. Due to the vast increase in global industrial output, rural to urban drift and the over-utilization of land and sea resources, the quality of water available to people has deteriorated greatly. The high use of fertilizers in farms and also other chemicals in sectors such as mining and construction have contributed immensely to the overall reduction of water quality globally. Water is an essential need for human survival and therefore there must be mechanisms put in place to vigorously test the quality of water that made available for drinking in town and city articulated supplies and as well as the rivers, creeks and shoreline that surround our towns and cities. The availability of good quality water is paramount in preventing outbreaks of water-borne diseases as well as improving the quality of life. The development of a surface water monitoring network is a critical element in the assessment and protection of water quality. We developed a prototype of easy to install technology by which the different surface water (e.g. rivers,lakes) quality indicators can be measured. This paper presents a smart water quality monitoring system.
There is need to improve existing system for monitoring water bodies, given that laboratory methods are too slow to develop an operational response and does not provide a level of public health protection in real time. Improve and expand monitoring and assessment tools to ensure a statistically robust and comprehensive picture of the status of the aquatic environment for the purpose of further planning
The water quality problems of surface water bodies are predominately caused by organic and nutrient material loads. More than 90% of the River Basin Management Plans (RBMP) assessed indicated that agriculture is a significant pressure in the basin, including diffuse or point source pollution by organic matter, nutrients, pesticides and hydro-morphological impacts.
Nowadays Internet of Things (IoT) and Remote Sensing (RS) techniques are used in different area of research for monitoring, collecting and analysis data from remote locations. Due to the vast increase in global industrial output, rural to urban drift and the over-utilization of land and sea resources, the quality of water available to people has deteriorated greatly. The high use of fertilizers in farms and also other chemicals in sectors such as mining and construction have contributed immensely to the overall reduction of water quality globally. Water is an essential need for human survival and therefore there must be mechanisms put in place to vigorously test the quality of water that made available for drinking in town and city articulated supplies and as well as the rivers, creeks and shoreline that surround our towns and cities. The availability of good quality water is paramount in preventing outbreaks of water-borne diseases as well as improving the quality of life. The development of a surface water monitoring network is a critical element in the assessment and protection of water quality. We developed a prototype of easy to install technology by which the different surface water (e.g. rivers,lakes) quality indicators can be measured. This paper presents a smart water quality monitoring system.
MOTIVATION
Water is used in various activities, such as consumption, agriculture and travel, which may affect water quality..The availability of good quality water is paramount in preventing outbreaks of water-borne diseases as well as improving the quality of life. Therefore, the water quality monitoring is necessary which includes several chemical parameters. Some of these are: pH, redox potential, conductivity, dissolved oxygen, ammonium and chloride ion amount
Objective
Monitoring Different parameters which affects the water quality like pH, temperature, turbidity, conductivity, smell detection through Blynk App.
Problem Definition:
Water is used in various activities, such as consumption, agriculture and travel, which may affect water quality. Therefore, the water quality monitoring is necessary which includes several chemical parameters. Some of these are: pH, redox potential, conductivity, dissolved oxygen, ammonium and chloride ion amount. The water quality problems of surface water bodies are predominately caused by organic and nutrient material loads. There is need to improve existing system for monitoring water bodies, given that laboratory methods are too slow to develop an operational response and does not provide a level of public health protection in real time.
Sewage water quality monitoring is also necessary because water pollution is the contamination of water bodies that occur when pollutant are indirectly or directly discharge into water bodies without adequate treatment to remove the harmful sediment. It will give an affect to ecosystem and human life and become an issue nowadays.
EXISTING SYSTEMS
Autonomous water quality monitoring system using GSM.
Good water quality is essential for the health of our aquatic ecosystems. Continuous water quality monitoring is an important tool for catchment management authorities, providing real-time data for environmental protection and tracking pollution sources; however, continuous water quality monitoring at high temporal and spatial resolution remains prohibitively expensive. An affordable wireless aquatic monitoring system will enable cost-effective water quality data collection, assisting catchment managers to maintain the health of aquatic ecosystems. In this project, a low-cost wireless water physic-chemistry sensing system is presented. The results indicate that with appropriate calibration, a reliable monitoring system can be established. This will allow catchment managers to continuously monitoring the quality of the water at higher spatial resolution than has previously been feasible, and to maintain this surveillance over an extended period of time. In addition, it helps to understand the behaviour of aquatic animals relative to water pollution using data analysis.
Using image processing technology for water quality monitoring system
As fish has been existing and adapting to the water ecological environment that it will sense physically when water quality changes. Thus, the fish responding behaviour has been taken one of the methods in monitoring water quality in recent years. This study has successfully in building a water quality monitoring system by utilizing the image processing and fuzzy inference in auto-recognizing the gesture of fish. It was our first time in setting up the image background model by using W4 method, and then adopted deduction of background in recognizing the fish profile. After finding the centre-of-gravity position of fish profile, we can obtain the real time characteristic information of fish in position, speed and moving track. Finally put these information the input of fuzzy inference system, via appropriate rules bank in analysing, the output value can be obtained. In this study, Zebra fish and Common Goldfish were adopted to be the study objects by using different into water and out of water device as well as different concentration of agent in observing the fish in response. From the result of experiment, the inferential method as proposed by this study in recognizing two kinds of fish has come to a satisfactory effect.
Design of Smart Sensors for Real-Time Water Quality Monitoring using zigbee.
This paper describes work that has been done on design and development of a water quality monitoring system, with the objective of notifying the user of the real-time water quality parameters. The system is able to measure the physiochemical parameters of water quality, such as flow, temperature, pH, conductivity, and the oxidation reduction potential. These physiochemical parameters are used to detect water contaminants. The sensors, which are designed from first principles and implemented with signal conditioning circuits, are connected to a microcontroller-based measuring node, which processes and analyzes the data. In this design, ZigBee receiver and transmitter modules are used for communication between the measuring and notification nodes. The notification node presents the reading of the sensors and outputs an audio alert when water quality parameters reach unsafe levels. Various qualification tests are run to validate each aspect of the monitoring system. The sensors are shown to work within their intended accuracy ranges. The measurement node is able to transmit data by ZigBee to the notification node for audio and visual display. The results demonstrate that the system is capable of reading physiochemical parameters, and can successfully process, transmit, and display the readings.
LIMITATIONS
· Good water quality is essential for the health of our aquatic ecosystems. Continuous water quality monitoring is an important tool for catchment management authorities, providing real-time data for environmental protection and tracking pollution sources
· Using GSM we cannot get the updates when there is network problems like rural areas and forest areas.
· Using Image processing techniques sometimes we didn’t get clear images. and
· Any how we cannot judge the purity of the water on image basis.
· Using zigbee we cannot make this system appropriate for long distances.
PROPOSED SYSTEM
We proposed a water quality monitoring system with ARM LPC2148 and Various sensors. Here we get water quality conditions through various sensors like pH level; sensor, water level sensor, turbidity, and conductivity and ARM LPC2148. The information will be uploaded continuously through Microcontroller and WiFi. We control and upload this data to cloud and users can access this data through Blynk application by installing into their phones. From this system a person from anywhere can monitor the information at anytime.
Literature survey
1. Sewere Spill
It is often assumed that the frequency or volume of combined sewer overflow (CSO) spill is a good indicator of receiving water pollution impact. Whilst this assumption would appear to be true, recently there have been challenges to its veracity. To test this basic premise, an integrated model (SYNOPSIS) has been applied to the urban wastewater system of a semi-hypothetical catchment. By increasing the storage volume at a single downstream tank in the drainage system, the CSO spill frequency and volume was reduced. River water quality criteria, based on UPM standards, were calculated and related to spill frequency and volume over a series of long-term simulation runs. It was found that, up to certain storage volume levels, decreasing overflow frequency improved river DO and BOD and total ammonia. Beyond these volumes, however, there was no further improvement in DO/BOD and an increase in total ammonia. It is concluded that overflow frequency/volume can be used as a performance indicator for receiving water quality, provided its significant limitations are understood.
2. Title: Water Quality Monitoring in Europe’s Largest Fluvial Aquarium
Nowadays Geographic Information System (GIS) and Remote Sensing (RS) techniques are used in different area of research for monitoring, collecting and analysis data from various geographical locations. Due to the vast increase in global industrial output, rural to urban drift and the over-utilization of land and sea resources, the quality of water available to people has deteriorated greatly. The high use of fertilizers in farms and also other chemicals in sectors such as mining and construction have contributed immensely to the overall reduction of water quality globally. Water is an essential need for human survival and therefore there must be mechanisms put in place to vigorously test the quality of water that made available for drinking in town and city articulated supplies and as well as the rivers, creeks and shoreline that surround our towns and cities. The availability of good quality water is paramount in preventing outbreaks of water-borne diseases as well as improving the quality of life. Fiji Islands are located in the vast Pacific Ocean which require a data collecting network for the water quality monitoring where GIS system can be applicable. This Paper presents a case study of water quality monitoring system with (key Performance Indicators) KPIs for Suva city, using GIS and remote sensing technology.
3. Title: Sea Water Monitoring For Chemical Parameters
The application of different multivariate statistical approaches for the interpretation of a large and complex data matrix obtained during a monitoring program of surface waters in Northern Greece is presented in this study. The dataset consists of analytical results from a 3-yr survey conducted in the major river systems (Aliakmon, Axios, Gallikos, Loudias and Strymon) as well as streams, tributaries and ditches. Twenty-seven parameters have been monitored on 25 key sampling sites on monthly basis (total of 22,350 observations). The dataset was treated using cluster analysis (CA), principal component analysis and multiple regression analysis on principal components. CA showed four different groups of similarity between the sampling sites reflecting the different physicochemical characteristics and pollution levels of the studied water systems. Six latent factors were identified as responsible for the data structure explaining 90% of the total variance of the dataset and are conditionally named organic, nutrient, physicochemical, weathering, soil-leaching and toxic-anthropogenic factors. A multivariate receptor model was also applied for source apportionment estimating the contribution of identified sources to the concentration of the physicochemical parameters. This study presents the necessity and usefulness of multivariate statistical assessment of large and complex databases in order to get better information about the quality of surface water, the design of sampling and analytical protocols and the effective pollution control/management of the surface waters.
4. Title: The internet of things: A survey
This paper addresses the Internet of Things. Main enabling factor of this promising paradigm is the integration of several technologies and communications solutions. Identification and tracking technologies, wired and wireless sensor and actuator networks, enhanced communication protocols (shared with the Next Generation Internet), and distributed intelligence for smart objects are just the most relevant. As one can easily imagine, any serious contribution to the advance of the Internet of Things must necessarily be the result of synergetic activities conducted in different fields of knowledge, such as telecommunications, informatics, electronics and social science. In such a complex scenario, this survey is directed to those who want to approach this complex discipline and contribute to its development. Different visions of this Internet of Things paradigm are reported and enabling technologies reviewed. What emerges is that still major issues shall be faced by the research community. The most relevant among them are addressed in details
METHODOLOGY
· All the Sensors data like pH , temperature , Conductivity, turbidity and smell detection are collected and sends to the ARM LPC2148 Microcontroller which analyze the collected data.
· The controller with the help of WiFi module sends data to the Blynk cloud server.
· From the blynk server data can be received in android phone through blynk app.
· So person can monitor water quality just by knowing different parameter values which affects the water quality and can take required measurements in order to maintain the water quality.
Hardware and Software Components Required:
Hardware:
1. Power Supply
2. pH Sensor
3. Turbidity Sensor
4. Conductivity Sensor
5. Temperature Sensor
6. LCD Display
7. WiFi Module
8. ARM LPC2148
9. MQ135 Sensor
Software:
1. Keil
2. Embedded C
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