Metering of Analysis of Industrial Waste Waterusing Cloud Computing

IDL - International Digital Library Of Technology & Research Volume 2, Issue 2, September - 2018

Available at: www.dbpublications.org

International e-Journal For Technology And Research-2018

Analysis and Metering of Industrial Waste Waterusing Cloud Computing Lingaraju M ITI (EM), ADIT, DHMN, DECE, BE (E&C), AMIT, C.Eng., ( M.Tech (VD&ES)) Dept.of VLSI Design and Embedded Systems UTL Technologies, VTU Extension Centre, Yeshwanthpur, Bangalore, Karnataka, India lingaraju.mtej@gmail.com

Abstract:

This paper deals about analysis of waste water affluent from Industries in an economical way. Industrial wastes generated through various industrial operations are of different chemical composition and complex to decompose. These wastes upon discharge, affect the normal life of a river stream or normal functioning of sewerage and sewage treatment plants, unless pre-treated at the source point itself. The waste water from industries have high proportion of suspended solids, dissolved organic and inorganic solids, COD, BOD, alkalinity or acidityalkalinity or acidity (pH levels), more temperature level. Their different constituents may not be in same proportion as they exist in a normal domestic sewage. This industrial waste water cannot always be treated easily by the normal methods used for treating domestic waste and certain specially designed methods or sequence of methods may be necessary. The detail study of effluents before discharge is necessary to reduce pollution and hence this paper is proposed. Metering also has been proposed to penalize industries if the waste content is beyond threshold levels.

As a Case Study the analysis and metering of water is been carried out randomly by collecting water samples of Bellandur lake, the most popular lake in Bengaluru, at different time using sensors and storing the measured values in a cloud (AWS-Amazon cloud Server) via GPRS for further use by the Government.

Keywords: pH level, COD, BOD, temperature, Metering, AWS

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INTRODUCTION Surface water is being polluted by anthropogenic activities. The discharge from various industries such as dairy, cane sugar, brewery, petrochemical, textile, paper and pulp have been increasing at an alarming rate making it one of the main sources of severe pollution worldwide. The important pollutants in all these waste effluents are chiefly recalcitrant, organics, colors and toxicants. The waste water possesses a huge variety of chemicals from the various stages of operations which include printing, scouring, bleaching and dyeing. The waste effluent from these units and industries are discharged in open land, agriculture land or water bodies causing adverse effects on the flora, fauna and general health of residents residing around such sites and villages/cities/towns [1][2].

The quality of wastewater effluents is responsible for the degradation of the receiving water bodies, such as lakes, rivers, streams, etc. The potential deleterious effects of polluted wastewater effluents on the quality of receiving water bodies are manifold and depend on volume of the discharge, the chemical and microbiological concentration/composition of the effluents. It also depends on type of the discharge, whether it is the suspended solids or organic matter or hazardous pollutants like heavy metals and organochlorines.

There are various Standardized Meters [3] and Measurements to gauge the pollution levels in water.

They are Water Temperature, pH level, COD and BOD levels, TOC level etc., helps to estimate the toxicity of water [2]. By monitoring these parameters [4] regularly, water pollution can be controlled by

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IDL - International Digital Library Of Technology & Research Volume 2, Issue 2, September - 2018

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International e-Journal For Technology And Research-2018 warning the industries that let go the polluted water into mainstream.

COD – Stands for Chemical oxygen demand – It is the total measurement of all the chemicals in water that can be oxidized. It provides an index to assess the effect discharged waste water will have on the receiving environment. Higher COD [4] [5] levels mean a greater amount of oxidizable organic material in the sample which will reduce the levels of dissolved oxygen levels (DO) in water. A reduced DO leads to anaerobic conditions which is perilous to aquatic life.

COD testing time is shorter compared to that of BOD.Permissible COD level as per Central Pollution Control Board (CPCB) is less than 250mg/L. pH level - [3] [4] It is the potential of Hydrogen that a liquid is measured for alkalinity or acidity. On a scale of 1 to 14, with 7 being neutral, acidic water sample will have values from 6 to 1 and alkaline water sample varies from 8 to 14. Lesser the pollution level in water more is its alkalinity.

Temperature Levels–[1] [2]of water levels vary especially if the water is polluted. Normal water has temperature around 25-27DegC but if the water is polluted the temperature crosses 32DegC. So measuring temperature is one of the methods to access pollution of water.

Controlling the flow and Metering concepts are required to alert Industries which keep letting out polluted water without any concern towards nature.

After analysis of water samples using sensors, there are various methods to transfer data to server [7] [8] like ZIgbee for live water monitoring.

IoT Concept–[9][10] is the latest method for updating sensed values In this project the analysis of water is done by sensors like PH sensor, Temperature sensor and COD levels.

Metering is done by water level / flow sensor. The measured sensor values are uploaded to cloud/server via GPRS.

1.

OBJECTIVES

The aim of the project is to characterize the waste water of industries and volume of waste water discharge and study the level of pollutants being IDL - International Digital Library

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discharged by these units. The necessity of treatment of water before its release from industries needs to be recognized. This is essential to reduce pollution inputs, particularly toxicants, to restore natural productivity and to promote sustainable development of the surroundings as well as regulate the quality of the effluent released into the environment.

The analysis of water is done by collecting water sample at random time without prior intimation to industry. If the values have crossed the pH level ie., if they are found acidic or if the temperature has crossed 40 Deg C or if the water has crossed prescribed COD level, the industry or factory is penalized which is by metering.

Government can then take required action against industries such as – applying more restrictions on chemical usage, issue notice or cancel license.

2.

IMPLEMENTATION

The Module devised here is Microcontroller-Based in combination with Wireless Technology using GPRS and on the latest technology of Amazon Web Services.

Water sample is collected from the waste water disposal area of the Industrial areas.

This sample is now to be sensed by the sensors of the Meter being developed.

Water Temperature testing: Polluted water usually has more temperature than normal un polluted water.

So testing for its temperature (more than 40Deg) using a temperature sensor is an indication of polluted water.

Water pH value testing: Polluted water will be acidic in nature, hence testing acidity level (greater than 7) using a pH level sensor is also an indication of polluted water level.

Water Flow Sensor : Also metering has to be done to calculate penalty on the polluting factories. For this, volume of water being let out from the polluting factories has to be known. The flow sensor along with metering facility is useful here.

COD Testing : Polluted water will be turbid if Chemical level is more. Hence using a simple technique by passing light and measuring its impact Copyright@IDL-2018

IDL - International Digital Library Of Technology & Research Volume 2, Issue 2, September - 2018

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International e-Journal For Technology And Research-2018 on a Light sensor like LDR, presence of chemicals in water can be checked.

Conductivity Testing : Polluted water has many chemicals which makes increases its conductivity level. Normal range should be between 100 and 200.

Electrodes of level sensor can be interfaced to ADC to test these values.

Sensors Data Processing: The controller needs to process sensors data before sending data to server.

The processed sensor data by the controller is nothing but the present condition of polluted water sample taken.

The microcontroller used is RENESAS RL78 series with 64 pins and can handle analog and digital data.

This is important because the sensors provide analog data and to communicate with GSM module digital data is required.

The Software (Embedded-C coding) is taken care by the customized RenesasCubeSuite development tool.

The Microcontroller unit operates under wide temperature range also.

Cloud Computing: The measured data is transferred through GPRS - AWS technology.

The data pattern will be coded in a string format and deciphered at the receiving end while displaying in the web location.

The Sever thus will have the database of all the water samples taken.

Fordemonstration - In the Meter being developed, the sensors like temperature Sensor, pH Sensor, InfraRed Sensor and Water-Level Sensor will be interfaced to the Renesas Microcontroller. The water samples are collected in test tube for COD testing and the same sample is collected in a bucket for temperature,pH level and flow meter interface.

A Relay is activated to pump water.

Programming is done for simplified understanding : Such as if water sample is Acidic pH value is displayed as 1, if Alkaline pH is 0.

Sensing Conductivity – If the water has to be consumed its conductivity level has to be between 100-200 which is sensed using electrodes and ADC .

If IR LED glows bright – then COD level is less.

If IR LED glows dull – then COD level is more.

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Different samples of water like – normal drinking water, salt water, foamy water, lime water, muddy water are collected for testing.

Fig 1 : Block Diagram

Fig 2 : Metering Setup

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International e-Journal For Technology And Research-2018

Fig 3: GPRS Set up for Cloud Computing

3. FLOWCHART

Fig 4: Flow Chart of Metering

4.

OUTCOMES

The result data that is transmitted in the format of the string is as below for normal cold Water: $T16P0T002C000U00A000@ T16 – 16Deg T020 – Less Turbid (less COD level) pH – 0 – Base C110 – Less Conductivity U01 – No of Units A000 – Amount Charged is NIL for good water.

The LCD display is as below:

Fig 2 : LCD Display

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IDL - International Digital Library Of Technology & Research Volume 2, Issue 2, September - 2018

Available at: www.dbpublications.org

International e-Journal For Technology And Research-2018 Other Samples are Analyzed as below: Lime water Sample $T34P1T235C240U01A020@ Acidic,More Turbid, COD is more, Temperature is 34 and Penalty amount 20 is displayed per unit.

Turbid water Sample $T32P0T378C090U01A010@ Little Alkaline, COD is more, Temperature is 32 and Penalty amount 10 is displayed per unit.

Below are the Displays of AWS login Windows which can be viewed by Authorized login:

solids, alkalinity or acidity and their different constituents may not be in same proportion as they exist in a normal domestic sewage.

Ex. Belandur Lake Effects of toxics waves frothing at Bangalore. Treatment of effluents before discharging waste water is necessary to reduce pollution by analysis and metering of Industrial waste water is been carried out randomly by collecting water samples at different time using sensors and storing the measured values in a cloud via GPRS for further use by the government. It was developed by using Embedded C programming software at VTU Extension Center, UTL Technologies Yeshwanthpura in Bangalore.

REFERENCES [1]. Impact of Industrial Effluent Discharge on

Physico-ChemicalCharacteristics of Agricultural SoilLadwaniKiran D., Ladwani Krishna D., ManikVivek S. and RamtekeDilip S. Oct 2012.

[2]. Analysis and Characterization of Industrial wastewaterKumudTanwar, Jaya Mathur-07-2016 [3].Standard Methods for the Examination of Water and Wastewater, Š Copyright 1999 by American Public Health Association, American Water Works Association, Water Environment Federation [4].Physicochemical Characterization of Textile

Waste Water www.ijird.com September, 2015 D. Vigneshpriya [5].Assessment of Physicochemical Properties of

Textile Wastewaters and Screening of Bacterial Strains for Dye Decolourisation Neha Sharma, SreemoyeeChatterjee, PradeepBhatnagarDepartment of Biotechnology, IIS University, GurukulMarg, SFS Mansarovar Jaipur-302020, Rajasthan -2013

Fig 5 : TCP window and weblogin

CONCLUSION The proposed New Idea / project isintended for Analyzing and Metering of untreated waste water from Industries that have high proportion of suspended solids dissolved organic and inorganic IDL - International Digital Library

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[6].Implementation of Electrochemical Sensors

inArsenic-contaminated Areas of West Bengal in

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International e-Journal For Technology And Research-2018 Indiatoward Rapid and Point-of-Use Detection of Arsenicin Drinking Water Unyoung Kim, Jessica VanderGiessen Department of Bioengineering Santa Clara UniversitySanta Clara, CA, USA And Xavier Savarimuthu, Department of Environmental Science Xavier CollegeKolkata, India, IEEE 2014 [7].Rapid, Affordable, and Point-of-Care Water

Monitoring via a Microfluidic DNA Sensor and a Mobile Interface for Global Health UNYOUNG KIM, SARAH GHANBARI, ANUSHA RAVIKUMAR, JOHN SEUBERT, AND SILVIA FIGUEIRA, Bioengineering Department, Santa Clara University, Santa Clara, CA 95053, USA Sep 2013 [8].Design of Smart Sensors for Real-Time Water Quality Monitoring NIEL ANDRE CLOETE, REZA MALEKIAN, (Member, IEEE), AND LAKSHMI NAIR, (Member, IEEE) Department of Electrical, Electronic and Computer Engineering, University of Pretoria, Pretoria 0002, South Africa , july 2016 [9]. Reconfigurable Smart Water Quality MonitoringSystem in IoTEnvironmentChoZinMyint, Lenin Gopal, and Yan Lin Aung, Department of Electrical and Computer EngineeringCurtin University, Sarawak Campus, CDT 250,98009 Miri, Sarawak, Malaysia, 2017 [10]. A Reconfigurable Smart Sensor Interface for IndustrialWSN in IoT Environment Qingping Chi, Hairong Yan, Chuan Zhang, Zhibo Pang, and Li Da Xu, Senior Member, IEEE, 2014 May [11].Watershed Protection Plan Development Guidebook.

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