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Survey- Pollution Monitoring using IoT
ScienceDirect ScienceDirect
Procedia Computer Science 00 (2018) 000–000 Procedia Computer Science 00 (2018) 000–000
Available online at www.sciencedirect.com
www.elsevier.com/locate/procedia www.elsevier.com/locate/procedia
ScienceDirect Procedia Computer Science 155 (2019) 710–715
2nd International Workshop on “Recent advances on Internet of Things: Technology and 2nd International Workshop on “Recent advances on Internet of Things: Technology and application approaches” (IoT-T&A 2019) application approaches” (IoT-T&A 2019) August 19-21, 2019, Halifax, Canada August 19-21, 2019, Halifax, Canada
Survey- Pollution Monitoring using IoT Survey- Pollution Monitoring using IoT
Jhanvi Aroraaa, Utkarsh Pandyaaa, Saloni Shahaa, Nishant Doshiaa* Jhanvi Arora , Utkarsh Pandya , Saloni Shah , Nishant Doshi * Pandit Deendayal Petroleum University, PDPU Road, Raysan, Gandhinagar-382007, Gujarat, India Pandit Deendayal Petroleum University, PDPU Road, Raysan, Gandhinagar-382007, Gujarat, India
a a
Abstract Abstract The progressing era of globalisation and industrialisation has brought upon its aftermath in disguise of its various concomitant The era of globalisation and hasenvironment. brought uponThe its improper aftermathtreatment in disguise its elements various concomitant toxicprogressing elements which have maladjusted theindustrialisation equilibrium of the of of such has resulted toxic elements which have maladjusted of the serve environment. improper treatment of such elements has resulted into the contamination of basic elementsthe of equilibrium ecosystem which the basisThe to sustain human life. This is one of the most crucial into thepertaining contamination of basic elements of coexistence ecosystem which serve the basis to sustain life.step Thistoisformulate one of thethe most crucial issues to survival of harmonious between human and nature. Thehuman foremost solution is issues pertaining to survival of harmonious coexistence between human and The foremost stepThe to formulate the solution of is determining the extent of damage and based upon it taking preventive andnature. eradication measures. evolving technology determining the extent of damage based upon models it takingforpreventive eradication The evolving technology of Internet of Things, provides a scopeand of lot potential the aboveand stated purposes.measures. The following paper throws a light on Internet provides scope of lot potential models for the above purposes. following paper a light ona some of of theThings, surveyed modelsaand strikes a comparison amongst them all tostated explore the areasThe of improvement andthrows move towards some ofreliant the surveyed models and for strikes comparison amongst them all to explore the areas of improvement and move towards a better, and efficient model the asame. better, reliant and efficient model for the same. © 2019 The Authors. Published by Elsevier B.V. © 2019 2019 The The Authors. Authors. Published Published by by Elsevier Elsevier B.V. B.V. © This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review responsibility of of the theConference Conference Program Chairs. Peer-review under under responsibility Program Chairs. Peer-review under responsibility of the Conference Program Chairs. Keywords: Air pollution; Water Pollution; Soil Pollution; Pollution; IoT; Survey Keywords: Air pollution; Water Pollution; Soil Pollution; Pollution; IoT; Survey
1. Introduction 1. Introduction Recently, global warming alone has caused a widespread hysteria among the citizens of the globe about possibly Recently, globalon warming caused a widespread hysteria among of the globe aboutOne possibly harmful effects the veryalone Earthhas they live in. Two solutions are there forthe thecitizens aforementioned problem. is to harmful effectsofonharmful the verywaste Earthand theyother live is in. toTwo solutions are there for the three aforementioned problem. One With is to stop burgeon process contaminants in all areas of the biosphere. stop burgeon struggling of harmfulatwaste and to other is totowards processthecontaminants in tech-savvy all three areas of the With entrepreneurs one end march green energy, people can biosphere. offer a solution entrepreneurs struggling at one end to march towards the green energy, tech-savvy people can offer a solution
* Corresponding author * Corresponding E-mail address:author [email protected] E-mail address: [email protected] 1877-0509 © 2019 The Authors. Published by Elsevier B.V. 1877-0509 © 2019 Thearticle Authors. Published by Elsevier B.V. This is an open access under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) This is an open access article under CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the Conference Program Chairs. Peer-review under responsibility of the Conference Program Chairs.
1877-0509 © 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the Conference Program Chairs. 10.1016/j.procs.2019.08.102
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Jhanvi Arora et al. / Procedia Computer Science 155 (2019) 710–715 Jhanvi Arora et al./ Procedia Computer Science 00 (2018) 000–000
711
through IoT for both the approaches. Internet of Things is a vast arena of devices communicating with each other on the basis of interconnected nodal devices. It is internet for the devices which are embedded with sensors which collect information and send it through a wired/wireless medium where data can be analyzed to take proper actions.
2. Preliminaries The surveyed models include these building blocks given in the diagram:
Fig. 1. Extract of Surveyed Model
The sensor nodes interact with the environment and collect various parameters which are processed via microcontrollers and further transmitted to end devices via various wireless technologies. The data obtained is stored in a database which is readily available to the end users through the set up of an Application Program Interface. 3. Literature Survey Technology is the cure of its own curse. It is an agreeable fact that pollution is an immediate consequence of inculcation of technology and automation in our lives but somehow, like always, the miraculous creativity of human brain finds a ray of light in all dark and paves a way out. The following survey intends to highlight some of such instances which make excellent use of IoT to find a cure to this curse of unchecked technology called 'Pollution'. 3.1. Air Pollution The increasingly degrading quality of air in numerous regions of the world can be an unswerving repercussion of human hassles of increasing globalization and urbanization. The myriad consequences of the same can be regulated by keeping a periodic check on the quality of air and undertaking efforts to improve if it deteriorates beyond a certain extent. However, the foremost step here is the analysis and detection of the harmful gases present in the atmosphere yielding to poor quality of air which is a task that can be easily accomplished by the latest evolved high technology of ‘IoT-Internet of Things’. Following models pose to be some of the good solutions for the aforementioned problem: The model represented by paper [1] and [3], proposed in 2017 describe an overall environmental pollution monitoring system wherein sensor networks have been established to control emission of toxic gases into the atmosphere, alongside also keeping an eye on the surrounding noise level. Model in paper [1] extends its scope to detect intensity of UV rays and also takes in consideration the temperature and humidity of the area where it is deployed in. Extending the scope of [1] and [3], model proposed in [4] progresses towards efficient and portable data extraction and accessibility. Another model [2], proposed a year later, in 2018 describes an efficient deployment system to curb the harmful emissions from individual vehicles by putting restraint and generating an alert if any individual emission goes beyond tolerance value. Another model [5] proposed in same year, extends all models and instantiates a new approach, bringing in the factor of machine learning to predict and forecast the pollution after having monitored it for a certain duration. 3.2. Water Pollution Rise in the value of water has been excruciating lately yet the clean amount of it is getting scarcer by the minute. This vital part of the existence of many life forms has been neglected for many decades over numerous hassles of human beings for unchecked development of mankind. The water bodies are getting depraved with the harmful contaminants. To keep a control on the same, the extensively used technology of Internet of Things offers a good
Jhanvi Arora et al. / Procedia Computer Science 155 (2019) 710–715 Jhanvi Arora et al./ Procedia Computer Science 00 (2018) 000–000
712
3
range of solutions. Some of which are surveyed herewith. The model portrayed in [6] describes an innovative way of reusing the wastewater released as effluents by using IoT to judge its potential and based upon the same it is converted to a renewable energy source. Model in [7] strives to keep a check on the water quality with efficient power consumption mechanism. The model in [8] proposes a solution to monitor the dumping lands by investigating the quality of water and certain other environment parameters to calculate the threat factor for surrounding areas. Model proposed in [9] moves towards the large water bodies monitoring by cumulative measurement of each region. Model presented in [10] regulates the consumption and analyses the consumption behaviour of the user. 3.3. Soil Pollution Soil is the kitchen of mother Earth. No mouth will be able to feed, by the extension of food chain, if not for the healthy soil to reap a fine and abundant harvest. The class of this soil has been degrading overall while its value ever increasing, henceforth arising the need of soil pollution control mechanism. IoT is an excellent way to reduce the aforesaid pollution by monitoring soil environment and alerting the users in order to take necessary actions. Numerous ways have been discovered in order to maintain the soil quality by monitoring its parameters. The surveyed models in brief for the same are: Paper [11] describes a model which monitors the soil nutrient level at fixed intervals and aids the soil with nutrients from a nutrient tank on obtaining a lower value. Model proposed in [12] presents an approach to keep an eye on soil moisture for cropping lands and efficiently updating the user on same. In model described by [13], system is designed to measure the agricultural parameters and smartly deployed to analyse and act upon the readings obtained. 4. Comparison of Surveyed Data 4.1. Air Pollution Table 1. Comparison of Surveyed Data for Models related to Air Pollution S. No.
Parameters/ Models
[1]
[2]
[3]
[4]
[5]
1.
Primary Purpose
To detect the general pollutants in environment using IoT
To keep a check on vehicular cause of air pollution
To analyse and monitor air pollutant and sound pollutants concentration
To detect the CO content in Air and find intensity of Noise pollution in environment
Collect air quality measurement and apply machine learning to predict and forecast pollution
2.
Technology to Transmit Data
Bluetooth Module (HC-06)
Wired Ethernet of Raspberry- Pi
ESP8266 Wi-Fi Module
ESP8266 Wi-Fi Module
ESP8266-12E Wi-Fi modules
1. MQ-135, MQ-2, UV-01, DHT11
1. MQ-135
1. MQ-135 2. Arduino Uno R3
1. MQ-135, MQ-7, MQ-2, DHT11 2. AVR Uno
Buzzer for alert generation, LCD for display, webpage to
MCP 3008 Analog to Digital conversion chip, Web server to display webpages, LED- to indicate threshold
3.
4.
Hardware Requirements: 1. Sensors used 2. Microcontroller board Tools and Technology
2. ARM -7 (LPC2138) Web enabled server and Mobile Data Acquisition Unit to access data, GPS for location access, UART for sensor
2. Raspberry Pi-3
MCP 3008 ADC Chip, charging cable in Vehicle to charge Raspberry Pi-3
1. MQ-2 2. Node-MCU
AI AlgorithmsRandom Forest, Linear Regression, XGBoost and ARIMA
4
Jhanvi Arora et al. / Procedia Computer Science 155 (2019) 710–715 Jhanvi Arora et al./ Procedia Computer Science 00 (2018) 000–000 board communication. 5.
Programming Specifications
6.
Measurement Capabilities
7.
Scope
8.
Research Gaps
MATLAB and C compiler, GNU\Linux Distribution for Raspberry Pi
713
monitor Arduino, Linux OS, DatabaseRaspberry Pi storage, Cloud
Arduino software
MATLAB, Databasegoogle spread sheets
Ammonia, Benzene, Smoke
Ammonia, Benzene, Smoke, Noise
Ammonia, Benzene, Carbon Monoxide, Smoke, Temperature, Humidity, Noise, LPG, Propane, Hydrogen
Pollution monitoring in urban and Industrial areas, Noise check
Toxic effluents of a particular vehicle
Environmental air and noise pollution check.
Efficient visualization of Data for monitoring in Urban, Residential and Industrial areas.
Monitoring and Forecasting Pollution in Urban, Industrial and Residential areas
1. Contribution of UV component to air depletion and deployment feasibility
1. Elimination of interference of other gases from atmosphere
1. Efficient classification of pollutant causes and categories.
1. Deployment feasibility and Mechanism to classify causes and categories
1. Application of Machine Learning to training and prediction of causes.
Ammonia, Benzene, Carbon Monoxide, Smoke, Temperature, Humidity, UV rays
Machine Learning Models, Databasecloud (ThingSpeak)
LPG, Propane, Hydrogen, Ozone, Sulphur Dioxide, Carbon Monoxide
4.2. Water Pollution Table 2. Comparison of Surveyed Data for Models related to Water Pollution S. No.
Parameters/ Models:
[1]
[2]
[3]
[4]
[5]
1.
Primary Purpose
Micro-algal production checking for industrial wastewater control and biomass energy production
Pollution monitoring for dumping areas
Rapid prototyping of WSN system by buoy- type sensors
IoT - Based Architecture for Intermittent water supply
HTTP
Water Quality Management with reduced power consumption X-Bee 802.154, RF module
Zig-Bee, Lora and Wi-Fi TCP/IP Protocols
UART implemented bus system of WSN
Bluetooth, 2G/3G Cellular Networks
1. TMP-BTA Vernier, CON-BTA Vernier, DOBTA Vernier, LS-BTA Vernier, PH- BTA Vernier 2. -
1. SEN0219, DS18B20, SEN0189, LVMaxSonar- EZ1, Atlas scientific pH kit 2. Altera DE1SoC FPGA Board
1. Temperature, pH, Turbidity, electrical conductivity sensors, Different Ions sensors 2. -
1. pH sensor, Turbidity Sensor 2. Node-MCU
Nios II processor, Altera Quartus II Software & Nios-
Wi-Fi, ZigBee, Lora communication protocols, nodes
2.
3.
Technology to Transmit Data
Hardware Requirements: 1. Sensors used 2. Microcontroller board
4.
Tools and Technology
Photo Bio Reactor (PBR) and HTTP protocol to transmit data
1. Continuous level sensor, water flow meter, electric valve 2. -
Buoy type sensors, UART communicate
CloudIoT for online storage, processing
Jhanvi Arora et al. / Procedia Computer Science 155 (2019) 710–715 Jhanvi Arora et al./ Procedia Computer Science 00 (2018) 000–000
714
5.
Programming Specifications
6.
Measurement Capabilities
7.
Scope
8.
Research Gaps
5
II Embedded Design Suite
with solar panel and batteries
with microcontroller
MATLAB, Cloud database (ThingSpeak)
Grafana, Eclipse, Quartus II CAD system, GNU C compiler
Data Aggregation algorithm for locating the polluted region
DatabaseGoogle spread sheets
Big Data algorithms for future state of nodes and notify user of water usage
Biomass moisture, Ash, Protein, Crude fiber, Carbohydrate, Calcium, Phosphorous, Potassium, Total Fat
Temperature, Turbidity, Water Level, pH, CO2
Temperature, pH, Turbidity, electrical conductivity sensors, Different Ions
Temperature, Electrical Conductivity, Illumination
Water Level, Flow Rate
Reservoir Water Quality
Dumping Land Water Waste Contaminants Monitoring
Uniform water parameter data collection of entire reservoirs
Mechanism for continuous usage and notification
Biomass Energy Detection in wastewater
Mechanism to reduce proportion of heavy metals in ash and for continuous production
Monitoring environment for natural water body Mechanism to report node failure.
Water usage in reservoirs at residences
Effective ways to reduce cost and classification of improper usage
4.3 Soil Pollution Table 3. Comparison of Surveyed Data for Models related to Soil Pollution S. No.
Parameters/Models
[11]
[12]
[13]
1.
Primary Purpose
To provide balanced nutrition level to plant by monitoring and modifying pH level of fertilizers
To develop a system to monitor the moisture present in the soil.
Its aim is to make agriculture smart using automation and IoT.
2.
Technology to transmit data
Wi-Fi module
On-chip Wi-Fi
Wi-Fi - 2.4 GHz, Bluetooth 4.1
3.
Hardware Requirement
1. Fibre optic pH sensor, Liquid level sensor
1. FC-28
1.Sensors used 2.Microcontroller Board
2. Raspberry Pi, MCP 3028
1. Temperature sensor LM35, Moisture sensor, Barometric Pressure sensor, humidity sensor
4.
Measurement Capabilities
Macronutrients- Nitrogen, phosphorous and potassium
Moisture content in soil
Moisture, temperature, pressure, humidity
5.
Scope
Overly used agricultural lands, hilly terrains
Agricultural lands red and black soil, arid areas
Agricultural fields where crops are yielded frequently or in large quantities
6.
Research gap
Efficient techniques to reduce requirement of data
Remotely operable soil moisture maintaining mechanism
Effective research to eliminate man
2. CC3200 Launchpad
2. Arduino Pro Mini (Atmega328)
6
Jhanvi Arora et al. / Procedia Computer Science 155 (2019) 710–715 Jhanvi Arora et al./ Procedia Computer Science 00 (2018) 000–000 collection and maximize yield 7.
Tools and Technology
Relay Switch to compare readings, LCD-Display
715
power completely AT&T Cloud Technology and Blynk Application
Automatic system that acts on sensor readings
5. Research Challenges Larger sensors networks are harder to manage in aspect of timely maintenance. Moreover, for concrete apprehension of quantity of such systems, there is a need of customized wireless network. Humidity wears off many sensor nodes which demands for a more robust protection for those sensors. Owing to the promptly expanding horizons of automation, it is now possible to impart to the metallic task-doers, the apprehension of a human brain. Here, all the surveyed models instantiate the same fact, where a machine is trained to percept the pollution at a more precise measure than humans can but the real challenge lies here is, the optimum and efficient knowledge extraction from the machine’s capabilities. Efficient formulation of a system which curbs the source on estimating a higher rate is the challenge here. Realization of appropriate preventive and neutralizing solutions is needed to be gained from machines in future and still remains an area to be explored further. 6. Conclusion and Future Work The above paper presents the efforts and varied implementations attempted in lieu to keep a check on the environmental pollution to improve the quality of ecosystem. There are few advancements possible before standardized implementation of such systems is made deployable. The surveyed models provide a basis for the same. The capabilities of such system could be extended by introduction of various Machine Learning Algorithms as stated in [5]. Paving the way further, these models guide the futuristic standardised model for implementing a more robust and secure model. 7. References: [1] Himadri Nath Saha, Supratim Auddy, Avimita Chatterjee, Subrata Pal, Shivesh Pandey, Rocky Singh, Rakhee Singh, Priyanshu Sharan, Swarnadeep Banerjee, Debmalya Ghosh, Ankita Maity. (2017) “Pollution Control Using Internet of Things (IoT)”. 8th Annual Industrial Automation and Electromechanical Engineering Conference (IEMECON) [2] Akshay Kajale, Prathamesh Inamdar, Vivek Bagad, Ankit Mhaske, Ameya Joshi, Prof. Pooja Dhule. (2018) “Cloud and IoT Enabled Smart Air Pollution Monitoring System”, International Journal of Innovative Research in Science, Engineering and Technology, Vol. 7, Issue 4. [3] Poonam Pal, Ritik Gupta, Sanjana Tiwari, Ashutosh Sharma. (2017) “IoT Based Air Pollution Monitoring System Using Arduino”, International Research Journal of Engineering and Technology (IRJET), Volume: 04 Issue: 10. [4] Lalit Mohan Joshi. (2017) “IoT based Air and Sound Pollution Monitoring System”, International Journal of Computer Applications (0975 – 8887) Volume 178 – No.7. [5] Ayaskanta Mishra. (2018) “Air Pollution Monitoring System based on IoT: Forecasting and Predictive Modelling using Machine Learning”. International Conference on Applied Electromagnetics, Signal Processing and Communication (AESPC). [6] Arys Carrasquilla-Batista, Alfonso Chac´on-Rodr´ıguez, Francinie Murillo-Vega1 Kattia N´ u˜nez-Montero, Olman G´omezEspinoza, Maritza Guerrero-Barrantes. (2017) “Characterization of biomass pellets from Chlorella vulgaris microalgal production using industrial wastewater”. International Conference in Energy and Sustainability in Small Developing Economies (ES2DE). [7] Cho Zin Myint, Lenin Gopal, and Yan Lin Aung. (2017) “Reconfigurable Smart Water Quality Monitoring System in IoT Environment”, IEEE/ACIS 16th International Conference on Computer and Information Science (ICIS) [8] Maneesha V Ramesh, Nibi K V, Anupama Kurup, Renjith Mohan, Aiswarya A, Arsha A, Sarang P R. (2017) “Water Quality Monitoring and Waste Management using IoT”, IEEE Global Humanitarian Technology Conference (GHTC) [9] Tomoaki Kageyama, Masashi Miura, Akihiro Maeda, Akihiro Mori and Sang-Seok Lee, “A Wireless Sensor Network Platform for Water Quality Monitoring”, IEEE Sensors [10] Sawsan Alshattnawi. (2017) “Smart Water Distribution Management System Architecture Based on Internet of Things and Cloud Computing”, International Conference on New Trends in Computing Sciences. [11] S. Brindha, J. Deepa, P. Charumathi, M. Aravind Kumar, P. Navin Karthi. (2017) “Involuntary Nutrients Dispense System for Soil Deficiency using IOT”. International Journal of ChemTech Research. [12] P. Divya Vani and K. Raghavendra Rao. (2016) “Measurement and Monitoring of Soil Moisture using Cloud IoT and Android System” Indian Journal of Science and Technology August. [13] Gokul Patil, Prashant S. Gawande and Rohit Vilasrao Bag. (2017) “Smart Agriculture System based on IoT and its Social Impact”. International Journal of Computer Applications.
Procedia Computer Science 00 (2018) 000–000 Procedia Computer Science 00 (2018) 000–000
Available online at www.sciencedirect.com
www.elsevier.com/locate/procedia www.elsevier.com/locate/procedia
ScienceDirect Procedia Computer Science 155 (2019) 710–715
2nd International Workshop on “Recent advances on Internet of Things: Technology and 2nd International Workshop on “Recent advances on Internet of Things: Technology and application approaches” (IoT-T&A 2019) application approaches” (IoT-T&A 2019) August 19-21, 2019, Halifax, Canada August 19-21, 2019, Halifax, Canada
Survey- Pollution Monitoring using IoT Survey- Pollution Monitoring using IoT
Jhanvi Aroraaa, Utkarsh Pandyaaa, Saloni Shahaa, Nishant Doshiaa* Jhanvi Arora , Utkarsh Pandya , Saloni Shah , Nishant Doshi * Pandit Deendayal Petroleum University, PDPU Road, Raysan, Gandhinagar-382007, Gujarat, India Pandit Deendayal Petroleum University, PDPU Road, Raysan, Gandhinagar-382007, Gujarat, India
a a
Abstract Abstract The progressing era of globalisation and industrialisation has brought upon its aftermath in disguise of its various concomitant The era of globalisation and hasenvironment. brought uponThe its improper aftermathtreatment in disguise its elements various concomitant toxicprogressing elements which have maladjusted theindustrialisation equilibrium of the of of such has resulted toxic elements which have maladjusted of the serve environment. improper treatment of such elements has resulted into the contamination of basic elementsthe of equilibrium ecosystem which the basisThe to sustain human life. This is one of the most crucial into thepertaining contamination of basic elements of coexistence ecosystem which serve the basis to sustain life.step Thistoisformulate one of thethe most crucial issues to survival of harmonious between human and nature. Thehuman foremost solution is issues pertaining to survival of harmonious coexistence between human and The foremost stepThe to formulate the solution of is determining the extent of damage and based upon it taking preventive andnature. eradication measures. evolving technology determining the extent of damage based upon models it takingforpreventive eradication The evolving technology of Internet of Things, provides a scopeand of lot potential the aboveand stated purposes.measures. The following paper throws a light on Internet provides scope of lot potential models for the above purposes. following paper a light ona some of of theThings, surveyed modelsaand strikes a comparison amongst them all tostated explore the areasThe of improvement andthrows move towards some ofreliant the surveyed models and for strikes comparison amongst them all to explore the areas of improvement and move towards a better, and efficient model the asame. better, reliant and efficient model for the same. © 2019 The Authors. Published by Elsevier B.V. © 2019 2019 The The Authors. Authors. Published Published by by Elsevier Elsevier B.V. B.V. © This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review responsibility of of the theConference Conference Program Chairs. Peer-review under under responsibility Program Chairs. Peer-review under responsibility of the Conference Program Chairs. Keywords: Air pollution; Water Pollution; Soil Pollution; Pollution; IoT; Survey Keywords: Air pollution; Water Pollution; Soil Pollution; Pollution; IoT; Survey
1. Introduction 1. Introduction Recently, global warming alone has caused a widespread hysteria among the citizens of the globe about possibly Recently, globalon warming caused a widespread hysteria among of the globe aboutOne possibly harmful effects the veryalone Earthhas they live in. Two solutions are there forthe thecitizens aforementioned problem. is to harmful effectsofonharmful the verywaste Earthand theyother live is in. toTwo solutions are there for the three aforementioned problem. One With is to stop burgeon process contaminants in all areas of the biosphere. stop burgeon struggling of harmfulatwaste and to other is totowards processthecontaminants in tech-savvy all three areas of the With entrepreneurs one end march green energy, people can biosphere. offer a solution entrepreneurs struggling at one end to march towards the green energy, tech-savvy people can offer a solution
* Corresponding author * Corresponding E-mail address:author [email protected] E-mail address: [email protected] 1877-0509 © 2019 The Authors. Published by Elsevier B.V. 1877-0509 © 2019 Thearticle Authors. Published by Elsevier B.V. This is an open access under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) This is an open access article under CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the Conference Program Chairs. Peer-review under responsibility of the Conference Program Chairs.
1877-0509 © 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the Conference Program Chairs. 10.1016/j.procs.2019.08.102
2
Jhanvi Arora et al. / Procedia Computer Science 155 (2019) 710–715 Jhanvi Arora et al./ Procedia Computer Science 00 (2018) 000–000
711
through IoT for both the approaches. Internet of Things is a vast arena of devices communicating with each other on the basis of interconnected nodal devices. It is internet for the devices which are embedded with sensors which collect information and send it through a wired/wireless medium where data can be analyzed to take proper actions.
2. Preliminaries The surveyed models include these building blocks given in the diagram:
Fig. 1. Extract of Surveyed Model
The sensor nodes interact with the environment and collect various parameters which are processed via microcontrollers and further transmitted to end devices via various wireless technologies. The data obtained is stored in a database which is readily available to the end users through the set up of an Application Program Interface. 3. Literature Survey Technology is the cure of its own curse. It is an agreeable fact that pollution is an immediate consequence of inculcation of technology and automation in our lives but somehow, like always, the miraculous creativity of human brain finds a ray of light in all dark and paves a way out. The following survey intends to highlight some of such instances which make excellent use of IoT to find a cure to this curse of unchecked technology called 'Pollution'. 3.1. Air Pollution The increasingly degrading quality of air in numerous regions of the world can be an unswerving repercussion of human hassles of increasing globalization and urbanization. The myriad consequences of the same can be regulated by keeping a periodic check on the quality of air and undertaking efforts to improve if it deteriorates beyond a certain extent. However, the foremost step here is the analysis and detection of the harmful gases present in the atmosphere yielding to poor quality of air which is a task that can be easily accomplished by the latest evolved high technology of ‘IoT-Internet of Things’. Following models pose to be some of the good solutions for the aforementioned problem: The model represented by paper [1] and [3], proposed in 2017 describe an overall environmental pollution monitoring system wherein sensor networks have been established to control emission of toxic gases into the atmosphere, alongside also keeping an eye on the surrounding noise level. Model in paper [1] extends its scope to detect intensity of UV rays and also takes in consideration the temperature and humidity of the area where it is deployed in. Extending the scope of [1] and [3], model proposed in [4] progresses towards efficient and portable data extraction and accessibility. Another model [2], proposed a year later, in 2018 describes an efficient deployment system to curb the harmful emissions from individual vehicles by putting restraint and generating an alert if any individual emission goes beyond tolerance value. Another model [5] proposed in same year, extends all models and instantiates a new approach, bringing in the factor of machine learning to predict and forecast the pollution after having monitored it for a certain duration. 3.2. Water Pollution Rise in the value of water has been excruciating lately yet the clean amount of it is getting scarcer by the minute. This vital part of the existence of many life forms has been neglected for many decades over numerous hassles of human beings for unchecked development of mankind. The water bodies are getting depraved with the harmful contaminants. To keep a control on the same, the extensively used technology of Internet of Things offers a good
Jhanvi Arora et al. / Procedia Computer Science 155 (2019) 710–715 Jhanvi Arora et al./ Procedia Computer Science 00 (2018) 000–000
712
3
range of solutions. Some of which are surveyed herewith. The model portrayed in [6] describes an innovative way of reusing the wastewater released as effluents by using IoT to judge its potential and based upon the same it is converted to a renewable energy source. Model in [7] strives to keep a check on the water quality with efficient power consumption mechanism. The model in [8] proposes a solution to monitor the dumping lands by investigating the quality of water and certain other environment parameters to calculate the threat factor for surrounding areas. Model proposed in [9] moves towards the large water bodies monitoring by cumulative measurement of each region. Model presented in [10] regulates the consumption and analyses the consumption behaviour of the user. 3.3. Soil Pollution Soil is the kitchen of mother Earth. No mouth will be able to feed, by the extension of food chain, if not for the healthy soil to reap a fine and abundant harvest. The class of this soil has been degrading overall while its value ever increasing, henceforth arising the need of soil pollution control mechanism. IoT is an excellent way to reduce the aforesaid pollution by monitoring soil environment and alerting the users in order to take necessary actions. Numerous ways have been discovered in order to maintain the soil quality by monitoring its parameters. The surveyed models in brief for the same are: Paper [11] describes a model which monitors the soil nutrient level at fixed intervals and aids the soil with nutrients from a nutrient tank on obtaining a lower value. Model proposed in [12] presents an approach to keep an eye on soil moisture for cropping lands and efficiently updating the user on same. In model described by [13], system is designed to measure the agricultural parameters and smartly deployed to analyse and act upon the readings obtained. 4. Comparison of Surveyed Data 4.1. Air Pollution Table 1. Comparison of Surveyed Data for Models related to Air Pollution S. No.
Parameters/ Models
[1]
[2]
[3]
[4]
[5]
1.
Primary Purpose
To detect the general pollutants in environment using IoT
To keep a check on vehicular cause of air pollution
To analyse and monitor air pollutant and sound pollutants concentration
To detect the CO content in Air and find intensity of Noise pollution in environment
Collect air quality measurement and apply machine learning to predict and forecast pollution
2.
Technology to Transmit Data
Bluetooth Module (HC-06)
Wired Ethernet of Raspberry- Pi
ESP8266 Wi-Fi Module
ESP8266 Wi-Fi Module
ESP8266-12E Wi-Fi modules
1. MQ-135, MQ-2, UV-01, DHT11
1. MQ-135
1. MQ-135 2. Arduino Uno R3
1. MQ-135, MQ-7, MQ-2, DHT11 2. AVR Uno
Buzzer for alert generation, LCD for display, webpage to
MCP 3008 Analog to Digital conversion chip, Web server to display webpages, LED- to indicate threshold
3.
4.
Hardware Requirements: 1. Sensors used 2. Microcontroller board Tools and Technology
2. ARM -7 (LPC2138) Web enabled server and Mobile Data Acquisition Unit to access data, GPS for location access, UART for sensor
2. Raspberry Pi-3
MCP 3008 ADC Chip, charging cable in Vehicle to charge Raspberry Pi-3
1. MQ-2 2. Node-MCU
AI AlgorithmsRandom Forest, Linear Regression, XGBoost and ARIMA
4
Jhanvi Arora et al. / Procedia Computer Science 155 (2019) 710–715 Jhanvi Arora et al./ Procedia Computer Science 00 (2018) 000–000 board communication. 5.
Programming Specifications
6.
Measurement Capabilities
7.
Scope
8.
Research Gaps
MATLAB and C compiler, GNU\Linux Distribution for Raspberry Pi
713
monitor Arduino, Linux OS, DatabaseRaspberry Pi storage, Cloud
Arduino software
MATLAB, Databasegoogle spread sheets
Ammonia, Benzene, Smoke
Ammonia, Benzene, Smoke, Noise
Ammonia, Benzene, Carbon Monoxide, Smoke, Temperature, Humidity, Noise, LPG, Propane, Hydrogen
Pollution monitoring in urban and Industrial areas, Noise check
Toxic effluents of a particular vehicle
Environmental air and noise pollution check.
Efficient visualization of Data for monitoring in Urban, Residential and Industrial areas.
Monitoring and Forecasting Pollution in Urban, Industrial and Residential areas
1. Contribution of UV component to air depletion and deployment feasibility
1. Elimination of interference of other gases from atmosphere
1. Efficient classification of pollutant causes and categories.
1. Deployment feasibility and Mechanism to classify causes and categories
1. Application of Machine Learning to training and prediction of causes.
Ammonia, Benzene, Carbon Monoxide, Smoke, Temperature, Humidity, UV rays
Machine Learning Models, Databasecloud (ThingSpeak)
LPG, Propane, Hydrogen, Ozone, Sulphur Dioxide, Carbon Monoxide
4.2. Water Pollution Table 2. Comparison of Surveyed Data for Models related to Water Pollution S. No.
Parameters/ Models:
[1]
[2]
[3]
[4]
[5]
1.
Primary Purpose
Micro-algal production checking for industrial wastewater control and biomass energy production
Pollution monitoring for dumping areas
Rapid prototyping of WSN system by buoy- type sensors
IoT - Based Architecture for Intermittent water supply
HTTP
Water Quality Management with reduced power consumption X-Bee 802.154, RF module
Zig-Bee, Lora and Wi-Fi TCP/IP Protocols
UART implemented bus system of WSN
Bluetooth, 2G/3G Cellular Networks
1. TMP-BTA Vernier, CON-BTA Vernier, DOBTA Vernier, LS-BTA Vernier, PH- BTA Vernier 2. -
1. SEN0219, DS18B20, SEN0189, LVMaxSonar- EZ1, Atlas scientific pH kit 2. Altera DE1SoC FPGA Board
1. Temperature, pH, Turbidity, electrical conductivity sensors, Different Ions sensors 2. -
1. pH sensor, Turbidity Sensor 2. Node-MCU
Nios II processor, Altera Quartus II Software & Nios-
Wi-Fi, ZigBee, Lora communication protocols, nodes
2.
3.
Technology to Transmit Data
Hardware Requirements: 1. Sensors used 2. Microcontroller board
4.
Tools and Technology
Photo Bio Reactor (PBR) and HTTP protocol to transmit data
1. Continuous level sensor, water flow meter, electric valve 2. -
Buoy type sensors, UART communicate
CloudIoT for online storage, processing
Jhanvi Arora et al. / Procedia Computer Science 155 (2019) 710–715 Jhanvi Arora et al./ Procedia Computer Science 00 (2018) 000–000
714
5.
Programming Specifications
6.
Measurement Capabilities
7.
Scope
8.
Research Gaps
5
II Embedded Design Suite
with solar panel and batteries
with microcontroller
MATLAB, Cloud database (ThingSpeak)
Grafana, Eclipse, Quartus II CAD system, GNU C compiler
Data Aggregation algorithm for locating the polluted region
DatabaseGoogle spread sheets
Big Data algorithms for future state of nodes and notify user of water usage
Biomass moisture, Ash, Protein, Crude fiber, Carbohydrate, Calcium, Phosphorous, Potassium, Total Fat
Temperature, Turbidity, Water Level, pH, CO2
Temperature, pH, Turbidity, electrical conductivity sensors, Different Ions
Temperature, Electrical Conductivity, Illumination
Water Level, Flow Rate
Reservoir Water Quality
Dumping Land Water Waste Contaminants Monitoring
Uniform water parameter data collection of entire reservoirs
Mechanism for continuous usage and notification
Biomass Energy Detection in wastewater
Mechanism to reduce proportion of heavy metals in ash and for continuous production
Monitoring environment for natural water body Mechanism to report node failure.
Water usage in reservoirs at residences
Effective ways to reduce cost and classification of improper usage
4.3 Soil Pollution Table 3. Comparison of Surveyed Data for Models related to Soil Pollution S. No.
Parameters/Models
[11]
[12]
[13]
1.
Primary Purpose
To provide balanced nutrition level to plant by monitoring and modifying pH level of fertilizers
To develop a system to monitor the moisture present in the soil.
Its aim is to make agriculture smart using automation and IoT.
2.
Technology to transmit data
Wi-Fi module
On-chip Wi-Fi
Wi-Fi - 2.4 GHz, Bluetooth 4.1
3.
Hardware Requirement
1. Fibre optic pH sensor, Liquid level sensor
1. FC-28
1.Sensors used 2.Microcontroller Board
2. Raspberry Pi, MCP 3028
1. Temperature sensor LM35, Moisture sensor, Barometric Pressure sensor, humidity sensor
4.
Measurement Capabilities
Macronutrients- Nitrogen, phosphorous and potassium
Moisture content in soil
Moisture, temperature, pressure, humidity
5.
Scope
Overly used agricultural lands, hilly terrains
Agricultural lands red and black soil, arid areas
Agricultural fields where crops are yielded frequently or in large quantities
6.
Research gap
Efficient techniques to reduce requirement of data
Remotely operable soil moisture maintaining mechanism
Effective research to eliminate man
2. CC3200 Launchpad
2. Arduino Pro Mini (Atmega328)
6
Jhanvi Arora et al. / Procedia Computer Science 155 (2019) 710–715 Jhanvi Arora et al./ Procedia Computer Science 00 (2018) 000–000 collection and maximize yield 7.
Tools and Technology
Relay Switch to compare readings, LCD-Display
715
power completely AT&T Cloud Technology and Blynk Application
Automatic system that acts on sensor readings
5. Research Challenges Larger sensors networks are harder to manage in aspect of timely maintenance. Moreover, for concrete apprehension of quantity of such systems, there is a need of customized wireless network. Humidity wears off many sensor nodes which demands for a more robust protection for those sensors. Owing to the promptly expanding horizons of automation, it is now possible to impart to the metallic task-doers, the apprehension of a human brain. Here, all the surveyed models instantiate the same fact, where a machine is trained to percept the pollution at a more precise measure than humans can but the real challenge lies here is, the optimum and efficient knowledge extraction from the machine’s capabilities. Efficient formulation of a system which curbs the source on estimating a higher rate is the challenge here. Realization of appropriate preventive and neutralizing solutions is needed to be gained from machines in future and still remains an area to be explored further. 6. Conclusion and Future Work The above paper presents the efforts and varied implementations attempted in lieu to keep a check on the environmental pollution to improve the quality of ecosystem. There are few advancements possible before standardized implementation of such systems is made deployable. The surveyed models provide a basis for the same. The capabilities of such system could be extended by introduction of various Machine Learning Algorithms as stated in [5]. Paving the way further, these models guide the futuristic standardised model for implementing a more robust and secure model. 7. References: [1] Himadri Nath Saha, Supratim Auddy, Avimita Chatterjee, Subrata Pal, Shivesh Pandey, Rocky Singh, Rakhee Singh, Priyanshu Sharan, Swarnadeep Banerjee, Debmalya Ghosh, Ankita Maity. (2017) “Pollution Control Using Internet of Things (IoT)”. 8th Annual Industrial Automation and Electromechanical Engineering Conference (IEMECON) [2] Akshay Kajale, Prathamesh Inamdar, Vivek Bagad, Ankit Mhaske, Ameya Joshi, Prof. Pooja Dhule. (2018) “Cloud and IoT Enabled Smart Air Pollution Monitoring System”, International Journal of Innovative Research in Science, Engineering and Technology, Vol. 7, Issue 4. [3] Poonam Pal, Ritik Gupta, Sanjana Tiwari, Ashutosh Sharma. (2017) “IoT Based Air Pollution Monitoring System Using Arduino”, International Research Journal of Engineering and Technology (IRJET), Volume: 04 Issue: 10. [4] Lalit Mohan Joshi. (2017) “IoT based Air and Sound Pollution Monitoring System”, International Journal of Computer Applications (0975 – 8887) Volume 178 – No.7. [5] Ayaskanta Mishra. (2018) “Air Pollution Monitoring System based on IoT: Forecasting and Predictive Modelling using Machine Learning”. International Conference on Applied Electromagnetics, Signal Processing and Communication (AESPC). [6] Arys Carrasquilla-Batista, Alfonso Chac´on-Rodr´ıguez, Francinie Murillo-Vega1 Kattia N´ u˜nez-Montero, Olman G´omezEspinoza, Maritza Guerrero-Barrantes. (2017) “Characterization of biomass pellets from Chlorella vulgaris microalgal production using industrial wastewater”. International Conference in Energy and Sustainability in Small Developing Economies (ES2DE). [7] Cho Zin Myint, Lenin Gopal, and Yan Lin Aung. (2017) “Reconfigurable Smart Water Quality Monitoring System in IoT Environment”, IEEE/ACIS 16th International Conference on Computer and Information Science (ICIS) [8] Maneesha V Ramesh, Nibi K V, Anupama Kurup, Renjith Mohan, Aiswarya A, Arsha A, Sarang P R. (2017) “Water Quality Monitoring and Waste Management using IoT”, IEEE Global Humanitarian Technology Conference (GHTC) [9] Tomoaki Kageyama, Masashi Miura, Akihiro Maeda, Akihiro Mori and Sang-Seok Lee, “A Wireless Sensor Network Platform for Water Quality Monitoring”, IEEE Sensors [10] Sawsan Alshattnawi. (2017) “Smart Water Distribution Management System Architecture Based on Internet of Things and Cloud Computing”, International Conference on New Trends in Computing Sciences. [11] S. Brindha, J. Deepa, P. Charumathi, M. Aravind Kumar, P. Navin Karthi. (2017) “Involuntary Nutrients Dispense System for Soil Deficiency using IOT”. International Journal of ChemTech Research. [12] P. Divya Vani and K. Raghavendra Rao. (2016) “Measurement and Monitoring of Soil Moisture using Cloud IoT and Android System” Indian Journal of Science and Technology August. [13] Gokul Patil, Prashant S. Gawande and Rohit Vilasrao Bag. (2017) “Smart Agriculture System based on IoT and its Social Impact”. International Journal of Computer Applications.