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9 III March 2021
https://doi.org/10.22214/ijraset.2021.33294
International Journal for Research in Applied Science & Engineering Technology (IJRASET)
ISSN: 2321-9653; IC Value: 45.98; SJ Impact Factor: 7.429
Volume 9 Issue III Mar 2021- Available at www.ijraset.com
©IJRASET: All Rights are Reserved
573
A Detailed Study on Smart Waste Monitoring
Systems, an Application of Internet of Things
Gayatri Bangar1, Kanupriya Ishu2
1, 2Student, Department of Information Technology, TEC, University of Mumbai, Mumbai, India
Abstract: Solid waste management is currently a crucial problem in urban areas. The overflowing dustbins create an unsanitary
state which can cause various health hazards including irritation in the nose, throat and lungs. To tackle these circumstances,
effective management of waste is necessary. The Internet of Things (IoT) has influenced our world significantly. There has been
a considerable amount of research in the field of Waste Management using IoT technology. This paper reviews various IoT-
based approaches presented by different researchers for solving this problem, and it provides a comparative study of the
available solutions.
Keywords: Smart Waste Management, IoT, Raspberry Pi, Arduino, Ultrasonic sensor, IR sensor, Load sensor, RFID sensor
I. INTRODUCTION
The world population has been increasing by the day and as does the generation of waste which makes the handling of waste more
tedious. The average amount of waste generated, worldwide, per day is 0.74 kgs per person, but ranges widely, from 0.11 to 4.54
kgs [1]. India alone generates between 0.2 and 0.6 kgs of garbage per person per day [2]. The waste generation per capita is so high
that irregular disposal and collection of garbage can result in overflowing dustbins, indirectly leading to unhygienic surroundings
that may result in the spread of diseases. Therefore, waste management has become a vital issue at hand.
Waste Management can be defined as the management of waste from its inception to its disposal. The waste management process is
not economical in terms of money as well as human labour. The routes provided for garbage collection may not be optimized and
can lead to wastage of resources like fuel, human labour, and time. To make the waste management process more economical, IoT
technology can be employed which will help automate the process with minimal human intervention. The smart dustbins can be
built at a very cost-effective rate since the actuators and sensors are not very costly. Along with this, many functionalities can be
provided like the shortest route planning, data monitoring, etc. A smart system will reduce human efforts considerably, consumption
of fuel, and most importantly it will help keep surroundings clean. In this paper, we have discussed the present IoT systems in
section II in which section II[A] consists of all the smart waste management systems that use Arduino as a microcontroller, section
II[B] consists of all the smart waste management systems that use Raspberry-pi as a microcontroller. In section III we have
discussed the merits and demerits of the systems discussed in the previous section. Finally, we conclude our study in section IV and
talk about the future scope in section V.
II. IOT-BASED WASTE MONITORING SYSTEMS
A. Smart Waste Monitoring systems with Arduino Microcontroller
Muyunda and Ibrahim [3] proposed a smart garbage monitoring system based on Arduino that monitors the sensor data and provides
route planning. Two types of sensors have been used, namely ultrasonic sensor and tilt sensor. The ultrasonic sensor detects the
garbage level in the bin and the tilt sensor detects whether the bin is in an upright position or not. The data from these sensors are
collected by the microcontroller, Arduino Nano. This data is then uploaded to the MySQL database using the Wi-Fi module, ESP-
8266. The system is powered using batteries, and to provide power efficiently to every component step-up and step-down converters
are used. To make the system power-efficient and enhance battery life, real-time data monitoring is not carried out. Instead, the
sensors directly communicate to the server as a single-hop network with flat architecture was selected for the sensor network, the
sensors store the data if there is an issue with uploading data in the database. Each sensor node has a unique ID with the help of
which each bin is identified. The data collected by these sensor nodes is presented on a website where bin color changes according
to the fill level of the dustbin. The bin icon is green, yellow, and red if the level is below 30%, between 30-70% and above 70%
respectively. This is done to show the priority of dustbins, so the route planning can be planned accordingly. The route planning
algorithm considers the location of the bin, the color of the bin and the initial location of the garbage collecting vehicle and provides
the optimized route.
International Journal for Research in Applied Science & Engineering Technology (IJRASET)
ISSN: 2321-9653; IC Value: 45.98; SJ Impact Factor: 7.429
Volume 9 Issue III Mar 2021- Available at www.ijraset.com
©IJRASET: All Rights are Reserved
574
Mirchandani et. al [4] proposed a smart waste management system that allows real-time garbage monitoring and also provides an
optimized path for garbage collection. The proposed system is categorized into three units namely, Data Generation Unit, Data
Processing Unit, and Application Unit. In the Data Generation Unit, the data from the ultrasonic sensor that detects the level of
garbage in the bin, the data from the toxicity sensor that detects the gases present in the bin, and information of RFID tags is
collected by the Arduino Uno and sent to the server. In the Data Processing Unit, the data received from the microcontroller is given
to an algorithm that decides which bins need to be collected and updates the list of services accordingly. Then from the list, the total
weight of waste is calculated by the algorithm and the number of trucks and type of trucks (high capacity or low capacity) is
selected. A cluster-based algorithm is used to select dustbins for collection, which considers neighboring dustbins as clusters. A top-
k query-based algorithm is used to select the clusters for garbage collection, based on the data parameters of the trucks. Then,
according to the cluster, suitable capacity trucks are selected. Using Dijkstra's algorithm, the shortest path from the current location
of the truck is determined. Two applications are designed, one for users to maximize their engagement by rewarding points that can
be redeemed later, and another for truck drivers to locate the clusters through the provided route for a particular truck. This system
provides an efficient waste collection plan.
Suryawanshi et. al [5] have developed a smart garbage clearance alert system that alerts the municipal web server after the fill level
in the trash bin crosses the threshold. The ultrasonic sensor has been used to detect the fill level, if the level crosses the threshold an
alert message is sent to the concerned authority, the message is sent using the GSM module. Arduino Uno is the microcontroller
used as an interface between the sensors and server. The microcontroller reads the data from the sensor and sends it to the web
server, this allows real-time monitoring of the waste. After sending an alert message the authority sends a garbage collecting vehicle
to collect the garbage. This process is iterated until the garbage gets collected. The driver, after collecting the garbage, confirms the
collection process with the help of an RFID tag which updates the status of the collection. Along with the webserver, an application
has also been developed that sends notifications using a Wi-Fi module.
A Patel and N Patel [6] have developed an IoT-based management system for garbage that tracks the amount of garbage in
containers and send the data via SMS to approved staff. They have used NodeMCU, ultrasonic sensor, geolocation API and IFTTT
service for their project. NodeMCU gives instruction to the ultrasonic sensor which calculates time. Then distance is calculated
using time. If the distance is more than the threshold value (70%), then the latitude and longitude of the location will be calculated
with help of geolocation API via the IFTTT service. After this IFTTT will generate a message which will include the level of waste
and location of the bin and this will be sent to the desired worker.
Sinha et. al. [7] have designed a Garbage Monitoring System using IoT. They have used Arduino Mega, ESP8266, ultrasonic sensor,
LCD and Blynk app. They have assigned a unique ID to every bin. Every dustbin has an ultrasonic sensor. The ultrasonic sensor is
used to measure the fill level of the garbage. The ultrasonic sensor is interfaced with Arduino Mega. The Arduino Mega is a
microcontroller board based on the ATmega2560. This system will be connected to the internet through the ESP8266 Serial Wi-Fi
wireless transceiver module. It is a wireless network microcontroller module. The level of dustbins can be monitored on the Blynk
app which is connected to the entire system. LCD will also display the ID and level of dustbins along with the location from time to
time.
B. Smart Waste Monitoring Systems with Raspberry Pi Microcontroller
Mahajan et. al. [8] proposed an IoT-based system for waste management that detects the fill level and monitors the fill level of
specific garbage bins. The proposed system has a master-slave configuration to avoid connectivity issues. The master bins are
provided with Raspberry-pi and the slave bins are provided with IoT modules. Each master and slave bin is given a unique id and
the placement of these bins depends upon the corresponding ids.
The proposed system makes use of an ultrasonic sensor, load cell, humidity sensor i.e. DHT11 and Raspberry-pi. An ultrasonic
sensor has been used to calculate the garbage level in the bin and when the level exceeds the threshold an alert is generated. The
load cell has been used to detect the weight of the garbage bin. The ultrasonic sensor and load cell, when used together provide
greater accuracy in the generation of an alert.
A humidity sensor has been used to detect dry and wet waste. The data received from the sensors attached to master and slave bins
is then processed by the microcontroller, Raspberry-pi. Then the Raspberry-pi applies a noise removal algorithm and, using the Wi-
Fi module, ESP8266, sends the data to the server. The data analysis is done using the tools like Storm or Hadoop and an accurate
report is generated. Along with this, an optimized route is also provided using Google maps which is advantageous in saving fuel
and indirectly reduces cost.
International Journal for Research in Applied Science & Engineering Technology (IJRASET)
ISSN: 2321-9653; IC Value: 45.98; SJ Impact Factor: 7.429
Volume 9 Issue III Mar 2021- Available at www.ijraset.com
©IJRASET: All Rights are Reserved
575
Singh et. al. [9] proposed an IoT-based waste collection system intending to provide optimized waste collection routes. The
proposed system uses 4 infrared sensors attached to the top of the bin; Raspberry-pi which acts as an interface between bin and
server which is a Django-based Python web application. The sensors read the level of garbage in the bin and send the data to the
Raspberry pi which sends this data to the web app using the GSM module. In this system, Infrared sensors are used instead of
ultrasonic sensors because of their faster response time. The web framework processes all the updates from various bins and places
their location on the map, and then provides an optimized route and schedules collection plan. One of the striking advantages of this
system is that it works well with a dustbin without a lid or a hinged dustbin etc, making it most efficient to use in Indian cities.
Pathak et. al. [10] proposed a garbage level monitoring system using Raspberry Pi which monitors the real-time fill level
information of dustbins. The proposed system uses ultrasonic sensors to measure distance, Raspberry Pi board and ESP 8266 Wi-Fi
Module. When the entire system is enabled and Raspberry Pi is supplied with power, the program runs and triggers the ultrasonic
sensor. The ultrasonic sensor measures the fill distance using a reflection mechanism. The outcome is given to the server as ESP
8266 connects to the internet. This gives the admin a detailed analysis of the garbage level of all the trash bins on the server
dashboard. They can view the status of all the dustbins from one place and take necessary actions. This system used Django and
Python-based dashboard for the purpose of monitoring garbage bins. The dashboard makes use of Google charts for visualization
and is connected to an SQLite database where all the data is stored. This system helps to simplify the process and reduce manpower
wastage.
Patra et. al. [11] proposed an IoT-based garbage management system for the smart city using Raspberry Pi. The proposed system
uses three kinds of sensors which are an ultrasonic sensor, load sensor and gas sensors. On top of the waste bin, the ultrasonic sensor
is attached which measures the fill level and four load sensors are also placed next to it. The signal from the load sensor is converted
into a digital signal from an analog signal using an analog to digital converter. This signal is sent to the node sensors which send the
data to the communication protocol. The ZigBee protocol receives the data from the communication protocol. The ZigBee prevents
simultaneous messages. The gas sensors are used to detect the odor of the dustbins. The data of the dustbins is stored in the MySQL
database which is installed on Raspberry Pi. The board has an ethernet interface which functions as a basic data web server. This
system allows the user to monitor the bins from a web browser and the garbage collector can collect the garbage on time.
Jenisha et. al. [12] proposed a garbage management system using Raspberry Pi, three types of sensors and GPS. The sensors used in
the proposed system are an ultrasonic sensor, IR sensor and gas sensor. The distance of the garbage in the bin is measured using an
ultrasonic sensor. IR sensor is used to count the number of items thrown into the bin. Gas sensors are used to detect the smell. When
any gas comes in contact with the gas sensor, the sensing element adsorbs the ionized components of the gas. This generates an
electric potential in the sensing element which is sent in the form of current to the output pin. The GPS is used to feed directions of
the garbage bins. This system uses Raspberry Pi 3 which is connected to other devices and installed on the computer. All the sensors
send value to the Raspberry Pi and then it decides whether mail is to be sent to Municipal Corporation or not. This system reduces
the need for human intervention in the process of garbage disposal.
III. DISCUSSION
Various IoT-based smart waste management systems were discussed in this paper. Mainly devices having Arduino and Raspberry-pi
as microcontrollers were discussed. Table 1 and Table 2 provide the merits and demerits of systems using Arduino and Raspberry-pi
as their microcontroller respectively. Using Raspberry-pi microcontroller can help provide more functionality to the smart system,
data mining and machine learning techniques can be implemented to make systems more efficient.
TABLE.1 Merits and Demerits Of Arduino Systems
Papers Merits Demerits
Muyunda and Ibrahim [3] ● The exact location of the bin can be found as Route
planning is provided
● Power efficiency is high as the Buck and Boost
converter is used
● Sensor nodes can also store the records if the database
connection is lost and after re-establishing the database
connection, the stored data is uploaded
● No feature is implemented to collect the
garbage from bins that are below the
specified level
● Real-time monitoring of garbage bins is
not carried out
International Journal for Research in Applied Science & Engineering Technology (IJRASET)
ISSN: 2321-9653; IC Value: 45.98; SJ Impact Factor: 7.429
Volume 9 Issue III Mar 2021- Available at www.ijraset.com
©IJRASET: All Rights are Reserved
576
Mirchandani et. al [4] ● Real-time monitoring of garbage dins is done
● The collection process is highly optimized
● Power consumption of the system is high
due to many sensors used
Suryawanshi et. al [5] ● RFID tags can distinguish the type of garbage filled
and it also sends the status of collection of garbage
completed to the server.
● The system keeps on sending alert messages via the
GSM module until the garbage is collected.
● The records are not stored in a database.
● The methodology is not explained quite
well.
A Patel and N Patel [6] ● The exact location of the dustbin can be found as the
project uses geolocation API is used
● It is cheaper as the project is entirely based on
NodeMCU
● The project uses NodeMCU and the
voltage level of NodeMCU is 3.3V.
Hence, any 5V Module can reset
NodeMCU.
● NodeMCU consumes more power
● Data is not stored anywhere; therefore,
only live monitoring can be done.
Sinha et. al. [7] ● As the project uses Arduino Mega, the power
consumption is less.
● Unique IDs have been used for dustbins, which makes
the collection process easier.
● No service has been used to detect the
location of the dustbin.
● Data is not stored anywhere; therefore,
only live monitoring can be done.
Table 2
Merits and Demerits Raspberry-PI Systems
Papers Merits Demerits
Mahajan et. al. [8] ● An optimized route is provided ensuring the fuel
consumption is minimal
● Real-time monitoring of fill level in the dustbins is
done
● The level of dry and wet waste in the bin is
determined
● The functions and usability of the web application is
mentioned inadequately
● This system uses Wi-Fi module ESP8266 which limits its
deployment range
● Using a load sensor increases the overall cost of the
system
Singh et. al. [9] ● It is a cost-effective system
● It can be employed on dustbins without a lid
● Route planning is also provided
● Using IR sensors instead of ultrasonic sensors do reduce
the system cost but reliability of system is also
compromised.
Pathak et. al. [10] ● Dustbins can be remotely monitored from any
location.
● It reduces manpower wastage by minimizing the
number of visits of the garbage collectors.
● Visualization tools help in keeping track of garbage
bins.
● The location of dustbins cannot be found.
● Dustbins only in the small range can be monitored as Wi-
Fi Module is limited to the Wi-Fi range.
Patra et. al. [11] ● Remote monitoring of dustbins can be done on a
web browser from anywhere.
● A hygienic environment is being created as the
system is also measuring the odor using the gas
sensor.
● As there are so many sensors, more power supply is
needed.
● The location of the dustbins can’t be found.
International Journal for Research in Applied Science & Engineering Technology (IJRASET)
ISSN: 2321-9653; IC Value: 45.98; SJ Impact Factor: 7.429
Volume 9 Issue III Mar 2021- Available at www.ijraset.com
©IJRASET: All Rights are Reserved
577
Jenisha et. al. [12] ● Dustbins can be monitored remotely from
everywhere.
● The location of dustbins is available with the help
of GPS.
● Bad smell is prevented as the gas sensor measures
the odor.
● More power is consumed as a lot of sensors are used.
IV. CONCLUSION
The waste monitoring system is among the most critical systems that contribute to environmental change by preventing garbage
overflow in the bins and foul odors. This analysis of various systems reveals that the Internet of Things has significantly improved
the consistency and reliability of waste management systems, as well as contributed to public health response. The use of Arduino
and Raspberry Pi in these systems has resulted in a more cost-effective and long-lasting waste management process. Both Arduino
and Raspberry Pi have their own benefits and drawbacks, but depending on the location and circumstances, one should select the
system which is most convenient and appropriate.
V. FUTURE SCOPE
Since the requirements for this project are easily available for engineering needs, we aim to develop a smart waste monitoring
system by ourselves and would like to see innovative ideas emerge in the future.
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