Design and development of intelligent waste bin system with advertisement solution

Bulletin of Electrical Engineering and Informatics
Vol. 10, No. 2, April 2020, pp. 940~949
ISSN: 2302-9285, DOI: 10.11591/eei.v10i2.2753  940
Journal homepage: http://beei.org
Design and development of intelligent waste bin system with
advertisement solution
Tarig Faisal, Moath Awawdeh, Anees Bashir
Department of Electrical Engineering, Higher Colleges of Technology, UAE
Article Info ABSTRACT
Article history:
Received Nov 21, 2020
Revised Jan 14, 2021
Accepted Feb 6, 2021
In cities where a large geographical area of the city is densely populated, the
process of waste collection is cumbersome, tiresome and expensive. Often,
the burden of manually tracking and collecting of waste causes waste
management companies enormous wasted effort and get them involved in
tasks that are not necessary. No doubt, a digital interaction between waste
management companies and targeted waste collection areas could ensure the
process becomes fast, efficient and traceable as they become aware of the
states of the wastes, aptly. It will considerably reduce any discrepancies that
may occur due to the lack of information available during a particular time.
Accordingly, this paper proposes a novel approach towards waste
management combined with the internet of things to reduce the problems that
would occur due to the accumulation of wastes and hence improvise waste
collection/management process. Additionally, an innovative feature which
generates revenue and creates business opportunities for waste management
companies is introduced via advertisement solution based on network-
attached storage technology.
Keywords:
Advertisement solution
Internet of Things
Microcontroller
Quality network appliance
provider
Smart waste management
This is an open access article under the CC BY-SA license.
Corresponding Author:
Tarig Faisal
Department of Electrical Engineering
Higher Colleges of Technology
Ruwais, Al Dhafra, Abu Dhabi, United Arab Emirates
Email: tfaisal@hct.ac.ae
1. INTRODUCTION
Unarguable, urban cities across the globe are burdened with problem associated with waste
management such as collection and sorting of waste. Urban cities are con- fronted with overflowing bins
which cause a serious nuisance to the public. It does not only affect the overall aesthetics of the city, it is
reeks of awful, lousy sight and bad smell. The foul odor can become a root cause of various diseases [1].
Broadly stated, waste management refers to various activities connected to efficient collection and effective
disposal of waste; this includes many sub-activities like waste collection, waste disposal, waste
transportation, and waste recycling. United Nations Department of Economic and Social Affairs statistics
depicts that 3.4 billion tons of urban wastes would be generated by 2025 [2].
Prevalent waste management systems are characterized with large number of containers with
obscured or inconsistent filling levels [3-4] These obscured waste bins, depending of variety of factors (such
as area, location, distance, and type of waste, and even the season of the year) to get filled-up to maximum
level; that too, at different and inconsistent hours, days, weeks, or even months. The type of waste bin been
used makes it difficult to the waste management companies to optimally manage wastes due to the
irregularities in fill-up levels which resulting in waste spillages and waste pollution. Based on the above,
waste management companies and municipalities need optimal way embedded with system and tools to

Bulletin of Electr Eng & Inf ISSN: 2302-9285 
Design and development of intelligent waste bin system with advertisement solution (Tarig Faisal)
941
manage wastes in public places at the minimum cost and maximum efficiency. Hence, the existing waste
management procedures need to be revolutionized and upgraded with the latest technology for a large-scale
waste management. In recent times, there has been a widespread focus and attention on internet of things
(IoT) systems embedded with cloud storage in multiple applications that create a plethora of convenient
opportunities for various stakeholders for efficiently enhancing and optimizing their business procedures [5-7].
The fast-growing applications field of IoT to sensors and smart bins are already gaining attention in the waste
management area, especially in urban scenarios from the point of managing resources and optimizing
collecting routes [8]. Scholars have suggested expedient use of technology to improvise waste bins and ease
waste collections processes. Saha et al. [9] experimented a solar panel powered compaction waste bin with
mounted sensors to obtain readings of waste levels in bid to enhance the process of waste collection. The
collected real-time data is transmitted wirelessly to the cloud, which can be accessed by any 3rd parties who
are involved in the waste collection process. Thakker et al. [10] proposed all levels of a waste management
process begin with waste collection, waste separation until, and waste disposal. In this study an alarm system
triggers when the waste bin is full, and the information is relayed to the authorities when the levels of the
dumps are reaching the overflow state. Near-infrared (NIR) spectroscopy was used to separate plastics from
the waste and biogas plant was fed with the biodegradable wastes. Faisal et al. [11] used the developed an
intelligent real-time waste segregation system that automates the process of waste segregation and classifies
the waste. Real time images of the waste were used by the convolutional neural network to segregate the
waste. Ramya et al. [12] proposed a system to transmit waste bins unique identity (ID) and their location to
workers responsible for maintaining the bin through global system for mobile communication (GSM)
whenever the levels of the waste in the container are high.
In densely populated cities, manually checking each waste bin is not only cumbersome, it is both
tiresome and an expensive process. Several methods were conducted to optimize waste collection and
routes. Omara et al. [13] opined various parameters like maximum capacity and distribution model based on
Poissons rule to estimate the arrival rate of wastes and hence improving the effectiveness of waste collection
route for trucks. The system was designed in a way that an alarm is flagged off to the base station when the
waste bin reaches a maximum level and then data is transmitted through the cloud to find the most effective
method for collecting the waste. The system optimizes the path or route for collecting the waste as well as the
operational cost. Folianto et al. [14] studied a model where the locations of dumps were identified and
decided to be removed or replaced at other locations of higher demands. Using this model, the cleaning
companies can plan better whether they need to sanitize the bins, clean the empty boxes with contingents,
and it can also facilitate the route for the truck. Catania et al. [15] proposed a smart solution platform based
on Raspberry Pi and XBee module to interconnect information and communication from various domains.
The system was implemented in 2 steps; a monitoring phase where waste levels are monitored; a data
processing phase for optimization of the routes for waste collection. Additionally, opportunities for residents
are made available for recycling activities, by notifying them of the nearest bins. Anagnostopoulos et al. [16]
exposed the decision- making process to choose between routes to maintain lost operational cost using
intelligent solutions. Sensors, radio-frequency identification (RFID), and actuators were used to implement
dynamic waste management systems in 3 phases: i) planning the route of waste collection, ii) transportation
based on waste type, and iii) the recycling of wastes. Manqele et al. [17] introduced a decision-making
algorithm for the process of waste collection. The performance of various algorithms related to the data
reception, the transmission of data loss, and improving data reception were discussed. Cloud-based waste
management systems were discussed in [18]. Sensors are mounted on different containers specific for
different types of wastes. The obtained sensors data could be uploaded for third- party service providers to
retrieve information which helps in deciding the route for waste collection.
In addition to the above system, several techniques were employed to develop smart waste pin
including distribution model and machine learning [19, 20], and developing of models for optimal truck path
for waste collection and management [21, 22]. Those systems will be compared with our developed system in
section 5.3 since they have similar feature. In line with the above studies, this research proposes a novel
system that not only improvises the existing methods of waste collection but also generates revenue and
creates business opportunities to waste management companies. The IoT technology is used in designing the
proposed system to improve the efficiency of waste collection process which considerably reduces the
associated costs. The remainder of this paper is structured as follows: the following section discusses the
proposed system and its functionality. The third section presents the system operation while the circuit
diagram and IoT implementation are shown in the fourth section. The hardware and software
implementations are demonstrated in section five and the conclusion is drowned in the last section.

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2. PROPOSED SYSTEM AND FUNCTIONALITY
The main function of the proposed system to enable targeted company or municipality for better
real-time monitoring and optimizing of the waste collection process by modernize and improvise the entire
process of waste management. In general, the system comprises of a network of Master and Slave waste bins
stations, IoT system, and advertising system based on network-attached storage technology (NAS) solutions
using quality network appliance provider (QNAP) high-end product. The proposed solar-powered system is
designed in the way that the Master waste bin station gathers real-time sensors data from the Slave stations
and transmits them wirelessly to the IoT system. The IoT system is used to automatically visualize, analyze
and export the data to a decision support system, in which a user can remotely, monitoring the waste bins
network. This feature helps in real-time monitoring of the data in order to act efficiently in removing the
waste and hence helps to manage waste efficiently. Additionally, this data can be accessed from any web
browser or mobile device. The system is also equipped with a display screen which used for generating
business opportunities for companies involved in the waste management process.
Figure 1 show the block diagram of the intelligent waste bin system which comprises of three main
distinctive segments that are controlling the operation of the entire system. Setting up the Master waste bin
and interconnectivity between the Master bin stations and the Slave bin stations are included in the waste bin
hardware and data integration segment. In the second segment, the IoT and data management responsible of
the transmission of the information and data to the IoT network. Finally, the advertisement solution segment
deliberates the displaying information from the clients to the end-users via the cloud server.
Figure 1. Block diagram of the intelligent waste bin system
2.1. Data integration
The section houses both the master and slave set up. It governs the overall data transformation in the
entire system and the connectivity between various modules. Additionally, it forms the basis for the internet
connectivity and cloud servers. The Master module is mainly involved in data extraction and processing
while the Slave modules are involved in data gathering. The Slave bin stations are only responsible for
collection of data via the in-house installed sensors then transmit them to the Master bin station via nodes
connection. Those data comprise of various parameters including the level of waste, temperature, and gas

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detection in the system and the pin location. The extracted data is then transmitted to the IoT platform for
process parameters monitoring and further data processing. The in-house sensors are also connected to three
visual indicators to assist general public or users perceive the waste level by displaying different colors to
indicate different measurement levels. There is also a feature of alarming protocol embedded in the system
that notifies the authorities managing the process of waste collection regarding the waste levels and the
presence of smoke in the waste bin.
2.2. IoT platform and data management
The IoT Platform is used as the main real-time data monitoring unit to process and analyze all the
collected data and optimizes the resource by routing the waste collection from the control room. The control
room is the main component in this system which involves in a wide variety of tasks but not limited to
sharing of resources, monitoring of incurring costs, monitoring of logistics, precise location sharing, and
delivering a system of high reliability and efficiency.
The task of the IoT platform begins with the Slave bin stations transmitting their measurements via
their node micro-controller (NodeMCUs) to the Master bin stations NodeMCU. Then the Master station
processes the data and transmits it to the IoT platform using 3G/4G link using GSM. The data is streamed via
the IoT platform on a live basis and can be visualized and analyzed on a real time basis with cloud storage.
2.3. Advertisement solution
Since most companies depend on outdoor advertising to attract customers and consumers, the
proposed advertisement solution aimed to be as a platform for those companies to reach their customers in
public and therefore generating revenue for waste management companies. This is accomplished by attaching
advertisement screens to the bins and paired them up with the system to display any information or
advertisement. In the proposed system, the QNAP based cloud server is included as a part of the Master bin
station and used as a storage source for the displayed information. The QNAP is based on NAS advanced
technology which has revolutionized the field of cloud storage. It has a feature of being able to provide video
control with flexibility while maintaining good security features and ease of use. It also featured with
provisions for storing of multimedia and remote access that can help in providing innovative solutions to
support users to develop and contribute to various IoT, artificial intelligence (AI) and machine learning
solutions.
The access to the system is made from a control room through preconfigured applications connected
to the web to constantly monitoring and tracking all the system parameters maintained by the QNAP cloud
applications. The system users have access to the user interface via the browser using separate authentication
passwords to maintain the reliability and integrity of the system. The system users display the information or
advertisement via their commands which provide solutions for the management of the resources by cloud
services. A separated cloud server access page is also provided for the clients to send their requested display
information to the system via internet without any need of physical interaction with the system, hence it
considerably reduces the maintenance cost of the system
3. SYSTEM OPERATION AND PRINCIPLES OVERVIEW
The interconnected-systems flowchart shown in Figure 2, illustrates the operation principles of the
proposed system which contains two paths working concurrently; the main path of the data
collection/processing and the standalone advertisement system. As soon as the system is started and
initialized, the solar panel system is activated. Then the standalone advertisement system is activated by
initializing the QNAP device, access point (via 4G router mobile), display screen, and the QNAP cloud
connectivity. This part of the system is working independently from the waste bin main controller and
circuitry. The main path of the data collection/processing is the main hardware/software of the waste bin;
which is working as following: after the initialization of the circuit and parameters, the Master waste bin start
taking the GPS reading as well as its sensors starts takes the temperature, level, and gas reading. This action
is taken by running a loop namely ACT loop in which if any of the reading exceeds the pre-defined value
(threshold), the alarming protocol will be activated. The activation of the alarming protocol results on
sending alerting message to pre-registered number(s) and turning on the corresponding lights allocated at the
waste bin. The Master waste bin is then starts collecting measurement from Slave waste bins after initializing
the serial connection configuration. Once all data are collected, the Master waste bin firstly construct a matrix
with all collected readings and then initiate the communication loop with Thing speak platform. The 4G
module connected in the Master waste bin controller is used to send the collected data to the ThingSpeak
platform for graphical representation. The ThingSpeak platform supported also with analytical tool for the
decision maker where measures can be extracted also as datasets.

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Figure 2. Flow chart of the proposed intelligent IoT waste bin system
4. CIRCUIT DIAGRAM AND IoT IMPLEMENTATION
The system is comprised of two circuits; the main circuit which attached to the Master station and
the sub-circuit which attached to the Slave stations. The main circuit shown in Figure 3 provides full
operating functionality of the system. The main supply of power constitutes of the solar panel and its
peripherals. The control circuitry of the system responsible for managing and governing the entire circuit.
The edge support is provided by the ATMEGA 2560 (8-bit microcontroller), which serves as the brain of the
system for processes data obtained from the sensors network (level sensor, temperature, gas) and the GPS
coordination. Additionally, the ATMEGA 2560 is connected to indicators to display the level of waste in the
system. The green panel indicator implies that there is a low level of waste in the system, the orange panel
indicator implies a medium level of occupancy, and red indicate the maximum level of waste.
The obtained data from the Slave stations is received by the NodeMCU controller and then transmit
them to IoT gateway via GSM module. The GSM module is used to transmit the data the IoT platform via a
3G/4G link. The circuit also includes buck voltage converter, a real time clock module, relay module, and a
voice recorder module. More details about the circuit operation can be found in [23]. The sub-circuit which
attached to the Slave stations comprises of the same constituents as the Master except for the GSM module
since the communication between the system and the IoT is performed only via the Master station.

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Figure 3. Circuit diagram of Master intelligent IoT waste bin system
5. RESULTS AND DISCUSSION
The hardware and software implementation of the intelligent waste bin are shown in the following
sections
5.1. Hardware implementation
The power supply circuit consists of a solar panel that powers the entire circuit which produces an
output voltage of around 18 V DC to power the control circuitry and the advertisement screen. A complete
solar panel circuitry is considered including a charge controller, a rechargeable DC battery, and a solar power
inverter. The overall system is fitted with a digital voltmeter that indicates the level of charge stored in the
battery (LED display) for monitoring the available charges percentage in the system. A buck converter board
is used to steps down the incoming voltage to power various other circuitry components that require different
level of voltages (including also DC-DC adjustable voltage regulator). Figure 4 shows the hardware circuitry
of the system that serves as the main controller. The circuit contains the ATMEGA 2560 Arduino mega
controller which serves as the data integration processor. The controller has 54 I/O pins that is used for
allowing smooth connections with different peripherals such as GSM, GPS, various sensors, and relay
module. The screw shields attached to the microcontroller provides robust connections between all the
control circuitry. The figure also shows the NodeMCU that communicate with other Slave bin stations
NodeMCUs. The Sim900a GSM module used in the circuit operates with cell phone network, controlled via
AT commands with Quad-band 850-1900 MHz. A preconfigured GPS development board is used for
location purposes with GPS antenna interface. The level, temperature, and gas sensor are placed underneath
the circuit board. The HC SR04 transducer sensor is used to measure the level in the systems (two units are
used for comparison reason). It can measure a level up to a maximum of four meters and the angle of
measurement is about 15 degrees. The digital temperature sensor uses a thermistor and humidity sensor in
order to monitor the surrounding environment and it takes about 2 seconds to read the real time measurement
values. In order to monitor the level of gas the MQ series sensor is used which has fast response rate and
good sensitivity. The voltage converters and relay board are used to control the different level of voltages in

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the circuit (3.3, 5, 9, and 12 Volts). The NodeMCU has the ESP 8266 chip with storage capacity of 4 MB
external flash memory and random-access memory (RAM) of 128 KB. The main technical challenge in
hardware implantation was the communication protocol from Espino to the IoT platform from different nodes
and the limitation of data format. To overcome this challenge, we have used the GSM module to send the
data to ThingSpeak and creating one access point at master side to ensure mostly the data connectivity
between 3 Slaves nodes and the master node.
Figure 4. Main control circuitry of the intelligent waste bin
The advertisement solution is implemented using QNAP as shown in Figure 5. The basic idea of
using such system is to create a remotely controlled space for sending advertisement to a connected screen.
The system is mainly constructed using QNAP TS-251 plus 4TB which is high-performance NAS with on-
the-fly and offline video transcoding, connected to 4G network using internet GSM 4G module of internes
access point and via high-definition multimedia interface (HDMI) cable to a smart screen. Finally, the
finalize prototype design is shown in Figure 6.
Figure 5. QNAP Connectivity and screen display
(a) (b)
Figure 6. Final designed prototype, (a) The final prototype design with covered top, (b) The final prototype
design showing control circuitry

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5.2. Software implementation
The system is operated with three main software platforms Arduino IDE, ThingSpeak, and QNAP
cloud. Those platforms aim to serve the main circuit hardware, IoT monitoring, and advertisement solution
respectively. The first platform provisions the Master station to collect the measurement from Slave waste
bins. This stage requires setting up the software serial and ESP8266 Wi-Fi packages for all stations (Arduino
and Espino, where NodeMCU ESP8266 has been used in many applications for remote monitoring [24, 25].
In the second platform the ThinkSpeak with academic license associated together with MATLAB license [26],
is used which is widely adopted for different applications [27, 28]. The platform aims to provide generic
graph representation of the received measurements over time scale for each waste bin and lamp indicator of
specific waste bin whenever the level reading is exceeding 80%. Figure 7 shows a sample of those graphs
while Table 1, shows an example of data extraction and availability. Additionally, all available data can be
exported in different format for detailed analysis using MATLAB visualization built-in tools in the project
page. ThingSpeak platform provides the ability to export all channels feeds in various formats which provide
an opportunity for more analysis application, and hence generating a detailed report of the waste bins
network.
(a) (b)
Figure 7. Sample of collected measurement, (a) Sample of level data representation, (b) Sample of
temperature testing and indicator lamp
Table 1. Data extraction tools and availability
Tools File type Raw data Available index
MATLAB visualization and analysis .mat [m]
Level, temp, and gas
detection for all
Date and time, entity ID, field,
and location for all
Export data JSON, XML, CSV
Graphical interpretation Plot
The proposed advertisement solution, mainly uses QNAP cloud, more specifically photo station, file
station, and QTS desktop; once the connection is set-up and the module is configured, the user can upload all
advertisement to the cloud in photo station sub content and hence push to show in the configured screen.
MyQNAP cloud GUI shown in Figure 8, is the main environment for the end user for uploading, processing
and pushing advertisement. The user needs to register for QNAP cloud and hence licensing the NAS account
in order to enable the cloud remote access services.
Figure 8. The main QNAP cloud page of the project

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5.3. Comparison with existing systems
Table 2 features the comparison between the proposed system and other some existing developed
systems. In general, the proposed system contributed to the existing systems in mainly three categories: i) the
design of waste bin networks which is described in previous sections as master and slave, such approach will
reduce the designing cost and operational efforts, ii) the collected data and alarming flags are stored to the
cloud and can be easily accessed by decision makers, iii) the advertisement solution present by using QNAP
technology.
Table 2. Brief comparison of the existing smart waste bins and the proposed system
Reference Feature Implemented HW/SW Advantages
Rahman, et
al., 2020 [19]
▪ CNN deep learning
▪ Waste classification
▪ Real-time IoT monitoring
▪ System is equipped with rasp-berry
pi, camera, sensors and Arduino for
the prototype with android
application
▪ Detecting of waste level and
weight
▪ Classification accuracy
Dubey, et al.,
2020 [20]
▪ KNN machine learning
▪ Waste segregation
▪ System is modeled with raspberry
and Adafruit IO free web Service
▪ Alarming accuracy
▪ KNN model accuracy
▪ Data visualization and dash-board
Likotiko, et
al., 2017 [21]
▪ Multi-agent based modeling
approach
▪ Simulation of optimal route
for waste collection
▪ Netlogo Multi-agent platform has
been used to simulate real time
monitoring and smart decisions on
waste management.
▪ Real-time reporting and waste
monitoring
▪ Use of WSN Technology
Khoa, et al.,
2020 [22]
▪ predicting the probability of
the waste level in trash bins
▪ ML and graph theory
▪ LoRa technology
▪ System is presented by optimal
algorithm combining graph theory
and LR (system architecture of IoT
and LoRa is presented)
▪ System optimizes the collection
of waste with the shortest path
▪ low-cost design circuit
▪ System is tested in real
environment and saves operation
and time costs
▪ Mobile application
Omara, et al.,
2018 [13]
▪ WSN-driven system
▪ ILP Model
▪ Trajectory assistant
▪ Optimal truck path
▪ The proposed framework is simulated
as the waste bins are equipped with
sensors for level monitoring and
alarms that are wirelessly
communicated to a cloud
▪ Optimization solution
▪ Cloud platform
▪ Reduce cost of waste disposal
▪ Alarming protocol to cloud is
adapted
Proposed
system
▪ Real-time waste monitoring
including temperature, level,
and gas monitoring
▪ Real-time authority alert
system
▪ Real-time advertisement
solution via video streaming
through cloud services
▪ QNAP and IoT technology
▪ The System is equipped with various
sensors, microcontrollers (ATMEGA
2560), QNAP technology (QNAP
TS-251 plus 4TB), GSM/GPS and
IoT/cloud based services to collect
data for monitoring, analyzing, and
alerting in addition to podcasting
advertisement from the server to the
public.
▪ Works for waste bin networks
▪ IoT End-user tool for data
analysis
▪ Advertisement solution
▪ Real-time data monitoring
▪ Cloud platform
▪ Alarming protocol
▪ Applied on real life
6. CONCLUSION
This research proposed a holistic solution aids the waste management companies and municipalities
in managing wastes in public places at the minimum cost, maximum efficiency, and additional revenue. The
designed smart waste bins (master and slave) combined with the IoT platform helps in facilitating real time
data for easy scheduling of waste collection and route planning and hence enables the targeted
company/municipality for better monitoring and optimizing the collection process. The proposed
advertisement solution based on the QNAP system helps in generating extra revenue to maintain and develop
the system. Additionally, the cloud server used to display information on the screen reduces the manual
intervention in the system and facilitate smooth operation. From a sustainability point of view, the proposed
system has the possibility of self-funding if adopted by waste management authority, thorough the revenue
that would be generated via adverts. Since most organizations rely heavily on outdoor advertising to attract
customers and consumers, the proposed IoT waste bin provides a veritable avenue to reach their customers at
the grassroots.
ACKNOWLEDGEMENTS
This research is supported by Higher Colleges of Technology, Interdisciplinary Applied Research
fund, Fund No. 103113.

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