Trash to Cash using Machine Learning and Blockchain

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 09 Issue: 06 | Jun 2022 www.irjet.net p-ISSN: 2395-0072
© 2022, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page 2244
Trash to Cash using Machine Learning and Blockchain
Deepti Teragunti1, Sahana Hegde2, Manjunath G.S.3
1VIII Semester, Dept. of ISE, BNMIT
2 VIII Semester, Dept. of ISE, BNMIT
3Asst. Professor, Dept. of ISE, BNMIT, Karnataka, India
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Abstract - Globally, 53.6 million tonnes of electronic
garbage were produced in 2019, according to the Global e-
waste Monitor 2020, with just 17.4 percent of that being
recycled. India is the world's third largestproducerofe-waste,
with 3.2 million tonnes created annually. Increases in
industrialization, living standards, and discretionary money
have led in an increase in the volume of electrical and
electronic equipment (EEE) on the market, aswellasagrowth
in e-waste, which is currently the world's fastest increasing
waste source. It causes CO2 emissions, which contribute to
global warming and climate change, with serious effects for
both humans and the environment. To build a sustainable
environment, increased efforts are needed to improve present
practices such as collection schemes and management
methods in order to eliminate illegal e-waste trafficking and
legacy waste management systems.
Key Words: Blockchain, Carbon emission,Circulareconomy,
E-waste, CO2 forecasting, Incentives, NetZero target
1. INTRODUCTION
In 2019, humans generated 53.6 million tonnes of e-waste.
Only about 20% of this is collected and professionally
recycled. It’s unclear what happened to the remainder.
However, it is anticipated that many electronics end up in
garages or basements and are never recycled. We also know
that businesses resell e-waste on a large scale. There, e-
waste is dumped in landfills, where it is improperly
managed, poisoning persons and the environment. Old
electronics, on the other hand, are gold mines:smartphones,
computers, and refrigerators contain rich metals and rare
earths, and recycling them is both commercially and
environmentally beneficial. It is critical to properly manage
the waste that is generated. Consumption of goods or the
minimization of waste are not extremely important to
humans. Therefore, it is necessary to manage garbage
generation so that people can reuse recycledwaste.Theidea
of Trash to Cash is based on this fundamental concept.
Electronic waste contaminates theland,air,water,andliving
things in the environment. It's toxic and non-biodegradable.
Toxic pollutants are released into the environment when
open-air burning and acid baths are employed to recover
precious elements from electronic components. Workers
may also be exposed to high levels of contaminants such as
lead, mercury, beryllium, thallium, cadmium, and arsenic, as
well as brominated flame retardants (BFRs) and
polychlorinated biphenyls, all of which can cause
irreversible health effects such as cancer, miscarriages,
neurological damage, and IQ decline.
Informal waste collectors help to clean up India's cities
by recycling around 20% of the waste created. On the other
side, these waste pickers lack formal recognition, equal
rights, stable and secure livelihoods, and dignity. As
spending patterns evolve with a flourishing economy, their
labour exposes them to ever higher levels of pollution and
dangerous chemicals.
It's also crucial to consider how technological
advancements effect climate change. Every electrical item
ever created has a carbon footprint that contributes to
human-caused global warming. When it comes to the
amount of carbon dioxide released over the course of a
device's lifetime, the majority of it happens during
production, before customers buy it. As a result, low-carbon
manufacturing processes and inputs (such as the utilisation
of recycled raw materials) as well as product longevity are
important elements inoverall environmental effect. Globally,
recycling rates are poor. The global average is 20%; the
remaining 80% is undocumented, with much of it ending up
buried beneath the ground forgenerationsaswaste.E-waste
is not biodegradable. The global electronic sector is
experiencing a recycling crisis, which is worsening as
gadgets get more numerous, smaller,andcomplicated.Some
types of e-waste are now too expensive to recycle and
recover materials and metals from. The remaining e-waste,
which mostly consists of plastics containing metals and
chemicals, is a more challenging challenge to manage.
Current problems in the ewasterecyclingmethodologyhave
been identified and theE-wastemanagementprocessshould
include the following steps
To increase the transparency along all the steps of the trash
chain to improve waste management processes.
Encourage more people to start recycling by making
recycling simpler and rewarding.
Helping recyclers and manufacturers choose products and
foresee what will likely fall out of the recyclingsupplychain.
Reduce CO2 emission and help achieve Net-Zero Carbon
target.

2. RELATED WORK
In [1], Supply Chain Managementisregardedasoneofthe
most important and valuable applications of Blockchain
technology, since it allows organisations and businesses to
handle products at numerouslevels,fromtheproducertothe
client. A 5G ecosystempoweredbyblockchainmaygiveasafe
and accuraterecord of userdata,aswellastheguaranteethat
it has not been tampered with.
a) This will enable smart contracts to explicitly specify
collection targets and penalize parties if needed. It is also
proposed that customers be included as members of this
blockchain.
b) E-waste incentives can help reduce the dominance of
the unorganized sector in EWM. A stakeholder list can
include producers, retailers, collection centers,andrecycling
units.
c)The participants of the EWM include government
agencies and consumers.
d)The goal is to make the process ofgeneratinggoodsand
disposing of them more stimulating for everyone involved,
including dealers and producers.
e) OWASP is a published non-profit organisation whose
mission is to recommend impartial and actionable data on
application safety to developers, as well as to easily
understand and analysesecurityexpertsforpotentialimpact,
to assess web security, web service security, and the security
of the DISV central server. Thedigitisationofplasticrecycling
can assist in ensuring material traceability.
The motive of [1]is to discover the use of NFC and RFID-
enabled devices to obtain real-time data on manufactured
goods with complete transparency via a centralised cloud
database, right on the spot.
Limitations: It's never easy to manage resources in an
organised manner and reduce waste. The current recycling
management system isn't considered transparent.
In [2], Carbon emissions are a significant factor to climate
change. To achieve common CO2 emission reductions,
companies must work closely together across the supply
chain. Blockchain is one of the most significant emerging
technologies in the Industry 4.0 era, with numerous uses for
supply chain collaboration and integration. Blockchain
technology is being used in logistics and supply chains, but
we are still in the early stages of realising its full potential.
Whileindustrialandcommerciale-wastecollectionreceivesa
lot of attention, alternatives for e-waste collection from
residential homes are scarce. This paper proposes the
development of a mobile robot that uses transfer learning to
identify common e-waste and can be attached to existing
municipal rubbish vehicles. The robot walks around,
identifies e-waste, and uses an arm-based lifting and storing
mechanism to separate the identified material. With 96
percent accuracy, an identification method based on a
convolutional neuron network was employed to classify e-
waste.
Result: The study framework, Developing a Blockchain-
Enabled Low Carbon Supply Chain Framework, proposes
research propositions linking blockchain, supply chain
integration capability, and carbon emission using the Socio-
Technical Theory and Resource-Based View.
Limitations: Influence the way that organizations
collaborateand interact with oneanotherisdifficult.Flawsin
improving the productivity and sustainability of the supply
chain.
[3] Implementation of blockchain technology to set up an
automatic payment system forcollecting wastefromanyone.
A person processes payments to a local government account
via a mobile app.
a) An architecture that intervenes IoT-compatible hardware
and SWM blockchain has been proposed.
b) Hardware adaptation is implemented on the sensornodes
and gateways.
c) Using the Python-based Flask framework, Icreated aWeb
API to implement the proposed reward system.
d) This studyshowsverificationofaprivateblockchainminer
with a trust point.
e) Security is now an important component of increasing
importance in all technologies. In the case of blockchain,
security features have been differentiated, encouraging
researchers to integrateblockchain technology. The security
features of blockchain technology are robust because each
block is associated with a public key cryptographic
framework.
Result: A mechanism has been implemented to integrate
cloud servers into the blockchain network via the Flask
server-based API. In a real-time implementation, container
weights are observed to generate new transactions on the
blockchain network using sensor nodes that send real-time
data over the gateway to the cloud server.
Limitations: There is currently a lack of accurateinformation
on the amount and characteristics of waste as local
governments struggle to effectively manage waste to reduce
its impact on the environment.
In [4] By implementing a circular economy, this method can
promote a collaborative digital consortium for effective
plastic waste management, which can bring together
numerous stakeholders, including plastic manufacturers,

government bodies, retailers, suppliers, garbage collectors,
and recyclers.
a) Blockchainsare extremelyusefulfortrackingmaterials
across all types of supply chains.
b) Blockchain can help connect major refiningcompanies
with a new mode of plastic recycling to reinvent current
supply chains.
c) With this technology, plasticrecyclingcanberefinedby
feeding back the raw materials to themanufacturingprocess.
This creates a complete CE of the earth's tragic waste.
d) Blockchain can be usedtotrackindividualitemsthrough
the recycling supply chain create physical marks such as QR
codes and digital badges on plastic products.
e) This strategy of full transparency with the adoption of
blockchain allows consumers and investors to understand
and easily analyze the potential impact. Digitization of the
plastic recycling industry can support traceability.
Result: A mechanism has been implemented to integrate
cloud servers into the blockchain network via the Flask
server-based API. In a real-time implementation, container
weightsare observed and new transactionsaregeneratedon
the blockchain network. Use a sensor node that sends real-
time data to the cloud server over the gateway.
Limitations: The disposal percentages were decreased and
replaced with recycling and incineration.
Implementation of [5] Researchers have traditionally been
valuable in discovering ways to reduce environmental effect
and boost innovation by modifying product designs,
enhancing recycling, or conservingenergyandresources.We
created a life cycle analysis (LCA) technique as a tool. To
achieve the sought circular economy, electronics makers
mustcollaborateto better understand andimplementpatent
and copyright rules to all post-consumer products. To be
sustainable, this processmustbenefitallpartiesinvolved,but
potential buyers must be convinced that the pricing
differential between new and refurbished products will
continue to provide incentives. Before and after the supply
chain, all product transfers can be accompanied by vital,
transparent data. Even without the ability to recycle and
correctly manage electronic trash around the world where
electronic items are soldandconsumed,blockchainsolutions
are electronic while safeguarding the economic value
manufacturers desire to protect. You have the option to
broaden the scope of your waste management efforts.
Results: LCA techniques have become commonplace and
used to quantitatively assess environmental impacts at each
stage of the product life cycle.
Limitations: Workersandtheenvironmentareexposedto
toxins during the mining of e-waste for such materials. The
patent and copyright policy, which has emerged as a viable
solution for the use of digital ledgers, is a key open limitation
in applying 3re to e-waste.
[6] Apply artificial intelligence toimprovee-wastecollection:
Possible solutions for household WEEE collection and
separation in India-AV: Shreyas Madhav, Raghav Rajaraman,
S. Harini, Cinu C. Kiliroor. The deep learning garbage
classification method was analyzed on the garbage net
dataset to determine the most appropriate modeling
approach. The dataset contains the Trashnet dataset. This
datasetcontains images of recyclable materialssuchasglass,
paperboard, plastic, metal, and paper. Implements an
algorithm that includes an integrated detection system with
deep learning Densenet 21.
Result: Recycle Cube Robot: A new e-waste robot system
for identifying and collecting e-waste in the home. The
functioning of the system begins at each collection point on
the move of the city's garbage truck. Robots run around all
home collection points, take picturesofindividuallydisposed
waste, and use deep learning to identify e-waste. The
identified e-waste is collected and placed on the robot's
storage platform.
Limitation: Different accuracy is observed for each dataset.
Irjet Template sample paragraph .Define abbreviations and
acronyms the first time they are used in the text, even after
they have been defined in the abstract. Abbreviationssuchas
IEEE, SI, MKS, CGS, sc, dc, and rms do not have to be defined.
Do not use abbreviations in the title or heads unless they are
unavoidable.
3. PROBLEM STATEMENT
Electronic trash is hazardous, non-biodegradable, and
accumulates in the environment, including soil, air, water,
and living things. The influenceofelectronicwasteonclimate
change should be assessed. Every piece of technology ever
created has a carbon footprint and contributes to human-
caused global warming.
There are no clear criteria forhow electronic trash shouldbe
handled in the unorganised sector. There are no incentives
given toencourageconsumerstohandleelectronicgarbagein
a more formal manner. Working conditions in the informal
recycling sector are comparabletothoseinthelegalrecycling
sector, and there are no incentive systems in place to
motivate producers to take action to deal with e-waste.
Climate change is caused by human-generated carbon
emissions thatare increasingat a rapid pace, and are already
threatening various life forms on Earth. The level of
greenhouse gas emissions in 2020 was significantly higher
than ever before. Scientists agree that reducing emissionsby

85% below 2000 levels is the best way to avoid the many
devastating consequences of global warming. There is an
urgent need for emissions from all industrial sectors to be
reduced, and corporate innovation and initiative are
necessary to achieve this goal.
4. PROPOSED SOLUTION
The project's main goal is to provide a software tool that
integrates carbon footprint and industry statistics so that
businesses can estimate the environmental benefits of
reusing IT equipment by selling it off as ewaste before the
expiry of lifetime of the product.
The specific Research Objectives (ROs) that shaped the
project towards achieving the aforementioned aim, were:
 Identify and review environmental impacts, carbon
emissions and life cycle indicators of IT equipment,
that can be utilized when developing the tool.
 Research company specific data regarding carbon
emissions and materials used in IT equipment.
Analyse Co2 emissions from various countries over
the span of years till date.Perform visualization on
this data and generate reports.
 Create a Machine Learning application to forecastt
the amount of Co2 emission produced by year 2030
when a raw material/productwouldreachzeroC02
target
 Develop and implement the carbon calculation
tool,and reward the users and make recycling
simpler.
Fig – 1: System Architecture Diagram
A. CIRCULAR ECONOMY FOR ELECTRONICS
Various economic theories, such as the steady state
economy or degrowth, have attempted to suggest a solution
for a green and sustainable economic future in response to
today's economic model. Circular economy, being the most
popular theory aimed at overthrowing today's dominant
economic model and addressing environmental concerns,
opens the way for long-term economic growth and
development. CE aspires to change a linear economic model
into a circular, closed loop economy, where the stakes
between economy, environment, and society are balanced,
based on three primary principles (The Three Rs) of
Reducing,Reusing, andRecycling.For the manufacturingand
use of electronic and electrical items, a new perspective is
required. E-waste is commonly thought of as a post-
consumption issue, although the issue extends throughout
the device's life cycle. Designers, manufacturers, investors,
merchants, miners, commodity producers, consumers,
policymakers, and others all have a role to play in reducing
waste, preserving system value, and extending the economic
and physical lifetimes of commodities. They can also aid in
the repair of items. It will be recycled and utilised. As a result
of the rise of service business models and improved product
tracking and takeback, global circular value chains may
emerge. To address the needs of electronics supply chains,
material efficiency, recycling infrastructure, and scaling up
the amount and quality of recycled materials will all be
necessary. If the right policy combination is in place and the
sector is handled properly, it has the potential to create
millions of excellent employments around the world.
Fig - 2: Data Flow Diagram

In order to createan MLapplicationtopredicttheamount
of Co2 emission produced byyear 2030 when a raw material
/product would reach zero C02 target we have made use of
the ARIMA model.
B. CO2 FORECASTING
ALGORITHM: AutoRegressiveIntegratedMovingAverage
Model.
ARIMA is a method for locating models that employ an
iterative process. A model was chosen, and its suitabilitywas
tested using new historical data. The model would havebeen
appropriateiftheresidual(thedifferencebetweentheresults
of forecasting with historical data) was scattered at random,
moderate, and independent of each other. Only a stationary
temporal frame can be used with ARIMA. To begin, we must
assess whether or not our data is stationary. If our data isn't
stationary, we can look for data differentiation that will
become stationary, or we can look for the d value. This
procedure can make use of ACF (Auto Correlation Function),
unit roots test, and Integration Degree.
A dataset and a validation setare created from thedata.After
generating the model using the dataset, the validation set is
used to verify how well it works. We choose to use theperiod
1960-1999 for the dataset, and 2000-2018 for the validation
set.
We evaluate ARIMA models with different parameters and
looks for the optimal combination of parameters by making
use of our observations. Thevalues of theparametershaveto
be in a certain range. P has to be between 0 and 5, d between
0 and 3, and q between 0 and 5.
For the other parameters of the ARIMA model, we used two
graphs, one for autocorrelation and one for partial
autocorrelation. If wecompare these graphs to this example,
weassume that weneed to correct for autocorrelation,when
looking at the first graph. The second graph can be used to
see whether there is seasonality. In this case, the data is
yearly, and seasonality would not be an issue. Therefore, the
resulting ARIMA model might have the parameters (1,1,0).
Then we load and predict the model.
C.INCENTIVE GENERATION BY BLOCKCHAIN
Crypto is a new digital technology that is gaining interest
from financial institutions, investors, businesses,andfintech.
In 2022, consumer acceptance will increase, enabling
businesses to accept bitcoin as payment and incorporate it
into their loyalty programmes. The Covid shutdowns have
significantlyaltered the everydayroutinesofconsumers.The
usage of the internettomakepurchasesofgoodsandservices
has grown significantly. The current environment is perfect
for the proliferation of digital assets. Digital currencies have
quickly gained favour withbothconsumersandbusinesses.A
recent Gartner study predicts that by 2024, 20% of large
organisations will be using digital currency.
In a variety of ways, blockchain technology is being used for
incentive programmes. Blockchain-based rewards systems,
for example, can track and distribute points, vouchers, and
other loyalty programme perks. Furthermore, blockchain
technology can be used to authenticate customers and
prevent fraud. Because it is liquid and global,cryptocurrency
is quickly becoming the most desired digital prize. Thus, we
would be rewarding the users who contribute to the circular
trash chain with trash coins generated on blockchain.
5. IMPLEMENTATION
Literature review, algorithm development, and testing were
among the strategies employed to complete the planned
project.
The modules were implemented in three phases namely:
Data storage and Analysis: UsageofIBMCloudPak forData
as a service, we are able to make predictive analysis and
generate a report to country wise results.
Prediction Model and carbon calculator: The Carbon
emission calculator would be done on the basis of ARIMA
forecasting model, displayed on the frontendofourwebsite.
Incentive application to generate reward points: Based
on the predictive analysis, reward points would be
generated and would be assigned to user taking part, who
would be benefited in the long run else the user is discarded
but with valuable suggestions to improve the process in the
future.
6. RESULTS
Table 1: Results Obtained
SL.NO
ALGORITHMS
Model Accuracy RMSE
1 ARIMA 88.9 0.2544
Fig - 3: Home page of trash selling platform

Fig - 4: Sustainability services provided by our
platform
Fig - 5: Carbon Calculator
Allocating user a trash coin from one address to another
Fig - 6: Reward allocation to user participating in
circular economy
6. CONCLUSIONS
The Trash to Cash initiative encourages all stakeholders to
join a special circular chain that contributes to
environmental sustainability. Our service will compute the
Co2 emission created by each product and how much co2
may be avoided in order to achieve it, allowing users to be
profitable stakeholders by lending away the used E-waste
products. Blockchain is a system for storing data in a way
that makes system changes, hacking,andcheatingdifficultor
impossible. Blockchain is essentially a network of computer
systems that duplicates and distributes a digital log of
transactions across the network. A combination of these
technologies help our user to be granted with reward points
for successfully being a holder in the chain and who is
contributing in their own ways to reduce co2 Emission to
minimal amount and help us achieve Net zero target. Being
involved in the development of Carbon calculators, this
project is of great interest to environmental assessment
professionals and engineerslookingtodevelopstandardized
tools for assessing the environmental impact of various
human activities.
REFERENCES
[1] An Effective Electronic waste management solution
based on Blockchain Smart Contract in 5G Communities
–Poongodi M, Mounir Hamdi,
[2] Blockchain TechnologyandItsRoleinEnhancing Supply
Chain Integration Capability and Reducing Carbon
Emission - Michael Wan, Bill
[3] Blockchain Enabled Automatic Reward System in Solid
Waste Management byAuthors: Shaik Vaseem Akram,
Sultan S. Alshamrani, Rajesh Singh, Mamoon Rashid,
Anita Gehlot, Ahmed Saeed AlGhamdi, 6th September
https://www.hindawi.com/journals/scn/2021/695212
1/
[4] Efficient Plastic Recycling and Remolding Circular
Economy Using the Technology of Trust–Blockchain by
Authors: Swikriti Khadke, Pragya Gupta, Shanmukh
Rachakunta ,Chandreswar Mahata ,Suma Dawn 16th
August 2021- https://www.mdpi.com/2071-
1050/13/16/9142
[5] Zero E-waste: Regulatory impediments and blockchain
imperatives by Authors: MengjunChen1, OladeleA.
Ogunseitan: 31stJanuary2020
researchgate.net/publication/349661961_Zero_Ewaste_
Regulatory_impediments_and_blockchain_imperatives
[6] Application ofartificial intelligenceto enhancecollection
of E-waste: A potential solution for household WEEE
collection and segregation in India by Authors: AV
Shreyas Madhav Raghav Rajaraman, Harini and
CinuKiliroor.-
https://journals.sagepub.com/doi/full/10.1177/07342
42X211052846

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