BLOCKCHAIN ENABLED SMART PUC SYSTEM FOR CONTINUOUS VEHICLE EMISSION MONITORING IN INDIA

Abstract

A system for predicting and monitoring vehicle emissions with a decentralized application and a wallet. A PUC kit attached to the tailpipe captures emission readings from pctrol/CNG and diesel vehicles. These readings arc transmitted securely to the blockchain network through the owner's mobile device, which acts as an edge node. Smart contracts enforce emission standards and endorse vehicles meeting the criteria. Endorsements are digitally signed by MVIs for added security. Owners receive redeemable tokens for compliance, which can be exchanged for services at fuel stations and insurance agencies. A predictive analytics engine forecasts emission patterns and prompts users to schedule maintenance when necessary. This framework promotes transparency, efficiency,, and accountability in vehicle emission monitoring, fostering a more environmentally conscious ecosystem.

Specification

Field of Invention
This invention relates to a decentralized and smart system for PUC testing vehicles to monitor
emissions continuously in India. By incorporating blockchain technology for emission tracking,
it enhances air quality control, supporting environmental conservation and sustainability
initiatives in the transportation sector.
Background of the Invention
The rapid urbanization in India has resulted in a tremendous increase in the number of motor
vehicles. As the number of vehicles continues to grow and the consequent congestion increases,
vehicles are now becoming the main source of air pollution in urban India. India is the fifthlargest
car manufacturer globally with a I 0% compound annual growth rate in vehicle
registrations as of20 19. Due to economic growth and the desire for vehicle ownership, annual
car sales in India are projected to triple fi·om 3.5 million to I 0.5 million by 2030, with cars and
two-wheelers expected to dominate the tleet at 87%.
The World Health Organization (WHO) identifies air pollution as a significant environmental
carcinogen, posing a higher risk of lung cancer than second-hand smoke. Particulate matter 2.5
(PM2.5) is highlighted as a particularly hazardous air pollutant due to its ability to deeply
penetrate human lungs. Typically, vehicles annually contribute about 290 gigagrams (Gg) which
is 20-30% of PM2.5 ai the breathing level of air quality. Vehicles in major metropolitan cities
are estimated to account for 70% of CO, 50% ofHC, 30-40% ofNOx, 30% ofSPM, and 10%
of S02 of the total pollution load. These high levels of pollutants are mainly responsible for
respiratory and other air pollution-related ailments including lung cancer, asthma, etc., which is
significantly higher than the national average. Recent studies indicate that in India, the Air
Quality Index (AQI) is deteriorating steadily, leading to a rise in lung cancer mortality rates.
Long-term exposure to PM2.5 can also increase the risks of cardiovascular diseases. The impact
of increasing vehicle pollution levels on the rising mortality rate in India is a growing concern.
The current Pollution Under Control (PUC) system has several limitations highlighting the need
for a more advanced and secure system:
• The current PUC certificates are prone to tampering and manipulating test results which
can compromise the accuracy and authenticity of emission data.
• The absence of a transparent and auditable system raises concerns about the reliability
and integrity of the emission data collected during PUC tests.
• The manual nature of the process for renewing PUC certificates and conducting periodic
tests leaves room for corruption and bribery, undermining the effectiveness of emission
monitoring and regulatory compliance.
• Manual testing offers a snapshot of emission levels at a specific time, failing to capture
real-time data on continuous emissions between tests. This allows vehicles with high
emissions to pass the test through temporary adjustments.
• There is no mandatory provision for vehicle servicing even if the PUC test fails to meet
the emission standards.
• Emission data from PUC tests is not centrally stored, making it difficult to track
individual vehicle histories and analyze pollution trends effectively.
Ineffective emission monitoring allows polluting vehicles to remain on the road, worsening air
quality. The rise in health problems due to air pollution translates to a significant economic burden
on individuals and the healthcarc system. To address these issues, the present invention proposes
a blockchain-enabled smart PUC system for continuous vehicle emission monitoring.
Prior Art
202121036987 discloses a method for testing vehicle emissions that involves the usc of an
analyzer unit, analyzing pipe, transmitter sensor, receiver sensor, gas analyzer, controller, and
vehicle module to ensure accurate and reliable emission testing. The process involves pressing
the PUC test button, signal transmission between components, comparing emission parameters,
and displaying results on the dashboard, highlighting a systematic approach for effective PUC
tests.
202121036971 discloses the system with the gas analyzer connects to the digital display timer
unit via a data cable. When the gas analyzer is inserted into the exhaust pipe, it assesses the
emission quality and r~eds the expiry time in days to the digital display timer -unit. The timer
then indicates the time remaining for the PUC recheck. When there is only I day left, the beeper
starts beeping to signal the impending expiry. If the timer reaches zero days left, the blue LED
indicates that the PUC certification has expired. Once the PUC recertification is completed, the
beeper and the blue LED are automatically turned off.
202321025855 discloses a system to detect license plates with vehicle monitoring and control
mechanisms. This invention demonstrates the use of deep learning models for segmentation,
and character recognition in license plates, along with real-time vehicle monitoring, and PUC
certificate verification processes for emission control compliance. It also proposes the
automation of manual tasks related to PUC certificate verification and enforcement of fines.
US20190025158Al involves an exhaust emissions monitoring device designed to attach to the
tailpipe of the vehicle. The device includes sensors for NOx, temperature, ammonia, and
particulate matter, each sensor exposed to the exhaust flow passage. These sensors collect data
on exhaust properties and constituents, which are then transmitted to a processor/data logger for
analysis and monitoring. The system utilizes loT technology to enable continuous and real-time
monitoring of vehicle emissions, ensuring compliance with environmental regulations.
Objectives of the present invention
I. Develop a system combining blockchain and loT for real-time monitoring of vehicle
emissions in India's pollution control certification, enhancing accuracy.
·2. Implement automated emission testing to replace manual processes in traditional centres
and eliminate the need for third-party testing facilities by decentralization.
3. Introduce predictive maintenance f~r vehicles using machine learning models to
forecast emission trtuds, promote timely maintenance, and enhance user awareness
through digital interfaces and alerts.
4. Encourage user participation by rewarding compliance with redeemable tokens, which
can be used for services, while restricting non-compliant vehicles from accessing certain
services.
5. Utilize smart PUC verification to ensure the credibility of endorsements, maintaining a
reliable system for evaluating vehicle emissions and conditions.
Summary ofthe Invention
The invention introduces a blockchain-enabled Internet ofThfngs (loT) solution designed for
ongoing monitoring of vehicle emissions, with a focus on enhancing the issuance of Pollution
Under Control (PUC) certificates in India. This system facilitates vehicle owner registration
through a decentralized application (DApp) and smart contract, creating a unique identifier
using the owner's Metamask wallet and public address. By integrating PUC kits with loT
sensors in vehicles, emissions from petroi/CNG and diesel vehicles are continuously monitored,
with data processed at the edge node and then transmitted to the blockchain network for
validation. The deployment of smart contracts within an Ethcreum Virtual Machine (EVM)
automates the PUC validation process based on predefined emission standards, with digital
endorsements provided by Motor Vehicle Inspectors (MVls). Compliant owners receive
redemption tokens as rewards, which can be exchanged for services at fuel stations, insurance
providers, and maintenance centers. Additionally, a Predictive Analytics Engine utilizing
XGBoost and meta-models predicts emission trends and recommends optimal vehicle
maintenance schedules, with notifications delivered to users via display systems and SMS. This
innovation aims to enhance security, transparency, and efficiency within the PUC certification
framework, encourage responsible vehicle maintenance, and promote a community of
environmentally conscious vehicle owners in India.
Short Forms used in the present description
I. Compressed Natural Gas is referred to as CNG.
2. Carbon Monoxide is referred to as CO.
3. Ethereum Virtual Machine is referred to as EVM.
4. Global Positioning System is referred to as GPS.
5. Hydrocarbons are referred to as HC.
6. Internet ofThings is referred to as loT.
7. Motor Vehicle Inspectors are referred to as MY Is.
8. Nitrogen Oxides are referred to as NOx.
9. Particulate Matter with a diameter of less than 2.5 micrometers is referred to as PM2.5 .
I 0. Pollution Under Control is referred to as PUC.
II. Short Message Service is referred to as SMS.
12. eXtreme Gradient Boosting is referred to as XGBoost.
Brief description of the accompanying drawings
Figure 1 illustrates the owner enrolment process
Figure 2 shows the components of the PUC kit with sensors
- Figure 3 depicts the internal architecture ofblockchain application
- Figure 4 encompasses the components of predictive analytic engine, dashboard and
redemption centres.
Reference numerals in the drawings
I. Vehicle owner
2. Metamask wallet
3. Pass phrase
4. Public address
5. License number
6. Registration number
7. Registration number photo
8. Unique 10
9. PUC Kit
10. Tailpipe
II. MiCS-5524 sensor
12. mq7 sensor
13. TGS2600 sensor
14. Plantower PMS5003 sensor
15. Edge node
16. GPS module
17. WiFi module
18. Pre-procesed data
19. Ethereum Virtual Machine
20. Smart contract
21. Flagged vehicles
22. Motor Vehicle Inspector
23. Endorsement
24. Token
25. Fuel station
26. Maintenance service
27. Insurance office
28. Incentives
29. Predictive analytics engine
30. Pre-historic dataset
31. Meta-model
32. XGBoost model
33. Prognostic data
34. Dashboard
35. Display system
36. Notification/Alert system
Detailed description of the invention
In India, the Pollution Under Control (PUC) system mandates continuous monitoring of vehicle
emissions to ensure environmental standards are met. The present invention combines loT for
real-time monitoring and blockchain for secure data management to represent a significant
advancement in ensuring vehicles comply with emission standards in the PUC certification
process oflndia. The process by which owners enroll and set up their accounts in the system is
depicted in figure 1. The owner of the vehicle (1) is directed to utilize the Metamask
cryptocurrency wallet (2) to submit the necessary details for the enrolment procedure, and they
are provided with a distinctive identification number, Unique ID (8). Figure 2 illustrates the
PUC kit (9), which consists of four sensors (11-14) attached to the vehicle's exhaust pipe (10).
This setup is used to monitor and record pollution levels emitted by gasoline and compressed
natural gas (CNG) powered vehicles. The internal architecture of the blockchain application,
which uses smart contracts (20) to automate processes and generate MVIs (22) is shown in
Figure 3. Figure 4 showcases the dashboard (34), redemption centres, and XGBoost (32) as
integral components of the system.
Initial Setup
The system mandates that vehicle owners (I) initiate the enrolment process by providing a
pass phrase (3) in conjunction with their license number (5), registration number (6), and a photo
of the registration document (7). Subsequently, this information is securely stored on the
blockchain network, generating a distinct 10 (8) for identification purposes. Through the
utilization of a secure elliptic curve encryption algorithm, the owner's public address (4),
passphrase, and Metamask account (2) are combined to form the unique 10.
To streamline the enrolment process, we have implemented an owner enrolment algorithm.
Before proceeding with enrolment, owners are required to complete registration on the official
website "parivahan.gov.in." It is imperative to segregate the vehicle into fuel type, either petrol
or diesel and engine type, whether BS-IV or BS-VI. This necessitates accessing the vehicle
details available on the Parivahan website to ensure accurate classification and seamless
enrolment. Upon successful registration, the owner is directed to the DApp dashboard, granting
them access to endorsements and view extensive emission statistics. This approach not only
enhances the issuance of PUC Certificates but also ensures improved levels of security,
transparency, and efficiency, setting a new standard in emissions control and certification
processes.
PUC kit
The owner enrolment process transitions into the emission testing phase, where the owner's
vehicles undergo testing utilizing the integrated PUC kit (9). The imperative need for this
integration stems from the inad~quacy of existing Pollution Under Control Certificate (PUCC)
test centers in terms of testing infrastructure, standards, and regulatory frameworks. By
incorporating the PUC Kit, we aim to eliminate the manual intervention inherent in traditional
testing centers and diminish reliance on external testing facilities, thereby enhancing efficiency
and accuracy in emissions testing procedures. The PUC Kit is designed to analyze emissions
from two distinct vehicle categories: diesel and gasolinc/CNG vehicles. Each vehicle type emits
different gases into the environment: diesel engines release PM2.5, while gasoline and CNG
vehicles emit carbon monoxide (CO), nitrogen oxides (NOx), and hydrocarbons (HC). To detect these specific gases, we utilize loT sensors like the Plantower PMS5003 (14) for diesel vehicles
and the MiCS-5524 (NOx) (II), MQ-7 (CO) ( 12), and TGS2600 (HC) ( 13) for petroi/CNG
vehicles. Positioned in the tailpipes (10), these sensors facilitate real-time emission
measurements, enhancing the accuracy and efficiency of monitoring processes.
The integration of an edge node (15), typically the user's mobile device, enhances sensor
functionality by enabling faster data processing, reduced latency, and improved device-todevice
connectivity. This edge node facilitates continuous monitoring, updating readings to the
blockchain and the user daily if the vehicle is in use. It filters, evaluates, and aggregates data
before transmitting relevant information to the blockchain network, reducing data transmission
and ensuring data quality. Processed data ( 18) is then swiftly sent via Wi-Fi ( 17) on the edge
node to the peer-to-peer (p2p) network for validation, supporting decentralized verification and
predictive analytics.
Blockchain application architecture
The processed data from PUC kit easily integrates with the smart contract running in EYM,
which is programmed with the PUC Endorsement algorithm. This algorithm ensures constant
system monitoring by running each time it receives data from the PUC kit. When certain criteria
are satisfied, the smart contract functions as a self-executing digital agreement that automates
the execution, enforcement, or verification of contractual provisions. This smart contract has
methods designed to examine emissions data from diesel and gasoline-powered automobiles.
The PUC Endorsement algorithm check readings against predetermined criteria, considering
the different standards for these vehicle types. If a vehicle fails the test, it is reported to the
authorities, flagged (21 ), and subsequently limited in access to gas stations (25) and insurance
services (27). This method ensures ongoing vehicle tracking and monitoring.
Every month, the vehicle owner receives an endorsement (23) containing the processed data
from the PUC kit for the previous 30 days. This data is sent daily as a parameter to the smart
contract, which evaluates it against predetermined criteria using integrated functions. After 30
days, vehicles meeting the required pollution levels are granted endorsements, entitling them to
services. However, vehicles that failed to meet the requirements on any given day arc prohibited
from continuing the certification process. Dedicated network members, known as MY Is (22),
stationed within Regional Transport Office (RTO) offices, arc responsible for the endorsement
process.
El Gamal algorithm is utilized by MY Is to digitally sign the endorsements, verifying vehicle
conditions and associated procedures. These signed endorsements are securely stored on the
blockchain network. Simultaneously, the edge node leverages GPS ( 16) to transmit the vehicle's
geographic location. This data allows the relevant regional MVI in any Indian region to access
and sign the endorsement. Owners are rewarded with redeemable tokens (24), serving as
incentives (28) for active participation in the network in exchange for compliance. These tokens
are accepted by refueling stations, insurance companies, and maintenance facilities as payment
for services (26). Additionally, information about approved owners is consistently updated in
the databases of gas stations and insurance providers.
Automobiles that do not engage with the network or lack endorsements face limitations,
rendering them ineligible for services from gas stations and insurance companies. This strategic
approach aims to foster an ecologically conscious owner community by incentivizing cars to
participate in the network. Occasionally, concerns may arise from other MVls in the network
regarding specific endorsements, necessitating resolution. The PUC Verification Algorithm is
utilized to address such issues by confirming the signature and data in endorsements. This
algorithm consists of two key steps: decoding the El Gamal algorithm to extract endorsement
data and verifYing the endorsement's signature using a two-step verification process involving
data bounds and public key validation. This meticulous verification process ensures the integrity
and accuracy of endorsements, maintaining a reliable system for evaluating emissions and
vehicle conditions
Predictive Analytic Engine, Redemption centers, and Dashboard display
Owners currently face challenges in maintaining their vehicles due to a lack of accountability
for emissions, leading to emission-related issues. To address this, a proactive approach utilizing
predictive analytics can forecast emission trends and recommend optimal maintenance
schedules. It incorporates a Predictive Analytics Engine that uses XGBoost (32) algorithm
known for its proficiency in complex predictions. XGBuost is a robust technique for time series
data to forecast maintenance needs beyond a two-day horizon. The initial phase involves the
generation of a prehistoric dataset (30), including handling missing data, encoding variables,
and scaling features, to ensure the model's effectiveness in predicting and optimizing vehicle
maintenance schedules.
XGBoost makes use of a meta-model (31), which is a different model trained to forecast
emissions if the vehicle is not serviced soon. By stacking these forecasts, a meta-model using a
Gradient gradient-boosting regressor can anticipate emissions with high accuracy and proactive
maintenance across several future periods. The foundational dataset, which was obtained from
the Parivahan database during owner enrolment, includes crucial characteristics I inked to
estimating car emissions, such as fuel type, model type, and engine type. To anticipate future
data, we use the XGBoost model in conjunction with a meta-model to compare the present data
with historical data based on fuel type and engine type. The vehicle's edge node receives the
expected data (33) and uses a decision tree model to forecast the next maintenance period based
on this anticipated data. The edge node notifies the user to schedule maintenance via the display
system (35) and SMS on their mobile device (36), if the decision tree data indicates a serious
state. Additionally, the dashboard interface (34) encourages responsibility by continuously
providing the user with information regarding the vehicle's emission trend. By increasing user
knowledge, this proactive strategy promotes more conscientious and prompt vehicle
maintenance.
Acknowledgments
The authors would like to extend their gratitude to the Management and Principal of Mepco
Schlenk Engineering College {Autonomous), Sivakasi for providing ample facilities and
support to carry out this work.
CLAIMS
We claim the following:
I. Blockchain-based loT integrated system where a PUC kit (9) is attached to the tailpipe
(I 0) that continuously measures and processes vehicle emissions, transmitting it to the
node running on Ethercum Virtual Machine (EVM) (19) via Wi-Fi (17).
2. The PUC kit mentioned in claim I includes MiCS-5524 (II), MQ-7 (12), and TGS2600
(13) sensors to detect carbon monoxide (CO), nitrogen oxides (NOx), and hydrocarbons
(HC) respectively from petrol/CNG vehicles and the plantower PMS5003 ·(14) for
diesel vehicles to detect particulate matter (PM2.5 -smoke density).
3. The edge node mentioned in claim I is the mobile phone of the vehicle owner (1), by
which the sensor data are forwarded to the EVM via its Wi-Fi at configured intervals
for analysis.
4. The endorsement is digitally signed using the EIGamal signature by the regional MVI,
uses GPS (16) from an edge node to locate the regional MVI, ami provides redeemable
tokens as a reward for following regulations.
5. The endorsed user details are promptly updated in the databases of fuel stations and
insurance companies where vehicles without endorsements arc banned from using
services and marked as flagged (21 ).
6. The predictive analytics engine pre-train XGBoost model that uses emission data,
maintenance history (30), and mileage to predict current and future emissions, with a
ITleta-model (31) estimating multi-period emissions for proactive maintenance.
7.· The prior notification and alert sub-module wherein if the forecasted data indicates a
critical condition, the edge node sends a notification to the user through the dashboard
interface and SMS via mobile, prompting scheduled maintenance.
8. The digital display is the interface in the dashboard (34) that consistently informs the
user about the emission pattern which enhances user awareness, contributing to more
responsible and timely vehicle maintenance.
9. Web user interface is a OApp that facilitates owner registration through the Parivahan database. It involves a digital signing process conducted by regional MVI and the
management of digital assets such as tokens and signed endorsements using a dedicated
wallet provided to the vehicle owner.

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