Thursday, 26 June 2025

Project ROTE = Reduction of Transport Emission

27 June, 2025 / My 92nd Birthday

Prof. V. Kamakoti

Director, IIT Madras

📧 kama@cse.iitm.ac.in

Subject:

Proposal Submission — ROTE: Reduction Of Transport Emissions (Simulation

Project for Chennai)

Dear Prof. Kamakoti,

As someone who has long admired your leadership in advancing India’s technological and environmental frontiers, I take great pleasure in submitting a proposal for your consideration:

ROTE = Reduction Of Transport Emissions

This initiative presents a novel, simulation-based research framework aimed at significantly reducing PM2.5 levels and achieving an AQI < 100 in a major Indian city such as Chennai. At its core is a two-year computer simulation experiment involving 1,000 vehicles tracked 24x7 via India’s own NaVIC satellite system.

The methodology synthesizes:

· HARM QUOTIENT – Each vehicle’s pollution footprint

· TRANS-SCORE – A behavioral eco-score derived from usage patterns

· TRANS-TAX – A dynamic credit/debit mechanism to incentivize sustainable

choices

Enclosed with this letter is a detailed project brief, which includes:

· Python-based simulation code

· Dynamic visual storyboards ( NaVIC dashboard & behavioral animations )

· A narrative framework suitable for academic research or doctoral investigation

Given your consistent support for student-led solar mobility projects and technology-for-society initiatives at IIT-M, I believe this proposal could be a strong candidate for incubation under either the Computer Science or Civil Engineering departments. It might even evolve into a long-term interdisciplinary doctoral thesis.

I would be deeply honoured if this proposal aligns with your vision for IIT-M’s role in building cleaner, data-driven cities of the future.

Warm regards,

Hemen Parekh
🌐 www.IndiaAGI.ai
📧 hcp@RecruitGuru.com
📞 +91 98675 50808

NaVIC will be watching your Vehicle ( 24x7 ) ... 30 Jan 2024

ROTE Simulation Proposal

Title: ROTE = Reduction of Transport Emissions — A Computer Simulation Experiment

for Chennai

Submitted to : Prof. V. Kamakoti, Director, IIT Madras

Submitted by : Hemen Parekh

PART 1 : Introduction to ROTE Theory

ROTE (Reduction of Transport Emissions) is a research-driven framework that aims to bring down PM2.5 levels and achieve a sustained Air Quality Index (AQI) below 100 in metropolitan areas through real-time data tracking, behavioural feedback, and policy innovation.

Originally conceptualized in a 2018 email to then Union Minister Shri Suresh Prabhu, the ROTE framework is built around three core metrics:
- HARM QUOTIENT — Quantifies an individual vehicle’s pollution footprint
- TRANS-SCORE — An eco-behavioral index reflecting usage patterns and emissions
- TRANS-TAX (TT) — A dynamic system of incentives or penalties based on the TRANS-

SCORE

This proposal outlines a 2-year computer simulation to be conducted for the city of Chennai, tracking 1,000 diverse vehicles using NaVIC satellite-based positioning, smart sensors, and real-time cloud analytics.

PART 2 : Simulation Design

Objective:
To model, monitor, and evaluate how behavior-linked carbon incentives and penalties impact vehicle emissions, using real-time location and usage data.

Scope & Parameters:
- Geography    :   Chennai (urban + peri-urban corridors)
- Duration        :   24 months, divided into 8 quarters (3 months each)
- Sample Size   : 1,000 vehicles across fuel types (Petrol, Diesel, CNG, EV)

Technology Stack:
- Embedded sensors or plug-in IoT smart devices
- Continuous location tracking via NaVIC
- Cloud-based simulation and analytics engine

Assumptions:
- All vehicles are fitted with energy/emission tracking modules
- TRANS-TAX is applied monthly as either debit (penalty) or credit (reward)
- Drivers receive real-time behavioral feedback to nudge eco-conscious choices

PART 3 : Simulation Software Code (Python Snippet)

import random

class Vehicle:
    def __init__(self, vehicle_id, type, base_emission, daily_km):
        self.vehicle_id = vehicle_id
        self.type = type # 'petrol', 'diesel', 'CNG', 'EV'
        self.base_emission = base_emission # grams/km
        self.daily_km = daily_km
        self.harm_quotient = 0
        self.trans_score = 0
        self.trans_tax = 0

    def calculate_harm_quotient(self):
        self.harm_quotient = self.base_emission * self.daily_km * 30 # Monthly footprint

    def calculate_trans_score(self):
        benchmark_emission = 1000 # Target benchmark for best eco-score
        self.trans_score = max(0, 100 - (self.harm_quotient / benchmark_emission))

    def calculate_trans_tax(self):
        if self.trans_score >= 75:
            self.trans_tax = -200 # Carbon Credit
        elif self.trans_score <= 25:
            self.trans_tax = 500   # Carbon Debit
        else:
            self.trans_tax = 0

# Run Simulation
vehicles = [
    Vehicle(i, random.choice(['petrol', 'diesel', 'CNG', 'EV']),
            random.uniform(90, 300), random.randint(10, 50))
    for i in range(1000)
]

for v in vehicles:
    v.calculate_harm_quotient()
    v.calculate_trans_score()
    v.calculate_trans_tax()

average_tt = sum(v.trans_tax for v in vehicles) / len(vehicles)
print("Average Monthly TRANS-TAX:", average_tt)

PART 4 : Visual Storyboards and Dashboard Concepts

A. NaVIC-Enabled Dashboard ( Static + Motion )

• Placeholder: [Insertimage - Dashboard_Monitor_View_Student.png]

A real-time digital interface displaying:
- Chennai city map with live vehicle movements (color-coded: red = high emissions, green = eco-friendly)
- GPS trail data and behavioral tax/reward indicators
- Carbon Credit/Debit logs and alerts
- AQI monitoring dial (goal: AQI < 100)

Prompt for Generation:
"A wide-angle, top-down view of a futuristic dashboard showing a satellite map of Chennai. Small colored vehicles move across roads. Real-time overlay shows blinking tax/rebate icons and AQI gauge. Clean, high-tech UI aesthetic."

B . Vehicle Shift Animation

• Placeholder: [Insert image - EV_Adoption_Storyboard.png]

Animation showing behavior transformation over time:
- Polluting red vehicles (petrol/diesel) fade out from the left
- Clean green EVs fade in from the right

Prompt:
"Side-scroll transition animation showing red cars disappearing and green EVs replacing them. Timeline ticks below, illustrating change over 2 years. Minimalist, infographic-style animation."

C . University Lab Scene

A young PhD researcher observing the live simulation:
- Ambient-lit room with a large wall-mounted screen
- Graphs of HARM QUOTIENT, TRANS-SCORE, TRANS-TAX updating live
- Pop-up: ‘Carbon Credit: ₹200 Credited to Owner’

Prompt:
"Young Indian male PhD student in a dark research lab, watching a large digital dashboard with vehicle animations and carbon credit updates. His expression reflects quiet focus. High-resolution, cinematic tone."