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// THESIS GUIDANCE PORTAL · Engineering

Air Quality Monitoring and Prediction in Kathmandu Valley

Level: Bachelor, MasterDifficulty: Intermediate

1. Introduction & Problem Statement

Overview: Develop an IoT-based air quality monitoring network across Kathmandu Valley with ML-based prediction models. Kathmandu consistently ranks among South Asia's most polluted cities.

Background Context (Nepal): Kathmandu Valley faces severe air pollution — AQI regularly exceeds 200 during dry season. Brick kilns, vehicle emissions, and open burning are major contributors. Real-time monitoring and prediction can support policy interventions.

2. Research Objectives

  • Deploy IoT sensor network across 10 locations in Kathmandu Valley
  • Build real-time dashboard for AQI monitoring
  • Train LSTM/Prophet model for 24-hour AQI prediction
  • Analyze pollution sources using statistical methods
  • Provide policy recommendations based on data

3. Proposed Methodology

  1. Sensor hardware selection and calibration
  2. IoT network setup — LoRaWAN or NB-IoT
  3. Data pipeline — MQTT, time-series database (InfluxDB)
  4. Dashboard development with real-time charts
  5. ML model training for prediction
  6. Statistical analysis of pollution sources

4. Thesis Chapter-by-Chapter Outline

Chapter 1: IntroductionTU/KU standard

Air pollution in Nepal, existing monitoring, research objectives

Chapter 2: Literature ReviewTU/KU standard

IoT in environment monitoring, air quality prediction models, Kathmandu studies

Chapter 3: System DesignTU/KU standard

Sensor network architecture, data pipeline, dashboard design

Chapter 4: ImplementationTU/KU standard

Hardware deployment, software development, ML model

Chapter 5: ResultsTU/KU standard

Data analysis, prediction accuracy, pollution pattern findings

Chapter 6: ConclusionTU/KU standard

Key findings, policy implications, future work

5. Recommended Tools & Technologies

To implement the practical, technical, or analytical portions of this thesis topic, the following software tools, libraries, or APIs are recommended:

Raspberry PiPythonInfluxDBGrafanaTensorFlowMQTTReact

6. Core References & Citations

  • [1]DoEnv Nepal — Air Quality Monitoring Reports
  • [2]WHO Air Quality Guidelines 2021
  • [3]Shrestha, I.L. et al. — Air Quality Studies in Kathmandu Valley
available for workKathmandu, Nepal 🇳🇵contact@sayyedabrarakhtar.com.np