Air Pollution Prediction Presentation & Thesis -- 2
Publicada el 2026-07-27
Descripción de la oferta
Project Title Spatial Analysis and Machine Learning-Based Air Pollution Prediction in Bihar Using Land Use Regression (LUR), GIS, Remote Sensing, Kriging, and Machine Learning Project Overview I have completed a B.Tech major project on air pollution prediction in Bihar. Most of the technical work has already been completed. I have all the required outputs, maps, figures, tables, graphs, machine learning results, and ArcGIS outputs. I need a professional PowerPoint presentation and a thesis report prepared using my existing work. --- Work Already Completed 1. Data Collection Landsat 8/9 satellite imagery downloaded from USGS Earth Explorer (2023–2025) CPCB air quality monitoring data Bihar administrative boundary Meteorological variables (Temperature and Relative Humidity) 2. GIS & Remote Sensing (ArcGIS) Area of Interest (AOI) creation Image mosaicking Image projection Raster clipping False Colour Composite (Band 5-4-3) Training sample collection Maximum Likelihood Classification (MLC) LULC map generation for 2023, 2024, and 2025 Fishnet generation (5 km × 5 km) Tabulate Area analysis Spatial Join Final LUR dataset preparation 3. Python Analysis Data preprocessing Exploratory Data Analysis (EDA) Descriptive statistics Histograms Boxplots Scatter plots Correlation matrix Correlation heatmap 4. Land Use Regression (LUR) Predictor variable preparation Response variable preparation Linear regression modelling Model evaluation 5. Machine Learning Models The following models have already been implemented: Linear Regression Decision Tree Random Forest Gradient Boosting Support Vector Regression (SVR) Available results include: R² RMSE MAE Model comparison tables Feature importance Individual pollutant results 6. Kriging Ordinary Kriging Semivariogram Nugget Range Sill Spatial interpolation maps 7. Future Prediction Future pollutant prediction maps Future prediction tables Model outputs --- Files Available I will provide: Existing PowerPoint presentation (~70 slides) ArcGIS screenshots USGS screenshots LULC maps Fishnet maps Tabulate Area outputs Spatial Join outputs LUR outputs Machine learning results Feature importance figures Kriging outputs Prediction maps Thesis draft documents Supporting ZIP files --- Task 1 – PowerPoint Presentation Update my existing PowerPoint only. Do NOT: Create a new presentation. Change the slide order. Change the theme. Change fonts. Change colours. Change layouts. Remove existing images. Required Work For every image, map, graph, screenshot, or table: Add concise technical content. Add Objective. Add Description. Add Key Observations. Add Significance. Add Figure Caption. If supporting documents contain explanations, use them after rewriting into presentation language. If no explanation exists, generate technically correct content matching the figure. Maintain a professional IIT/NIT seminar presentation style. --- Task 2 – Thesis Report Prepare a complete thesis using my project work. Include: Chapter 1 Introduction Problem Statement Research Gap Objectives Chapter 2 Literature Review Chapter 3 Study Area Dataset Methodology Chapter 4 LULC Analysis Fishnet Tabulate Area Spatial Join LUR Dataset Chapter 5 Exploratory Data Analysis Correlation Analysis Regression Analysis Chapter 6 Machine Learning Models Individual Model Results Feature Importance Model Comparison Chapter 7 Kriging Semivariogram Spatial Prediction Chapter 8 Future Prediction Discussion Conclusion Future Scope --- Writing Requirements Original content (no plagiarism) Technical and academic language Suitable for a B.Tech thesis Consistent formatting Proper figure captions Proper table captions Cross-references to figures and tables Logical flow between sections --- Expected Deliverables 1. Updated editable PowerPoint (.pptx) with all existing figures retained and completed technical content. 2. Complete thesis report (.docx) based entirely on my project. 3. Figure captions and table captions throughout. 4. Presentation and thesis aligned so that the same technical interpretations are used consistently. Note: The research work, maps, models, and outputs are already completed. The task is to transform the existing material into a polished presentation and thesis without altering the technical workflow or results.
Skills
Fuente original: freelancer