Data Analytics Case Study

Turbidity Analysis App

The Turbidity Analysis App provides a digital solution for monitoring water quality. By converting optical sensor data into clear, actionable metrics, it helps environmentalists and researchers track pollution levels with high precision.

Technology Stack

PythonData Analysis

System Architecture

Data Processing

Python script for signal processing and calibration.

UI

Lightweight interface for real-time monitoring.

Storage

CSV-based logging for long-term data tracking.

The Challenges

Calibrating sensor readings to match laboratory standards.

Handling noisy data from low-cost optical sensors.

Designing an interface for non-technical field workers.

The Solutions

Developed a multi-point calibration algorithm to improve sensor accuracy by 15%.

Applied a moving-average filter to smooth out sensor jitter.

Created a simplified 'Traffic Light' status indicator (Safe/Caution/Hazard).

Key Results & Metrics

01

Automated data analysis

02

Environmental monitoring

03

Precision readings