Create collected_data_sample.md

README.md

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-# Mars Rover Navigation Optimization System 🛰
+# Rover Navigation Optimization System (R-NOS) 🛰
 
-The Mars Rover Navigation Optimization System is a passion project by [Tejas Gupta](https://github.com/multiverseweb) and [Ojas Gupta](https://github.com/ojas-git). This system is designed for indoor environments, focusing on data mining and analysis rather than mobility. Obstacles will be placed to test its functionality while gathering and processing key environmental data like temperature and humidity.
+The Rover Navigation Optimization System is a project by **[Tejas Gupta](https://github.com/multiverseweb)** and **[Ojas Gupta](https://github.com/ojas-git)** developed under the guidance of **`Prof. Bindu Garg`**, HOD, CSE & CSBS, Bharati Vidyapeeth University, College of Engineering, Pune. It is a scaled-down prototype designed to explore real-time environmental monitoring and data-driven decision-making. The project focuses on collecting temperature and humidity readings to analyze climate conditions and detect anomalies that could impact autonomous navigation.
 
-## Objectives
+![Visitors](https://api.visitorbadge.io/api/visitors?path=multiverseweb2%2rover%20&countColor=%23263759&style=flat&initial=5767)
+  ![License](https://img.shields.io/badge/License-CC%20BY%204.0-4e3eb5)
+  ![Languages](https://img.shields.io/github/languages/count/multiverseweb/rover?color=20B2AA)
+  ![GitHub contributors](https://img.shields.io/github/contributors/multiverseweb/rover)
+  ![GitHub last commit](https://img.shields.io/github/last-commit/multiverseweb/rover)
+  ![GitHub repo size](https://img.shields.io/github/repo-size/multiverseweb/rover)
+  ![GitHub total lines](https://sloc.xyz/github/multiverseweb/rover)
+  ![GitHub Repo stars](https://img.shields.io/github/stars/multiverseweb/rover)
 
+#### Table of Contents
+| [Research Hypothesis](#research-hypothesis) | [Objective](#objective) | [Components](#components) | [Circuit](#circuit) | [Snapshots](#project-snapshots) | [Dataset](#dataset) | [ThingSpeak](#data-visualised-on-thingspeak) | [License](#license) |
+|-|-|-|-|-|-|-|-|
+
+## Research Hypothesis
+A scaled-down Rover prototype can effectively collect temperature and humidity data, demonstrating how real-time environmental monitoring can be used for autonomous navigation, climate analysis, and anomaly detection.  
+
+By analyzing the collected data, we aim to identify trends, evaluate sensor accuracy, and explore potential improvements in robotic exploration. This includes assessing response time, consistency, and anomalies caused by external factors like human interference or sudden environmental changes.  
+
+## Objective
+- To explore potential improvements in robotic exploration through data-driven insights.
 - Collect and transmit thermal data wirelessly to a computer.
 - Detect obstacles using ultrasonic sensors.
 - Indicate path changes via buzzer and LED.
@@ -21,13 +39,62 @@ The Mars Rover Navigation Optimization System is a passion project by [Tejas Gup
 | Display | OLED Display (0.96" or 1.3", SSD1306/SH1106, I2C/SPI) |
 | Data Handling | Data will be transmitted and analyzed using ThingSpeak. The Arduino API will be used for interfacing and control. |
 
-## Future Enhancements
+## Circuit
 
-- Implementing autonomous navigation.
-- Adding more sensors for enhanced environmental data collection.
-- Visualizing data with advanced analytics and machine learning.
+| ![](https://github.com/multiverseweb/rover/blob/main/images/rover.png?raw=true) |
+|-|
 
-## License
+## Project Snapshots
+
+| ![](https://github.com/multiverseweb/rover/blob/main/images/breadBoard.jpg?raw=true) |
+|-|
+
+## Environmental Sensor Readings from Rover Prototype
+
+## Dataset
+|<a href="https://github.com/multiverseweb/rover/blob/main/data/data_3hrs.csv"><img src="https://img.shields.io/badge/GitHub-181717.svg?style=flat&logo=GitHub&logoColor=white"></a> | <a href="https://www.kaggle.com/datasets/tejasgupta7/sensor-based-data-temperature-and-humidity"><img src="https://img.shields.io/badge/Kaggle-20BEFF.svg?style=flat&logo=Kaggle&logoColor=white"></a> | <a href="https://data.mendeley.com/datasets/pdsjz2wjw7/1"><img src="https://img.shields.io/badge/Mendeley-9D1620.svg?style=flat&logo=Mendeley&logoColor=white"></a> |
+|-|-|-|
+
+### What the Data Shows
+This dataset contains `5,400` timestamped temperature and humidity readings collected over a period of `3` hours and logged every `2` seconds by the rover’s onboard DHT22 sensor. The data highlights:
+- Gradual fluctuations in environmental conditions.
+- Notable temperature spikes ``(~10°C)`` introduced using a lighter to test sensor response.
+- Stable humidity levels with minor deviations due to air circulation or sensor drift.
+
+### Notable Findings
+- **Controlled Temperature Spikes:** Short bursts of heat resulted in clear temperature increases `(~10°C)`, demonstrating the sensor's ability to detect and log transient changes.
+- **Humidity Stability:** Humidity levels remained within a narrow range, confirming minimal impact from applied temperature fluctuations.
+- **Gradual Environmental Variations:** Small temperature and humidity shifts were observed, likely due to ambient conditions and ventilation effects.
 
-This project is open-source under the MIT License.
+### How the Data Was Gathered
+- **Sensor Used:** DHT22 (for temperature & humidity).
+- **Data Collection Frequency:** Logged every few seconds.
+- **Controlled Testing:** Heat spikes added using a lighter to simulate external interference.
+- **Data Transmission:** Logged in real-time via wireless communication to a laptop.
+
+### Data Visualised on ThingSpeak
+
+| ![](https://github.com/multiverseweb/rover/blob/main/images/thingspeak.png?raw=true) |
+|-|
+
+| [View Live](https://thingspeak.mathworks.com/channels/2890599) |
+|-|
+
+### How to Interpret and Use the Data
+- **Identify Trends:** Observe temperature and humidity variations over time.
+- **Detect Anomalies:** Locate sharp temperature spikes (`~10°C` increases) caused by external heating.
+- **Compare Sensor Performance:** Evaluate how quickly temperature normalizes after a spike.
+- **Develop Predictive Models:** Train machine learning models to predict environmental changes.
+
+| View [code/data_analysis.ipynb](code/data_analysis.ipynb) for more |
+|-|
+
+### Potential Applications
+- **Autonomous Environment Monitoring:** Detecting and responding to environmental anomalies.
+- **Sensor Calibration & Validation:** Testing DHT22 sensor accuracy under different conditions.
+- **Climate Simulation & Research:** Indoor climate modeling & environmental trend analysis.
+- **Robotics & AI:** Training AI for automated responses to climate fluctuations.
+
+## License
 
+This project is open-source under the [CC BY 4.0](https://github.com/multiverseweb/rover/blob/main/LICENSE.md).

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