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Vehicle Survey and Service Record is an innovative project designed to streamline the way we manage vehicle maintenance and gather crucial survey data. This comprehensive platform enables users to keep meticulous records of vehicle service histories, ensuring that all necessary maintenance actions are performed timely and efficiently. By consolidating data on various vehicle parameters, including usage patterns, fuel efficiency, and mechanical performance, this tool empowers users to make informed decisions about vehicle management.

The project encompasses a user-friendly interface that facilitates easy entry and retrieval of service data. It features automated reminders for upcoming services, a robust search functionality for past records, and detailed report generation capabilities. Furthermore, the platform includes a survey module that collects user feedback on vehicle performance and service satisfaction, providing valuable insights to business owners and fleet managers.

Not only does this project aim to enhance vehicle longevity and reliability, but it also seeks to reduce operational costs by preventing unplanned maintenance and improving overall service quality. Whether for individual car owners, automotive service stations, or fleet management companies, Vehicle Survey and Service Record serves as an essential tool for achieving optimal vehicle performance and customer satisfaction.

Created UI for Home page

## Abstract

The "Vehicle Survey and Service Record" project presents a revolutionary approach to managing vehicle maintenance and collecting essential survey data. Designed as a comprehensive platform, this project facilitates the meticulous recording of vehicle service histories, automated service reminders, and detailed reporting capabilities. With user-friendly features aimed at enhancing vehicle reliability, reducing operational costs, and optimizing customer satisfaction, this project serves as a crucial tool for both individual vehicle owners and fleet management professionals.

## Introduction

In today's fast-paced world, effective vehicle management plays a vital role in different domains, from personal usage to fleet operations. As the vehicle population increases, so does the complexity of maintenance management. Traditional methods of tracking vehicle services are often cumbersome, leading to data oversights and inefficient operation. The Vehicle Survey and Service Record project aims to revolutionize this landscape through an integrated platform that streamlines vehicle maintenance and enhances service delivery through valuable data collection.

## Objectives

The primary objectives of the Vehicle Survey and Service Record project are:

* To develop a user-friendly system for maintaining and retrieving vehicle service records.
* To automate reminders for routine maintenance to ensure timely service.
* To integrate a survey module that collects feedback on vehicle performance and service satisfaction.
* To analyze data concerning usage patterns, mechanical performance, and fuel efficiency to aid in better decision-making.
* To reduce operational costs through preventative maintenance strategies and increased service quality.

## Features of the Project

The project encompasses a variety of features designed to enhance the user experience and improve vehicle management efficiency. Some of the key features include:

* **Data Collection Module**: Facilitates the gathering of essential vehicle data for analysis.
* **On-board Diagnostics Module**: Integrates vehicle diagnostic tools to monitor vehicle performance metrics.
* **Flutter-Based Mobile App**: Provides a seamless mobile interface for users to manage their vehicle records.
* **User Management System**: Allows for service centers to register and manage their clients efficiently.
* **API Development for Data Handling**: Ensures data can be processed and transmitted securely to the server.
* **Service Record Management System**: A systematic approach to keeping track of service history.
* **Secure Login and Vehicle Registration**: Ensures that users can access their data securely.
* **Data Visualization for Vehicle Status**: Provides graphical representations of vehicle performance metrics.
* **Service Completion and Maps Status**: Integrates geographic data to provide additional context for service points.

## Final Outputs

The final outputs of the project include:

* Hardware
* Mobile App
* 3D Design and CAD File
* Complete Codebase

## Components Used

The following components were utilized in the development of the project:

| Image                                                                                                                                                                                                                                      | Component Name                                 | Quantity | Price (₹) |
| ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | ---------------------------------------------- | -------- | --------- |
| <img height="109" width="109" alt="ESP32 DevKit" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2FQRX42DFHu2kKWLoewGf3%2Fimage_0?alt=media&token=d74c9129-b069-472a-a473-1fe1c9d2ee80" />             | ESP32 DevKit                                   | 1 pcs    | ₹340      |
| <img height="124" width="124" alt="GPS GLONASS Antenna" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2FXemusG1Kc5O8BY5mSqQv%2Fimage_0?alt=media&token=802d491e-b18f-4e0c-b2f2-b7a5ded4c4d3" />      | GPS GLONASS Antenna Module Beitian Dual BN-220 | 1 pcs    | ₹1710     |
| <img height="112" width="112" alt="MPU6050 Sensor" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2FYPezcZTMB4oiHKIxCobQ%2Fimage_0?alt=media&token=5fd959d0-ea03-492a-b4c6-40a1c44144d6" />           | MPU6050 Accelerometer & Gyro Sensor            | 1 pcs    | ₹113      |
| <img height="88" width="133" alt="360 Degree Rotary Encoder" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2FEhT8KpQWVKOnG8tNMqfS%2Fimage_0?alt=media&token=0bd867e7-e7d3-4550-b030-85f3e5a8bdd3" /> | 360 Degree Rotary Encoder Module               | 1 pcs    | ₹900      |
| <img height="119" width="119" alt="Rocker Switch" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2FNWrWMg4ZfkRpHdhrMdyF%2Fimage_0?alt=media&token=c138b613-981d-47ae-a5df-7dc156e7aab4" />            | 6A 250V AC DPST ON-OFF Red Round Rocker Switch | 1 pcs    | ₹80       |
| <img height="136" width="136" alt="Li-ion Battery" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2F4o6oTiYmefVOmJ1P64yb%2Fimage_0?alt=media&token=8432a839-fb67-4234-bbc6-c1d97ff0c72f" />           | 3.6V 2600mAh 2C Li-ion Battery                 | 1 pcs    | ₹305      |
| <img height="138" width="138" alt="Printing Service" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2F6e0Imq6gRpEyts0O0mlw%2Fimage_0?alt=media&token=a5967fcf-f856-4203-9caf-04c41440afb9" />         | FDM 3D Printing Service                        | 150 gm   | ₹5        |

## Innovativeness and Social Relevance

The innovative aspect of the Vehicle Survey and Service Record project lies in its comprehensive approach to vehicle management. By integrating various technical components—such as GPS tracking, onboard diagnostics, and user feedback mechanisms—into a singular platform, the project bridges a significant gap in existing vehicle maintenance solutions.

The project's relevance extends to both individual car owners and businesses managing fleets. For car owners, it provides an intuitive mechanism to ensure vehicles remain in top condition, thereby enhancing personal safety and investment longevity. Fleet managers benefit from cohesive data, facilitating better resource allocation, improved operational efficiency, and ultimately resulting in significant cost savings.

Moreover, the collection of survey data offers insights into customer satisfaction and vehicle performance, potentially leading to enhancements in service offerings and overall industry standards.

## Conclusion

The Vehicle Survey and Service Record project stands at the intersection of technology and vehicle management, providing an innovative solution that satisfies both user needs and operational efficiency. With its focus on collecting and analyzing vehicle service data, it aims to transform how vehicle maintenance is approached. The project not only showcases the potential of integrated technologies in enhancing vehicle reliability and safety but also emphasizes its social relevance in the context of societal transportation needs and fleet management practices.

Through comprehensive features, user-centric design, and systematic data handling capabilities, this project embodies a forward-thinking approach that promises substantial benefits for a wide range of stakeholders in the automotive ecosystem.

## Project Overview

The **Vehicle Survey and Service Record** is a pioneering initiative aimed at enhancing vehicle management through comprehensive tracking of maintenance and survey data. This project focuses on ensuring meticulous documentation of service histories, optimizing maintenance schedules, and providing valuable insights into vehicle performance. The raised platform ultimately aims at improving vehicle longevity and reliability while minimizing operational costs for car owners, service stations, and fleet management companies.

## Development Phases and Updates

### Phase 1: Circuit Design and Initial Setup

#### Circuit Diagram Creation

A pivotal advancement in the **Vehicle Survey and Service Record** project commenced with the successful development of the circuit diagram. This diagram encompasses all essential hardware components, providing a comprehensive guide for assembling the device.

<img height="335" width="530" alt="Circuit Diagram" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/projects%2Fvehicle-survey-and-service-record%2Fupdates%2F8J3rPs0QRLFlStoY868U%2Fimage_0?alt=media&token=ccb31d6e-4ad7-484b-b872-8d9dc9fbaac7" />

**Key Components**:

* **ESP32 DevKit**: The central microcontroller managing communications and processing data.
* **GPS GLONASS Antenna Module**: Utilized for real-time location tracking, thereby enhancing service data collection.
* **MPU6050 Accelerometer & Gyro Sensor**: Provides essential data regarding vehicle movement and orientation.
* **3.6V 2600mAh Li-ion Battery**: Ensures reliable operation by powering the entire assembly.
* **360 Degree Rotary Encoder Module**: Facilitates the tracking of rotational movements, contributing to detailed vehicle dynamics.

### Phase 2: Hardware Integration

#### Assembling the MPU6050 and BN-220 GPS Module

Following the establishment of the circuit diagram, substantial progress was made with the assembly of the **Data Collection Module**, integrating the **MPU6050 Accelerometer & Gyro Sensor** and the **Beitian Dual BN-220 GPS**.

<img height="638" width="479" alt="Integrated Modules" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/projects%2Fvehicle-survey-and-service-record%2Fupdates%2FaznmJyuKDshE049XLRTp%2Fimage_0?alt=media&token=47fda720-15b8-4dbb-9574-324cbb87be1c" />

**Details**:

* The module facilitates precise data collection on vehicle movement and status, aiding in the understanding of usage patterns.
* Initial functionality tests yielded promising results, with accurate data transmission.

### Phase 3: Input/Output Modules

#### Rotary Control Module for Distance Measurement

To accurately capture distances traveled by the vehicles, a **Rotary Control Module** was integrated into the system.

<img height="431" width="575" alt="Rotary Control Module" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/projects%2Fvehicle-survey-and-service-record%2Fupdates%2FJwBSzj0pG4Avux4eQ55D%2Fimage_0?alt=media&token=64221af3-1562-4565-a453-c123afea5149" />

**Key Highlights**:

* Incorporation of the **360 Degree Rotary Encoder Module** allows for precise distance calculations.
* The module is linked with the ESP32 DevKit for real-time processing of rotary encoder signals.

### Phase 4: Software Integration

#### Complete Data Readings Page

A significant improvement was made by introducing a new page designed to provide users with comprehensive data readings gathered from various modules and sensors.

<img height="579" width="260" alt="Data Reading Page" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/projects%2Fvehicle-survey-and-service-record%2Fupdates%2FJCJ7TrGJeN1efIL9npc4%2Fimage_0?alt=media&token=5c2978df-8391-4edf-bc41-8b2998789f99" />

**Features**:

* Access to vehicle performance, diagnostics, and service records consolidated in one centralized location, improving user experience and tracking capabilities.

### Phase 5: Mobile Application Development

#### Creation of Flutter-Based Mobile Application

The development team successfully created the **UI for the mobile app**, which is designed to enhance user engagement and management flexibility.

<img height="622" width="280" alt="Mobile App UI" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/projects%2Fvehicle-survey-and-service-record%2Fupdates%2F1W9P3LfRohmh1oxODqgG%2Fimage_0?alt=media&token=f515451f-beb7-469f-9ef3-7211ef9ab4a7" />

**Key Features Implemented**:

* **Secure Login**: Ensures user data is protected and only accessible to authorized personnel.
* **Vehicle Registration & Management**: Users can easily manage their vehicles with a few taps.
* **Real-Time Data Integration**: The app is seamlessly connected to Firebase Real Time Database for immediate updates on vehicle service records.

### Phase 6: Service Completion and Mapping Integration

#### Service Completion and Maps Integration

Further advancements were accomplished with the incorporation of service completion tracking alongside a maps integration feature.

<img height="299" width="400" alt="Maps Integration Feature" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/projects%2Fvehicle-survey-and-service-record%2Fupdates%2FpSOCrleOBuXayl3mR3zf%2Fimage_0?alt=media&token=dc5424ac-7620-4f15-a232-3f41fe48c79e" />

**Details**:

* Users can now log service statuses directly within the app, ensuring that all actions are documented accurately.
* The map feature aids users in navigating service centers efficiently.

### Future Plans

As we progress towards completing the **Vehicle Survey and Service Record** platform, the upcoming steps include:

1. **Refining Functionalities**: Integration of user feedback to enhance the hardware and software aspects of the platform.
2. **Extensive Testing**: Continuous testing of both software and hardware components for reliability and performance.
3. **Launch Preparations**: Concluding development to facilitate a successful launch, ensuring users can benefit from a fully functional vehicle management system.

## Conclusion

The **Vehicle Survey and Service Record** project showcases significant advancements in vehicle maintenance technology. Through the integration of various hardware and software components, the project sets the foundation for enhancing vehicle management, thereby contributing to improved operational efficiency for users. Continuing community feedback and rigorous testing will guide the successful implementation of this innovative platform, ultimately serving as a critical tool for vehicle owners and fleet managers alike.

We are excited about the prospect of rolling out a sophisticated vehicle survey and service record management system and will continue to provide updates throughout the development process. Thank you for your ongoing support and enthusiasm for this project.

Vehicle Survey and Service Record is an innovative platform designed to optimize vehicle maintenance management and collect essential survey data to improve performance and service quality.

Vehicle Survey and Service Record

Fully autonomous floating waste collection robot detects waste using yolo and robot automatically navigate towards the waste and collect it using a conveyor belt. 

The object detection using yolo is not precise it isnt getting fully captured all the time using our webcam feed.so we have to  look into the object detection. The motor controlling works in such a way that if the detected waste is in the left it moves left with a delay and checks again for the detected waste if it's in the center
. it uses  a raspberry pi 400 for processing and has a basic webcam .the feed is getting lag i dont knw it is beause of the camera or the raspberry pi. We have made a rc car model of the project and it should collect the waste using conveyor belt. And we need the full project before 26th. 

Circuit diagram of the project

A fully autonomous floating waste collection robot that uses YOLO for waste detection and a conveyor belt for collection, powered by a Raspberry Pi 400 and a basic webcam, with ongoing improvements in object detection and motor control.

Fully autonomous waste collection robot

Suspicious Activity Detection in Protected Areas using Image Processing is a groundbreaking project designed to mitigate unauthorized and potentially harmful activities in forests and other safeguarded regions. This innovative solution leverages advanced image processing techniques to monitor and analyze real-time footage, detecting unusual human behaviours indicative of suspicious activity. Key indicators such as running, face coverings, carrying foreign objects, and other atypical actions are meticulously identified to trigger timely alerts. The system aims to provide a robust defence mechanism that enhances the security and preservation of protected areas by enabling rapid response to threats. Through continuous monitoring and sophisticated analysis, this project aspires to safeguard biodiversity and maintain ecological balance, thereby ensuring the sanctity of our natural and protected environments.

# Suspicious Activity Detection in Protected Areas Using Image Processing

## Abstract

The project "Suspicious Activity Detection in Protected Areas Using Image Processing" aims to harness the power of advanced image processing techniques to monitor protected regions, specifically forests. Through continuous surveillance and analysis of real-time footage, the project aspires to detect unusual human behavior that may indicate unauthorized or harmful activities. This marks a significant step towards enhancing the security of biodiversity and preventing ecological degradation. The solution meticulously identifies key indicators of suspicious behavior such as running, face coverings, and the carrying of foreign objects to trigger timely alerts for relevant authorities.

## Introduction

Protected areas, including forests and wildlife reserves, are essential for safeguarding biodiversity and maintaining ecological balance. However, these regions often face threats from unauthorized activities such as poaching, deforestation, and illegal gatherings. Traditional surveillance methods are often inadequate due to their reliance on human monitoring, which can be inconsistent and prone to error. To address these challenges, the project utilizes cutting-edge image processing technologies to create a robust monitoring solution that enables real-time detection of suspicious activities in protected areas.

Image processing refers to the technique of using algorithms to enhance and analyze images. By employing machine learning tools and custom algorithms, the project seeks to provide a proactive approach to forest surveillance, contributing to better conservation efforts and security measures. By acting on alerts generated by the system, authorities can respond more effectively to threats, thereby protecting these vital environments for future generations.

## Objectives

1. Develop a real-time monitoring system capable of identifying suspicious activities in protected areas through image processing techniques.
2. Trigger timely alerts based on the detection of specific human behaviors that deviate from regular patterns.
3. Enable efficient management of resources by reducing the need for constant human surveillance.
4. Create a user-friendly mobile application that allows easy access to surveillance data and alert notifications.
5. Foster collaboration between conservation groups and technological innovators to enhance forest protection strategies.

## Features of the Project

* **Flutter App Interface Development**: Creation of a mobile application for user interaction, alerts, and data visualization.
* **Basic Image Labeling, Text, and Person Detection**: The system uses foundational image processing functions to identify and label objects within the monitoring area.
* **Google ML Kit Image Processing**: Integration of Google's machine learning kit for advanced image processing capabilities to enhance detection accuracy.
* **ESP32 Circuit Build**: Construction of the electronic circuitry required for image capture and video processing.
* **Fusion360 for Designing Enclosure**: Utilizing CAD software for designing the enclosure that houses the electronic components.
* **Image Capture Unit**: A specialized unit responsible for capturing images and video footage from the monitored areas.
* **Power Supply Unit**: Ensures a reliable power source for the entire monitoring system.
* **Connectivity Module**: Facilitates data transfer between the camera and the monitoring application.
* **ESP32 CAM Wireless Image Transfer**: Enabling seamless and wireless transmission of captured footage.
* **Integration of Hardware and Software**: Combining all components into a cohesive system for effective operational functionality.
* **TensorFlow for Image Processing and Suspicious Activity Detection**: Employing TensorFlow frameworks to design and train machine learning models focused on detecting unusual human behaviors.

## Final Outputs

The project aims to deliver several key outputs that encapsulate various aspects of its implementation:

* Hardware
* Mobile App
* Complete codebase
* 3D design and CAD file

## Components Used

The following components and materials were utilized in the project:

| Image                                                                                                                                                                                                                                                     | Component Name                                     | Quantity | Price (₹) |
| --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------- | -------- | --------- |
| <img height="121" width="121" alt="ESP32 CAM Camera Module" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2FGNgMBo8fq2aS9DdvWeAn%2Fimage_0?alt=media&token=1c1e9bfe-2d51-44fc-ab6a-b635f283fb84" />                 | ESP32 CAM Camera Module                            | 1        | 499       |
| <img height="133" width="133" alt="TP4056 1A Li-Ion Battery Charging Board" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2F5UxzRWIgW1JSPnfRFbaR%2Fimage_0?alt=media&token=05e52db9-5710-4282-a6bb-a7d174e6d3e7" /> | TP4056 1A Li-Ion Battery Charging Board            | 1        | 19        |
| <img height="130" width="130" alt="Rechargeable LiPo Battery" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2FsRDs0MJzy2TUkTHEGneN%2Fimage_0?alt=media&token=13e459f4-d462-437c-ab5d-4ba573889c68" />               | 950 mAh 3.7V single cell Rechargeable LiPo Battery | 1        | 350       |
| <img height="138" width="138" alt="FTDL Mini USB to TTL Serial Converter" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2FmNaLkf6yR2yfVJCXKyGT%2Fimage_0?alt=media&token=44d96d0d-59d1-483b-97fd-b30065dbc354" />   | FT23RL FTDL Mini USB to TTL Serial Converter       | 1        | 362       |
| <img height="131" width="131" alt="FDM 3D Printing Service" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2F6e0Imq6gRpEyts0O0mlw%2Fimage_0?alt=media&token=a5967fcf-f856-4203-9caf-04c41440afb9" />                 | FDM 3D Printing Service                            | 200 gm   | 5         |
| <img height="100" width="100" alt="Red Round Rocker Switch" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2FNWrWMg4ZfkRpHdhrMdyF%2Fimage_0?alt=media&token=c138b613-981d-47ae-a5df-7dc156e7aab4" />                 | 6A 250V AC DPST ON-OFF Red Round Rocker Switch     | 1        | 80        |

## Innovativeness and Social Relevance

The use of image processing technology in environmental conservation reflects a novel approach to safeguarding natural resources. By employing machine learning and image analysis, this project creates a proactive solution to monitor and protect sensitive ecosystems from human intrusions. The project holds significant social relevance as it contributes to the global initiative of preserving biodiversity and mitigating negative anthropogenic effects on environments.

Furthermore, the ability to detect suspicious activities in real-time may deter potential violators from entering protected areas, thus bolstering conservation efforts. This kind of technological innovation not only enhances wildlife security but also paves the way for various applications in environmental management, wildlife protection, and sustainable development.

## Conclusion

The "Suspicious Activity Detection in Protected Areas Using Image Processing" project stands at the intersection of technology and environmental conservation. By implementing advanced image processing techniques, this initiative promises to revolutionize the monitoring of protected areas, enabling authorities to respond swiftly to potential threats.

Through its comprehensive approach to detecting unusual behavior and providing alert notifications, the project embodies a significant step forward in safeguarding biodiversity while promoting ecological health. The holistic integration of hardware and software components ensures that the system operates efficiently and effectively. It is clear that projects like this are imperative in the ongoing fight to preserve our natural landscapes for future generations.

## Development Phases and Updates

### Phase 1: Initial Setup and Hardware Procurement

**Date:** April 5, 2024
**Update:** Hardware parts purchased
The project began with the acquisition of essential components for the development of the suspicious activity detection system. The parts purchased included:

* **ESP32 CAM Module**
* **TP4056 1A Li-Ion Battery Charging Board with 5V booster**
* **1000 mAh 3.7V Rechargeable LiPo Battery**
* **Perfboard**
* **Female header pins**
* **USB to UART convertor**

<img height="472" width="630" alt="Hardware Parts Purchased" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/projects%2Fsuspicious-activity-detection-in-forest-or-other-protected-areas-using-image-processing%2Fupdates%2FSwduiFExaW9IoVJfTqbU%2Fimage_0?alt=media&token=0746e924-fb05-4448-ae06-7e76c9229acd" />

The procurement of these parts was crucial for building a functional prototype capable of detecting suspicious activities.

### Phase 2: Design and Testing of Hardware Components

**Date:** April 15, 2024
**Update:** Hardware enclosure designed

With all necessary components secured, the team moved forward with designing the hardware enclosure. Utilizing Fusion360 software, the team designed an enclosure meant to house the components securely. This design ensures that the unit is weather-proof and suitable for outdoor installation.

Online view of the design: [Fusion360 Enclosure Design](https://a360.co/4aBab67)

<img height="440" width="467" alt="Hardware Enclosure Designed" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/projects%2Fsuspicious-activity-detection-in-forest-or-other-protected-areas-using-image-processing%2Fupdates%2FMqLJMeWJZCzUWv3PGjyY%2Fimage_0?alt=media&token=d7e1978d-8e89-4dda-bbb2-e5fd5ae768fe" />

### Phase 3: Integration Testing of Circuits

**Date:** April 15, 2024
**Update:** ESP32 Circuit Testing and Integration
Following the design phase, the ESP32 circuit underwent rigorous testing for functional performance across various scenarios. The integration of the ESP32 circuit is essential as it forms the brain of the image processing system.

<img height="525" width="701" alt="ESP32 Circuit Testing" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/projects%2Fsuspicious-activity-detection-in-forest-or-other-protected-areas-using-image-processing%2Fupdates%2FL8iN8KxRWoMZ4ExVAvah%2Fimage_0?alt=media&token=5d6c86d5-49a4-418d-8770-b5af2218ae6f" />

<img height="528" width="704" alt="ESP32 Circuit Testing" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/projects%2Fsuspicious-activity-detection-in-forest-or-other-protected-areas-using-image-processing%2Fupdates%2FL8iN8KxRWoMZ4ExVAvah%2Fimage_1?alt=media&token=ce949df9-a622-4df6-90be-2f3157242b96" />

### Phase 4: Software Development and Integration

**Date:** April 9, 2024
**Update:** Developed Home screen view with InApp, Hardware, FaceTrain, text
In parallel with hardware development, the software development team focused on the core functionality of the app, including the Home screen view. This interface integrates capabilities related to in-app processing, hardware integration, and facial recognition technologies.

### Features Implemented:

* Integration of Flutter App Interface for the Home screen.
* Basic image labeling and text detection functionalities.
* Hardware components such as ESP32 CAM, Li-Ion Battery Charging Board, and Rechargeable Battery were integrated.
* FaceTrain technology employed for improved facial detection.

<img height="372" width="710" alt="Home Screen Development" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/projects%2Fsuspicious-activity-detection-in-forest-or-other-protected-areas-using-image-processing%2Fupdates%2Fr3RuwquZfpuMP1BDppIM%2Fimage_0?alt=media&token=dd2b6a6f-39e7-471e-89e8-c87432ff5e83" />

<img height="372" width="173" alt="Home Screen Development" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/projects%2Fsuspicious-activity-detection-in-forest-or-other-protected-areas-using-image-processing%2Fupdates%2Fr3RuwquZfpuMP1BDppIM%2Fimage_1?alt=media&token=571ea039-b0ef-4e4a-b461-b3c192cc6036" />

### Phase 5: Wireless Image Transfer Implementation

**Date:** April 16, 2024
**Update:** Wireless Image Transfer Completed
The project team successfully integrated the ESP32 CAM wireless image transfer functionality, which allows captured images to be transmitted wirelessly for further processing. This step significantly boosts the system's performance in real-time monitoring.

<img height="399" width="533" alt="Wireless Image Transfer Completed" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/projects%2Fsuspicious-activity-detection-in-forest-or-other-protected-areas-using-image-processing%2Fupdates%2FmFPFi0aBJIKZMlV3rL7C%2Fimage_0?alt=media&token=afa8ae59-bf52-4f65-8b23-49c23f8b7c9a" />

### Phase 6: TensorFlow Integration for Enhanced Detection

**Date:** April 16, 2024
**Update:** TensorFlow for Image Processing Added
The integration of TensorFlow into the project was a critical enhancement, enabling improved image processing and abnormal behavior detection capabilities.

### Features Implemented:

* Deployment of TensorFlow for processing captured images.
* Enhanced image analysis and suspicious activity detection accuracy.

<img height="513" width="231" alt="TensorFlow Integration" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/projects%2Fsuspicious-activity-detection-in-forest-or-other-protected-areas-using-image-processing%2Fupdates%2FIeubVkQOGp5Pc47u0PEr%2Fimage_0?alt=media&token=ff874d84-d9da-4e05-bfd4-b3df2ce03c9a" />

### Phase 7: Testing of Live Web Server and Final Adjustments

**Date:** April 15, 2024
**Update:** Tested Basic Wireless Live Web Server Setup
The team tested the basic setup of a wireless live web server, focusing on its functionality and reliability in transmitting real-time images captured by the ESP32 CAM module.

<img height="519" width="693" alt="Wireless Live Web Server Setup" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/projects%2Fsuspicious-activity-detection-in-forest-or-other-protected-areas-using-image-processing%2Fupdates%2F48mnzymFG9ajpgs6rhqv%2Fimage_0?alt=media&token=86d21a46-b2a2-45a8-8f37-eba4f92ec086" />

## Conclusion

The "Suspicious Activity Detection in Protected Areas Using Image Processing" project has made considerable advancements, covering hardware procurement, design, testing, and software development. Each phase has contributed towards building a comprehensive system capable of monitoring and detecting suspicious activities effectively.

By replicating the steps outlined in this report, individuals working on similar projects can leverage the insights gained from this initiative, enhancing their capabilities in managing protected areas through innovative image processing solutions. The integration of advanced imaging and real-time processing technologies stands to greatly benefit biodiversity preservation and elicit efficient responses to detected threats in protected environments.

Future work will involve refining the algorithms for better detection accuracy, further optimizing the system for diverse environments, and conducting field tests to validate the setup under real-world conditions. Your engagement and collaboration in these endeavors are highly encouraged as we strive towards achieving our goals in conservation and protection.

A project focused on detecting and mitigating unauthorized activities in protected areas using image processing to identify suspicious behaviors such as running, face masking, and carrying foreign objects.

Suspicious activity detection in forest or other protected areas using image processing.

MEDICUS is a cutting-edge medicine dispenser designed to service rural areas with limited access to healthcare facilities. Acting as a 24x7 medicine bank, MEDICUS ensures that patients receive timely and essential medications. The device is integrated with live doctor support, allowing healthcare professionals to dispense medications remotely, tailored to each patient's needs.

This state-of-the-art system operates using RFID cards, ensuring secure and personalized access to medicines. Additionally, MEDICUS is equipped with advanced sensors capable of monitoring vital statistics such as pulse and temperature. This real-time data collection enables doctors to make informed decisions about each patient’s treatment plan, enhancing the overall healthcare experience.

MEDICUS aims to bridge the gap between urban and rural healthcare by providing an accessible, efficient, and reliable solution for dispensing medicines. With its innovative technology and user-friendly interface, MEDICUS stands as a beacon of hope for improving healthcare accessibility in underserved areas.

Completed medicus project

## Abstract

MEDICUS is a transformative project aimed at addressing healthcare disparities in rural areas with limited healthcare access. By leveraging advanced technology, this innovative medicine dispenser operates as a 24x7 medicine bank, ensuring patients receive essential medications in a timely manner. Integrated with live doctor support and equipped with real-time monitoring capabilities, MEDICUS enhances patient care through remote medical assistance, ultimately aiming to bridge the urban-rural healthcare gap.

## Introduction

Healthcare accessibility remains a significant challenge in rural regions worldwide. Many individuals in these areas experience delays in receiving medical treatments due to insufficient healthcare infrastructure. This gap in healthcare access can lead to serious health complications and even loss of life. Responding to this pressing issue, the MEDICUS project was conceived to provide a reliable and efficient solution for delivering medications to individuals in underserved regions.

MEDICUS stands out as an advanced medicine dispenser that combines automation, real-time monitoring, and remote medical support. By utilizing cutting-edge technology such as RFID for secure access, live doctor consultations, and health monitoring sensors, MEDICUS aims to ensure that patients receive timely, personalized medical support.

## Objectives

* To provide an automated medicine dispensing mechanism that operates 24/7.
* To offer real-time vital sign monitoring for remote healthcare consultations.
* To ensure secure and personalized access to medications using RFID technology.
* To enhance communication between healthcare providers and rural patients.
* To improve health outcomes in underserved communities through accessible medication provision.

## Features of the Project

* **Automated Medicine Dispensing Mechanism**: Ensures efficient and timely dispensing of medications.
* **Medicine Storage Containers**: Safely store various types of medications.
* **LCD Display for Instructions**: Provides clear instructions for users.
* **User Authentication System**: Enhances security and ensures personalized access.
* **Embedded System Integration**: Facilitates seamless operation of all system components.
* **Raspberry Pi System for Video Call and User Interface**: Supports real-time doctor consultations.
* **User Interface Application**: Provides an easy-to-use interface for patients and healthcare providers.
* **Database for Patient Records**: Maintains secure and organized patient data.
* **Remote Monitoring System**: Allows healthcare providers to monitor patients' vital statistics wirelessly.
* **Real-time Alert System**: Notifies healthcare providers about critical health changes.
* **API for Data Synchronization**: Ensures consistency and up-to-date information across devices.
* **Security Encryption**: Protects sensitive patient data from unauthorized access.

## Final Outputs

Upon completion of the MEDICUS project, the following outputs are expected:

* Hardware
* Mobile App
* 3D Design and CAD File
* Web App
* Circuit Diagram

## Components Used

| Image                                                                                                                                                                                                                                                                        | Component Name                                             | Quantity | Price (₹) |
| ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------- | -------- | --------- |
| <img height="140" width="140" alt="ESP32 DevKit" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2FQRX42DFHu2kKWLoewGf3%2Fimage_0?alt=media&token=d74c9129-b069-472a-a473-1fe1c9d2ee80" />                                               | ESP32 DevKit                                               | 1 pcs    | 340       |
| <img height="125" width="125" alt="DS18B20 Water Proof Temperature Probe" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2F003jUzSzoUFLjeT5Gg4c%2Fimage_0?alt=media&token=ed70fac5-9ab3-4743-85e6-a75a61338d6b" />                      | DS18B20 Water Proof Temperature Probe                      | 1 pcs    | 89        |
| <img height="119" width="119" alt="Heart Beat Pulse Sensor Amped" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2FKnMOL20gVMjrzpOUSOlW%2Fimage_0?alt=media&token=808628f7-ed44-4bd0-abc8-0f65693fecdd" />                              | Heart Beat Pulse Sensor Amped                              | 1 pcs    | 135       |
| <img height="147" width="147" alt="Raspberry Pi 4 Model-B with 4 GB RAM" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2FUnke80JI0U6kIw7P8Viv%2Fimage_0?alt=media&token=b9707400-0880-44a7-8e09-836ff2a3d34d" />                       | Raspberry Pi 4 Model-B with 4 GB RAM                       | 1 pcs    | 5300      |
| <img height="140" width="140" alt="5 Inch Touch Screen HDMI Interface TFT LCD" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2FuukA6eDHZGgy5RdpzR1N%2Fimage_0?alt=media&token=7bd8e92e-7a72-4c5e-8177-0df23d5d573d" />                 | 5 Inch Touch Screen HDMI Interface TFT LCD                 | 1 pcs    | 2900      |
| <img height="129" width="129" alt="5MP Raspberry Pi 3/4 Model B Camera Module" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2FFQeCwfov8JvbBDuA7Lrq%2Fimage_0?alt=media&token=a2748443-c48d-4f4d-a017-3788db8c4df6" />                 | 5MP Raspberry Pi 3/4 Model B Camera Module                 | 1 pcs    | 220       |
| <img height="131" width="131" alt="RC522 RFID Card Reader Module 13.56MHz" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2FQrDk0RJoGEPQMDMiG8WC%2Fimage_0?alt=media&token=2a92b9d8-6327-4af6-b10e-f5f027fb6711" />                     | RC522 RFID Card Reader Module 13.56MHz                     | 1 pcs    | 85        |
| <img height="130" width="130" alt="Micro HDMI Male to HDMI Male Adapter" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2FDabiZr7U2gY7IBIDEo0O%2Fimage_0?alt=media&token=097266cc-f6b9-4958-bf3e-c77a52f26c1e" />                       | Micro HDMI Male to HDMI Male Adapter                       | 1 pcs    | 125       |
| <img height="133" width="133" alt="TowerPro SG90 Servo Motor (180° Rotation)" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2FSMmE8TyqpxGlP0RKz1d3%2Fimage_0?alt=media&token=6d1137da-0c90-4544-b275-3f25807b5f09" />                  | TowerPro SG90 Servo Motor (180° Rotation)                  | 2 pcs    | 292       |
| <img height="144" width="144" alt="Orange INR 18650 11.1V 2000mAh 3C 3S1P Li-Ion Battery Pack" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2Ff1FLahYsUTI4msCpuD2P%2Fimage_0?alt=media&token=1d48b4f1-c2b8-4cc4-bd68-d0ebd45e15d3" /> | Orange INR 18650 11.1V 2000mAh 3C 3S1P Li-Ion Battery Pack | 1 pcs    | 820       |
| <img height="148" width="148" alt="3D Printing Service" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2F6e0Imq6gRpEyts0O0mlw%2Fimage_0?alt=media&token=a5967fcf-f856-4203-9caf-04c41440afb9" />                                        | FDM 3D Printing Service                                    | 250 gm   | 1250      |

## Innovativeness/Social Relevance/Real World Application

The MEDICUS project embodies innovation by integrating various technological elements into a unified healthcare solution. The use of RFID technology ensures secure access to medications, while real-time monitoring capabilities empower healthcare professionals to make informed decisions about patient care. Moreover, the remote doctor consultation feature enhances healthcare delivery, making it possible for medical professionals to assist patients without being physically present.

The social relevance of MEDICUS cannot be overstated. By providing access to essential medications and healthcare advice in rural areas, this project addresses health inequalities and improves the quality of life for underserved populations. The potential for saving lives and preventing health complications is immense, as patients can receive timely interventions and necessary treatments through this innovative medicine dispenser.

In the real world, MEDICUS holds the potential to revolutionize healthcare accessibility. Its implementation in rural healthcare systems could serve as a model for similar future initiatives aimed at enhancing healthcare services across geographical barriers. Whether in remote villages or areas struck by natural disasters, MEDICUS can become a lifeline for many in need.

## Conclusion

MEDICUS, with its state-of-the-art technology and thoughtful integration of features, presents a compelling solution for improving healthcare access in rural areas. By automating the medicine dispensing process, integrating remote healthcare support, and enabling real-time health monitoring, this project aims to transform healthcare delivery. The successful implementation of MEDICUS could reduce health disparities and save lives in underserved communities. Moving forward, the MEDICUS initiative stands as a beacon of hope, pushing the boundaries of healthcare accessibility and setting a new standard for innovative health solutions.

# Project MEDICUS Update Document

## Introduction

The MEDICUS project is a pioneering venture focused on developing a sophisticated medicine dispenser that leverages both hardware and software components to ensure efficient medication administration. This document provides a comprehensive overview of the project's development phases, including detailed descriptions of features, progress updates, challenges faced, and future steps.

## Project Overview

### MEDICUS Integration

MEDICUS utilizes modern technologies to create a user-friendly and automated medicine dispensing system. The core technologies employed in the project include:

* **Embedded Systems**: Integration of multiple sensors and actuators for real-time monitoring and dispensing.
* **Software Application**: Utilizing Python and API integration for seamless operation.
* **Networking Technologies**: Connect various devices for enhanced interaction and monitoring.

The project comprises several key components aimed at improving patient care and medication management.

***

## Development Phases

### Phase 1: Project Initiation

* **Date**: December 7, 2023
* **Update**: The development of the circuit diagram for the MEDICUS project commenced. The circuit design illustrates the integration of various crucial components needed for the automated medicine dispensing mechanism.<img height="443" width="749" alt="Circuit Diagram" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/projects%2Fmedicus%2Fupdates%2FLZZGZ4ljmwecLHuR2WDm%2Fimage_0?alt=media&token=715c119e-8828-4956-a213-327133888444" />
  * **Microcontroller**: The ESP32 DevKit acts as the central microcontroller.
  * **Sensors**: Integrated along with DS18B20 Waterproof Temperature Probe for environmental monitoring and Heart Beat Pulse Sensor for user health monitoring.
  * **User Authentication**: An RC522 RFID Card Reader Module for secure access.
  * **Actuators**: TowerPro SG90 Servo Motors to control the dispensing mechanism.

### Phase 2: Circuit Board Development and Sensor Integration

* **Date**: December 11, 2023
* **Update**: The development team successfully created the circuit board. This component is pivotal for integrating various hardware and software features of the MEDICUS project.

#### Components Included:

* **ESP32 DevKit**: For connectivity and control.
* **RFID Card Reader**: Ensuring user authentication.
* **Servo Motors**: To dispense medicine effectively.
* **Sensors**: These include a heart rate sensor and a DS18B20 temperature sensor.

### Phase 3: Connecting Sensors and Features

* **Date**: December 15, 2023
* **Update**: The integration of the Connected RFID Card Reader was completed, enabling secure user authentication. The implementation also covered the DS18B20 Waterproof Temperature Probe to monitor storage temperatures and the Heart Beat Pulse Sensor.**Images**:
  * <img height="179" width="179" alt="RFID Card Reader" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2FQrDk0RJoGEPQMDMiG8WC%2Fimage_0?alt=media&token=2a92b9d8-6327-4af6-b10e-f5f027fb6711" />
  * <img height="108" width="108" alt="DS18B20 Temperature Probe" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2F003jUzSzoUFLjeT5Gg4c%2Fimage_0?alt=media&token=ed70fac5-9ab3-4743-85e6-a75a61338d6b" />
  * <img height="220" width="220" alt="Heart Beat Pulse Sensor" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2FKnMOL20gVMjrzpOUSOlW%2Fimage_0?alt=media&token=808628f7-ed44-4bd0-abc8-0f65693fecdd" />

### Phase 4: Hardware Assembly and Mechanism Implementation

* **Date**: December 22, 2023
* **Update**: Attention turned towards assembling the hardware. The team covered the dispensary structure using multi-wood, giving it both aesthetic appeal and durability. The mechanism for dropping medicines has been successfully implemented.**Images**:
  * <img height="757" width="567" alt="Assembly Structure" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/projects%2Fmedicus%2Fupdates%2FRQBiXJaFiVw0dyO69pan%2Fimage_0?alt=media&token=ddee173b-bb44-43b4-b919-4ad65b6ac92e" />

### Phase 5: LCD Display Integration

* **Date**: December 27, 2023
* **Update**: Focus shifted towards the implementation of the LCD display. This feature enhances user interaction by providing clear, real-time instructions for medication dispensing.
*
  * Finalizing design and layout of the LCD display.
  * Developing the display interface using Python.
  * Ensuring compatibility with the overall system architecture.

### Phase 6: Automatic Medicine Dispensing Mechanism

* **Date**: January 4, 2024
* **Update**: The development of the Automated Medicine Dispensing Mechanism was initiated. Leveraging the TowerPro SG90 Servo Motor for precise control over dispensing.

<img height="725" width="543" alt="Medicine Dispensing Mechanism" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/projects%2Fmedicus%2Fupdates%2FyvwStNVoKEJe59Byduuf%2Fimage_0?alt=media&token=8129fdd5-6377-4c4c-b727-0c660a8eba50" />

### Phase 7: Integration of Embedded System Components

* **Date**: January 25, 2024
* **Update**: Integrate various elements of the embedded system, ensuring seamless connectivity between the medicine dispensing mechanism, user authentication, and monitoring features.

#### Components Being Integrated:

* **ESP32 DevKit** for connectivity.
* **Raspberry Pi** for managing operations and control.

MEDICUS: An innovative medicine dispenser designed to streamline and automate medication management.

MEDICUS - An innovative medicine dispenser

Introducing the RFID-Based Smart Shopping Cart, a revolutionary solution for modern supermarkets designed to enhance the shopping experience. This innovative cart integrates advanced RFID technology to seamlessly scan and track products as customers shop. Each item added to the cart is instantly recognized and its price is automatically tallied, providing a real-time total of the cart's value. 

Moreover, the Smart Shopping Cart is equipped with a motorized system that can be controlled via a mobile app. Shoppers can effortlessly navigate the aisles, directing the cart with ease and focusing more on selecting their desired products rather than pushing a cumbersome cart. The mobile app also offers additional features, such as a shopping list manager and real-time promotions, further enhancing the convenience and efficiency of the shopping experience.

With the RFID-Based Smart Shopping Cart, supermarkets can offer a cutting-edge solution that reduces checkout time, improves accuracy, and enhances customer satisfaction. This futuristic approach to shopping not only streamlines the in-store experience but also aligns with the growing demand for smart, tech-driven retail solutions.

Circuit diagram of the project rfid based smart shopping

# RFID-Based Smart Shopping Cart Report

## Abstract

The RFID-Based Smart Shopping Cart represents a cutting-edge innovation in the retail space, a sector traditionally bogged down by long checkout lines and cumbersome shopping experiences. Leveraging the power of Radio Frequency Identification (RFID) technology, this intelligent shopping cart significantly simplifies the shopping process for customers while improving operational efficiency for supermarkets. Each item scanned is logged in real-time, providing accurate pricing and inventory management, allowing customers to focus on product selection without the distraction of manual checkouts. Furthermore, with motorized navigation supported by a dedicated mobile application, the cart enhances user comfort and enables controlled shopping experiences. This report outlines the key components, features, and implications of the RFID-Based Smart Shopping Cart and delves into its potential impact on the future of retail shopping.

## Introduction

In today's fast-paced world, technology has permeated every facet of our lives, changing how we shop and interact with our surroundings. Supermarkets, which are at the forefront of consumer interaction, have not been spared from this technological evolution. The RFID-Based Smart Shopping Cart introduces a seamless shopping experience, transforming the mundane act of grocery shopping into an intuitive, engaging activity. This project aims to revolutionize the shopping experience by eliminating the traditional hassle associated with shopping carts while utilizing modern technology to enhance user satisfaction.

## Objectives

The main objective of the RFID-Based Smart Shopping Cart project is to:

1. Integrate RFID technology to improve the shopping experience by enabling automatic scanning and tracking of items.
2. Develop a user-friendly mobile application for cart control and management of shopping lists.
3. Provide an efficient solution that minimizes checkout times while improving accuracy in pricing and inventory management.
4. Enhance the shopper’s comfort through the implementation of a motorized control system.

## Features of the Project

* **3D Modelling of Cart with Fusion360**: A detailed 3D model of the shopping cart was designed, allowing for visualization and enhancements before physical construction.
* **RFID Scanner**: This component facilitates automatic identification and tracking of products in real-time as they are added to the cart.
* **Motor Driver and Motor Integration**: The integration allows the cart to be maneuvered with minimal physical effort through advanced motorized technology.
* **ESP32 Integration**: An ESP32 microcontroller was used to facilitate wireless communication between the cart and the mobile app.
* **Flutter Development**: The mobile application was developed using Flutter to ensure a cross-platform experience on various devices.
* **Firebase Integration**: Firebase was leveraged for secure data management and real-time syncing of user data.
* **Cart Control Feature in App**: Users can control the cart via the mobile application, making navigation in stores significantly easier.
* **Mobile Application with Complete Functionality**: The app offers users features such as shopping list management, real-time promotions, and a streamlined checkout process.
* **Arduino Setup**: The Arduino platform was utilized for the hardware setup, facilitating various sensor and control integrations.
* **Product Listing Feature in App**: Users can easily browse and manage their products within the application.
* **Total Cart Amount Calculation Feature**: As items are added, the app automatically calculates the total cart amount in real-time.
* **Hardware Assembly**: All hardware components were meticulously assembled to ensure seamless operation.

## Final Outputs

Upon project completion, the following outputs will be delivered:

* Hardware
* Mobile App
* Complete codebase
* 3D design and CAD file
* Circuit Diagram

## Components Used

The project utilizes several components vital for the operation of the RFID-Based Smart Shopping Cart. The details of these components are as follows:

| Image                                                                                                                                                                                                                                                                 | Component Name                                      | Quantity | Price (₹) |
| --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------- | -------- | --------- |
| <img height="190" width="190" alt="ESP32 DevKit" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2FQRX42DFHu2kKWLoewGf3%2Fimage_0?alt=media&token=d74c9129-b069-472a-a473-1fe1c9d2ee80" />                                        | ESP32 DevKit                                        | 1        | 340       |
| <img height="199" width="199" alt="LCD1602 Parallel LCD Display with IIC/I2C interface" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2FyoeYbocGlxDIO8gIYOMF%2Fimage_0?alt=media&token=ed9c780f-d81b-4850-a975-77a3b948f95e" /> | LCD1602 Parallel LCD Display with IIC/I2C interface | 1        | 180       |
| <img height="139" width="139" alt="RC522 RFID Card Reader Module 13.56MHz" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2FQrDk0RJoGEPQMDMiG8WC%2Fimage_0?alt=media&token=2a92b9d8-6327-4af6-b10e-f5f027fb6711" />              | RC522 RFID Card Reader Module 13.56MHz              | 1        | 85        |
| <img height="195" width="195" alt="60RPM 12V DC Geared Motor 60 RPM TORQUE 3.6kg-cm" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2FeyIG2B10OtgRbfXwzSwo%2Fimage_0?alt=media&token=39af1b68-aa74-4d7f-97d8-629343045494" />    | 60RPM 12V DC Geared Motor                           | 2        | 360       |
| <img height="183" width="183" alt="L298N 2A Based Motor Driver Module" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2FWqbyMsrU6jT1GaVRX75J%2Fimage_0?alt=media&token=a6e72615-14a3-4149-a59b-c65f69bab18a" />                  | L298N 2A Based Motor Driver Module                  | 1        | 100       |
| <img height="199" width="199" alt="6A 250V AC DPST ON-OFF Red Round Rocker Switch" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2FNWrWMg4ZfkRpHdhrMdyF%2Fimage_0?alt=media&token=c138b613-981d-47ae-a5df-7dc156e7aab4" />      | 6A 250V AC DPST ON-OFF Red Round Rocker Switch      | 1        | 80        |
| <img height="172" width="172" alt="FDM 3D Printing Service" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2F6e0Imq6gRpEyts0O0mlw%2Fimage_0?alt=media&token=a5967fcf-f856-4203-9caf-04c41440afb9" />                             | FDM 3D Printing Service                             | 250 gm   | 1250      |

## Innovativeness/Social Relevance/Real-World Application

The RFID-Based Smart Shopping Cart stands as a paradigm shift in retail shopping. The integration of modern technologies can be perceived as a contributor to various societal aspects such as enhanced consumer experiences, reduced labor costs, and increased operational efficiency for supermarkets. Here are several key points illustrating the innovativeness and social relevance of this project:

1. **Enhanced User Experience**: Shoppers no longer need to endure long wait times at checkout lines. Instant price calculations make the entire shopping process smoother.
2. **Operational Efficiency**: For supermarkets, this technology means reduced manpower for checkout processes, freeing employees for customer service roles or stock management.
3. **Data Analytics**: RFID technology allows retailers to gather and analyze sales data effectively. Understanding customer preferences and buying patterns becomes easier, ultimately informing inventory strategies and marketing decisions.
4. **Cost Reduction**: Although the initial investment in smart devices may be significant, over time, the decrease in labor costs and improved efficiency can lead to substantial financial savings.
5. **Health and Safety**: In a post-pandemic world, contactless shopping options and reduced interactions can promote safety and health, aligning with current consumer priorities.

## Conclusion

The RFID-Based Smart Shopping Cart presents a remarkable fusion of convenience, efficiency, and innovation in retail shopping. By eliminating traditional checkout processes and enhancing the in-store shopping experience, the project aligns with the ever-evolving expectations of modern consumers. Furthermore, the successful integration of motorized navigation into a user-friendly mobile application provides a glimpse into the possibilities of smart retail solutions. As supermarkets continue to embrace technology, the potential advantages of this project could lead to widespread adoption, fundamentally altering the shopping landscape. This report highlights the necessity and relevance of implementing smart solutions in retail settings, paving the way for an improved future of shopping.

In summary, the RFID-Based Smart Shopping Cart is not just a technological advancement; it is a leap towards a more innovative and effective retail environment that meets the needs of both consumers and retailers alike.

# Project Report: RFID-Based Smart Shopping Cart

## Introduction

The RFID-Based Smart Shopping Cart is a pioneering solution aimed at transforming the shopping experience in modern supermarkets. The cart employs advanced RFID technology that allows for seamless scanning and tracking of products, enabling shoppers to focus on product selection without the hassle of traditional checkout processes.

This document serves as a comprehensive guide to the development phases of the RFID-Based Smart Shopping Cart project, detailing the essential steps, components, and updates throughout the project lifecycle.

## Project Development Phases

### Phase 1: Component Procurement

**Update:** Bought the necessary parts for RFID-Based smart shopping cart

<img height="773" width="580" alt="Component Procurement" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/projects%2Frfid-based-smart-shopping-cart%2Fupdates%2FtKf5BE9g2EOQrrkakLPX%2Fimage_0?alt=media&token=d6c0668a-81a6-4bac-abb1-93c63815b7fc" />

In this initial phase, key components were procured to implement the RFID Scanner feature of the smart shopping cart. Highlights of this procurement phase include:

* **RFID Reader Module:** Acquired an RC522 RFID Reader Module for efficient scanning of RFID tags.
* **RFID Tags:** Secured necessary RFID tags compatible with the reader to enable rapid item identification.
* **Integration Planning:** Evaluation of hardware and software compatibility to ensure a cohesive system.

This foundational step is critical to facilitate subsequent developments effectively.

### Phase 2: Circuit Design

**Update:** Circuit diagram of the project RFID-based smart shopping

<img height="332" width="591" alt="Circuit Diagram" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/projects%2Frfid-based-smart-shopping-cart%2Fupdates%2FoQZP7hoTpL1hmS2L1RTu%2Fimage_0?alt=media&token=7e1bcc79-cd6c-492d-8fca-624063b57d98" />

The next essential phase involved designing a comprehensive circuit diagram that outlines the integration of various components within the smart shopping cart. The components included:

* **ESP32 DevKit:** Serves as the primary microcontroller for managing operational tasks.
* **RC522 RFID Card Reader Module:** Utilized for scanning RFID tags on products.
* **L298N Motor Driver Module:** Controls the 12V geared motors integral for moving the cart.
* **LCD1602 Display:** Provides visual feedback and displays cart totals and product information.
* **Power Management:** Incorporated a red round rocker switch to manage power supply.

This circuit diagram acts as a blueprint for assembling the electronic components effectively.

### Phase 3: User Interface Development

**Update:** Completed UI screen for user

<img height="846" width="381" alt="UI Screen" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/projects%2Frfid-based-smart-shopping-cart%2Fupdates%2FJkykEKzb2qzkYRa67mbL%2Fimage_0?alt=media&token=b0183ce9-85c8-4ec9-9846-9d5d42c64f51" />

In this phase, the user interface (UI) was designed to enhance customer interaction with the shopping cart system. Key accomplishments include:

* **Modern Design:** Crafted a visually appealing and intuitive interface focusing on usability.
* **Interaction Features:** Implemented asynchronous elements for scanning products, viewing the cart's content, and managing shopping lists.
* **Real-Time Updates:** Integrated a system to display the total cart amount and product information dynamically.
* **Control Options:** Added buttons for controlling the cart’s movements conveniently.

### Phase 4: Admin Interface Completion

**Update:** Completed Admin Screen UI

<img height="773" width="348" alt="Admin UI" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/projects%2Frfid-based-smart-shopping-cart%2Fupdates%2Fmq05bWkTjwh5hkZS3yki%2Fimage_0?alt=media&token=98df875d-5a47-4bb9-8558-8d5df2be72e4" />

The Admin interface enables effective management of the smart shopping cart system. Key features include:

* **User-Friendly Layout:** Designed to be intuitive with easy navigation.
* **Responsive Elements:** Ensured the interface adjusts seamlessly across various devices.
* **Control Options:** Added functionalities relevant to product addition, purchase processing, and cart control.

This phase ensures that administrators can effectively manage the cart system efficiently.

### Phase 5: Integration of Components

**Update:** Integrated Sensors and LCD Display with ESP32

<img height="786" width="590" alt="Sensor Integration" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/projects%2Frfid-based-smart-shopping-cart%2Fupdates%2Fkt9krFdGVpTEzEjbCVF7%2Fimage_0?alt=media&token=ee0526d2-56d8-4d51-8219-c74accf813ab" />

The integration phase involved connecting various components, enhancing the cart’s interactive functionalities. Accomplishments included:

* **LCD Display:** Added for providing visual feedback to users.
* **RFID Technology Integration:** Successfully connected the RFID scanner with the existing system.
* **Motor Controller Connection:** Integrated the motor controller allowing for cart mobility.

Following comprehensive testing, these integrations significantly improved system responsiveness.

### Phase 6: 3D Design Implementation

**Update:** 3D Designed and printed the case for the smart shopping project

<img height="638" width="848" alt="Case Design" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/projects%2Frfid-based-smart-shopping-cart%2Fupdates%2F2nRCU4ZEu5koLzoPa4jl%2Fimage_0?alt=media&token=95f6b190-c76f-4a47-b574-9d20d63cf022" />

The physical structure of the smart shopping cart was developed using 3D design and printing techniques:

* **Case Modeling:** Developed a 3D model of the shopping cart body using Fusion360.
* **Printing:** The case was 3D printed, taking care to ensure optimal protection for electronic components.
* **Testing for Durability:** Conducted tests to assess the functionality and durability of the printed case.

### Phase 7: Assembly of Hardware Components

**Update:** Assembled RFID module into the cart

<img height="546" width="728" alt="RFID Module Assembly" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/projects%2Frfid-based-smart-shopping-cart%2Fupdates%2FJkdU2IR0qSAy22P94EpR%2Fimage_0?alt=media&token=1bf58bfb-33c6-41f2-b08a-f79714fed5c4" />

The final assembly phase involved integrating all hardware components into the smart shopping cart structure:

* **Component Assembly:** Successfully integrated the RFID scanner, ESP32 DevKit, motor driver module, LCD display, and card reader into the cart.
* **Alignment and Stability:** Ensured that each component was securely attached and properly aligned.
* **Functional Testing:** Conducted comprehensive testing to validate proper operations.

This step concluded the hardware assembly, resulting in a fully operational smart shopping cart.

### Phase 8: Final Integration Testing

The final phase involved rigorous testing of the entire system to ensure seamless operation, thus setting the stage for practical deployment:

* Conducted **integration testing** on the software and hardware components for system coherence.
* Verified that all features, including scanning, mobility control, and data display, function as intended.
* Adjusted the user interfaces based on feedback from initial user tests to enhance the shopping experience.

## Conclusion

The RFID-Based Smart Shopping Cart project exemplifies a significant innovation in the retail space through technology integration. Each phase has been meticulously documented to provide stakeholders with the guidance needed to understand, replicate, and improve upon the project. This document serves as a blueprint for future developments and enhancements within the smart shopping cart domain.

For further inquiries or clarifications regarding any step or feature described, stakeholders are encouraged to reach out to the project team for support and elaboration. The potential for refinement and additional features, including advanced analytics and user behavior tracking, continues to grow, establishing a foundation for further research and development in the realm of smart retail solutions.

A smart shopping cart for supermarkets that uses RFID to scan products, display the total amount, and can be controlled via a mobile app.

RFID-Based Smart shopping cart

Sleep apnea is a serious disorder that causes breathing to be interrupted, or stopped for 10 seconds 
or more. Sleep apnea occurs in three main forms: Obstructive sleep apnea (OSA), Central sleep 
apnea (CSA), and Complex sleep apnea. OSA is the most prevalent cause due to the softening of 
muscles leading to obstruction of the airway. This disorder can cause various complications and health risks such as heart failure, stroke, anxiety, depression, etc. Several factors contribute to the 
development of sleep apnea like obesity, excessive use of alcohol, smoking, etc. Early detection 
of sleep apnea is crucial for timely intervention and effective treatment of the disorder. We are 
mainly focusing on Obstructive sleep apnea. Here, our main aim is to develop a cost-effective 
sleep monitoring system that integrates ML algorithm to improve performance, and also develop 
a web interface for both the patient and doctor to access. We used a Random-forest algorithm to 
train our model that predicts sleep apnea. SpO2, heart rate, accelerometer readings as well as the 
duration of each apnea event are taken as the inputs to train the model. With the above 
information, the model calculates AHI Index and differentiates the condition into Severe sleep apnea, moderate sleep apnea, mild sleep apnea. 

Completed 3D design of the project

## Abstract

Sleep apnea remains a prevalent and serious disorder that significantly impacts patients' health and quality of life. This report presents the design and implementation of the "Apnea Aware: Sleep Monitoring System," which aims to provide a cost-effective solution for monitoring and detecting obstructive sleep apnea (OSA). By integrating a machine learning (ML) algorithm and developing a web interface for both patients and doctors, this project seeks to facilitate early detection and timely intervention. The system primarily focuses on analyzing data from key physiological parameters such as SpO2 levels, heart rate, and accelerometer readings. This innovative solution is designed to improve health outcomes for individuals suffering from sleep apnea.

## Introduction

Sleep apnea is characterized by repeated interruptions in breathing during sleep, lasting at least 10 seconds. With its three main forms—Obstructive Sleep Apnea (OSA), Central Sleep Apnea (CSA), and Complex Sleep Apnea—OSA is the most common and troubling, primarily due to airway obstruction caused by relaxation of throat muscles. The disorder poses substantial health risks, including cardiovascular issues, stroke, anxiety, and depression, thereby emphasizing the necessity for early diagnosis and intervention.

Risk factors contributing to the development of sleep apnea include obesity, heavy alcohol consumption, and smoking habits. Considering these substantial health implications, the purpose of this project is to establish a user-friendly, cost-effective sleep monitoring system that leverages the latest advancements in technology, including machine learning.

## Objectives

The goal of the "Apnea Aware: Sleep Monitoring System" project is to create an efficient solution to monitor sleep apnea, particularly OSA. Our specific objectives include:

1. Develop a hardware platform that captures vital physiological data (e.g., heart rate, SpO2, accelerometer readings).
2. Construct an ML model using the Random Forest algorithm capable of predicting the severity of sleep apnea by calculating the Apnea-Hypopnea Index (AHI).
3. Create an intuitive web interface for patients to visualize their data and for doctors to access patient reports easily.
4. Promote accessibility and affordability of sleep monitoring solutions for patients and healthcare providers, potentially reducing the long-term health burden.

## Features of the Project

* **Hardware Design & Assembly (Fusion360)**: The design of the hardware platform enables efficient monitoring of patients’ vital signs during sleep.
* **Backend System for Storage and Retrieval (Firebase)**: Implementation of a robust backend for secure data storage that allows seamless retrieval of patient information.
* **Patient Web Interface Development (Flutter)**: A user-friendly web platform where patients can view their health data, including the results of their sleep monitoring.
* **Doctor Web Interface Development (Flutter) - Video Calling Feature**: A separate access point for doctors that supports remote consultations and reviews patient data.
* **Sleep Monitoring Hardware Device**: Comprising the ESP32 microcontroller and various sensors (mic, heart rate, SpO2, accelerometer), this device captures necessary physiological readings.
* **ML Algorithm Development for Sleep Apnea Detection**: The integration of machine learning to enhance detection capabilities through the analysis of the collected data.
* **Data Collection and Processing**: Thorough procedures to ensure accurate data capture and preprocessing before being input into the machine learning model.
* **AHI Index Calculation & Severity Categorization Feature**: The system calculates the AHI Index to categorize the severity of sleep apnea into mild, moderate, or severe.
* **Final Conclusion Features**: The application generates a detailed report summarizing the severity level based on the AHI results, enhancing the prediction interval heuristically.

## Final Outputs

The project culminates in several deliverables, including a hardware prototype, mobile and web applications, comprehensive source code, and a detailed circuit diagram. These deliverables ensure that users receive a well-rounded product with sufficient support for implementation and usability.

## Components Used

The following components were utilized in the development of the Apnea Aware system:

| Image                                                                                                                                                                                                                                       | Component Name                                                    | Quantity | Price (₹) |
| ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------- | -------- | --------- |
| <img height="177" width="177" alt="LILYGO T-Display ESP32" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2Fbn5xHXlIQGzU8lZlyyYm%2Fimage_0?alt=media&token=131b9ec3-bef6-41a9-a5e7-87e39ef363c6" />    | LILYGO T-Display ESP32 WiFi Bluetooth Development Board           | 1        | 1590      |
| <img height="168" width="168" alt="MPU6050 Accelerometer" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2FYPezcZTMB4oiHKIxCobQ%2Fimage_0?alt=media&token=5fd959d0-ea03-492a-b4c6-40a1c44144d6" />     | MPU6050 Accelerometer & Gyro Sensor                               | 1        | 113       |
| <img height="170" width="170" alt="MAX30100 Pulse Oximeter" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2FoipnzcJ9UMD1OgcY3m6u%2Fimage_0?alt=media&token=98b7e9ac-1fa7-47e7-a074-42c23bc2d24c" />   | MAX30100 Pulse Oximeter Heart Rate Sensor Module                  | 1        | 115       |
| <img height="156" width="156" alt="INMP441 MEMS Microphone" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2FBmU851mjN7uIZp9RkeeI%2Fimage_0?alt=media&token=54e523ee-8f64-4a50-aeb8-a347ecb40e99" />   | INMP441 MEMS High Precision Omnidirectional Microphone Module I2S | 1        | 215       |
| <img height="182" width="182" alt="Rechargeable LiPo Battery" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2FsRDs0MJzy2TUkTHEGneN%2Fimage_0?alt=media&token=13e459f4-d462-437c-ab5d-4ba573889c68" /> | 950 mAh 3.7V single cell Rechargeable LiPo Battery                | 1        | 350       |
| <img height="159" width="159" alt="OLED Display Module" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2F4PXOn5hDhxI7zG1WpsN3%2Fimage_0?alt=media&token=e8882f5b-8a08-4a31-884e-2616e09e3b94" />       | 0.96 Inch I2C/IIC 4pin OLED Display Module BLUE                   | 1        | 170       |
| <img height="174" width="174" alt="4mm SPDT Slide Switch" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2F8grwWO7j0SaVMgtUL6SC%2Fimage_0?alt=media&token=30f1dd8d-16fa-4254-bdb6-2e3cabfd6ff3" />     | 4mm SPDT 1P2T Slide Switch                                        | 1        | 5         |
| <img height="194" width="194" alt="FDM 3D Printing Service" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/parts%2F6e0Imq6gRpEyts0O0mlw%2Fimage_0?alt=media&token=a5967fcf-f856-4203-9caf-04c41440afb9" />   | FDM 3D Printing Service                                           | 250 gm   | 5         |

## Innovativeness/Social Relevance/Real World Application

The Apnea Aware system is designed with social relevance in mind, addressing a widespread health issue impacting millions globally. Traditional diagnostics for sleep apnea often require extensive setups and may be inaccessible to many patients due to costs and logistics. By creating an integrated sleep monitoring system that is both cost-effective and easy to use, we empower patients and healthcare providers alike.

The usage of the Random Forest algorithm enhances the accuracy of sleep apnea detection, which can ultimately lead to timely diagnostics and improved sleep health outcomes. The inclusion of web interfaces for both patients and doctors facilitates improved communication, allowing for remote consultations and making healthcare more accessible.

In the broader context, such innovations may also pave the way for a more extensive array of wearable health technologies, bridging gaps in real-time health monitoring and patient care.

## Conclusion

The "Apnea Aware: Sleep Monitoring System" exemplifies how technology can be harnessed to tackle critical health issues like sleep apnea through innovative, user-friendly solutions. Our project’s multidisciplinary approach integrates advanced machine learning techniques with robust hardware and software development to address the challenges posed by sleep disorders. By focusing on accessibility and affordability, we aim to make a meaningful impact on the lives of individuals suffering from sleep apnea, ultimately contributing to enhanced healthcare outcomes and improved awareness of sleep-related health issues. Through ongoing enhancements and potential integration with other health monitoring technologies, the project aspires to remain at the forefront of innovation in sleep health.

# Apnea Aware: Sleep Monitoring System Project Report

## Project Overview

Sleep apnea is a serious disorder that leads to interrupted breathing during sleep, affecting individuals significantly. The **Apnea Aware: Sleep Monitoring System** aims to develop a cost-effective solution focusing primarily on Obstructive Sleep Apnea (OSA) detection using a combination of Machine Learning algorithms and advanced sensory hardware. This document provides a comprehensive overview of the development phases of the project, detailing each step taken to create a reliable and efficient sleep monitoring solution.

***

## Development Phases

### Phase 1: System Design and Initial Setup

The **initial phase** focused on identifying the necessary components and designing the fundamental architecture of the system. The components include:

* MPU6050 Accelerometer & Gyro Sensor
* MAX30100 Pulse Oximeter Heart Rate Sensor Module
* INMP441 MEMS High Precision Omnidirectional Microphone Module
* ESP32 Development Board
* 950 mAh 3.7V Single-cell Rechargeable LiPo Battery

#### 3D Design of Hardware Components

A crucial step in the project was to create a **3D design** of the hardware system using Fusion 360, which included integrating sensors for effective monitoring of different parameters.

![3D design of hardware components](https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/projects%2Fapnea-aware%3A-sleep-monitoring-system%2Fupdates%2F7naYKKYoZhErtYso3KWO%2Fimage_0?alt=media\&token=da43a388-55b5-475d-b3cd-32afa391c821)

***

### Phase 2: Circuit Diagram and Component Integration

As part of the design process, the team successfully developed a **circuit diagram** that connects all the components for accurate data collection.

<img height="541" width="767" alt="Circuit diagram of the project" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/projects%2Fapnea-aware%3A-sleep-monitoring-system%2Fupdates%2FPCa5oZN46UZvO92vAh8k%2Fimage_0?alt=media&token=ea2ab0de-fd09-4eb7-833d-ef0cda11e0b7" />

The circuit integrates the sensors, which are pivotal in gathering critical physiological data, including SpO2 levels, heart rate, and movement during sleep.

***

### Phase 3: Hardware Updates and Power Management

During the **hardware updates**, the team made significant enhancements, particularly in the power management aspect, optimizing energy usage.

<img height="633" width="844" alt="Power management update" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/projects%2Fapnea-aware%3A-sleep-monitoring-system%2Fupdates%2FwicrPiU200EwLYodCjDZ%2Fimage_0?alt=media&token=4544d2a0-d414-423d-92e0-86e362b5a563" />

These improvements are crucial for maintaining the functionality of the sleep monitoring system while ensuring efficient performance over long periods.

***

### Phase 5: Integration and Testing

Following the successful development of the ML model, the project transitioned into the **integration** phase, where hardware and software components were combined to create a unified system.

The integration process involved:

* Connecting sensors to the ESP32 microcontroller.
* Setting up a **Flask server** to deploy the predictive model for real-time predictions.

<img height="529" width="847" alt="Integration process" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/projects%2Fapnea-aware%3A-sleep-monitoring-system%2Fupdates%2FQ6iOS9pNKxBYe18Q80nb%2Fimage_0?alt=media&token=5ab905f4-2dd1-41f6-9094-eb588785f8ab" />

***

### Phase 6: Web Interface Development

To facilitate both patients and doctors in monitoring progress, a **web interface** was developed using Flutter, providing an intuitive platform for accessing sleep data and healthcare checks.

##### Web Interface Features:

* Real-time display of heart rate and SpO2 graphs.
* Interactive movement graphs utilizing gyro data.

<img height="383" width="725" alt="Heart rate graph integration" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/projects%2Fapnea-aware%3A-sleep-monitoring-system%2Fupdates%2F96OVZtyLY2PbFKguOk74%2Fimage_0?alt=media&token=3b094008-cb5e-4056-bb6a-f272a6298c19" />

The patient interface allows for seamless navigation and easy interpretation of monitoring data, ensuring users can track their health comprehensively.

***

### Phase 7: API Development and Real-time Data Retrieval

In this phase, a **real-time prediction API** was developed, enabling the system to display predictions based on incoming sensor data, enhancing user engagement with immediate feedback.

<img height="648" width="291" alt="API development" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/projects%2Fapnea-aware%3A-sleep-monitoring-system%2Fupdates%2F0Slh8yBWr02hrfD94Qd4%2Fimage_0?alt=media&token=aded4fd1-c9c3-466a-a6e0-2ce0a381a4f1" />

Key characteristics of the API include:

* Continuous data stream processing for accurate health monitoring.
* Seamless integration of various sensor inputs to predict sleep apnea events.

***

### Phase 8: User Communication Enhancement

Recognizing the importance of communication in healthcare, the team implemented a **video calling feature**, enabling real-time consultations between patients and doctors.

<img height="422" width="825" alt="Video call feature" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/projects%2Fapnea-aware%3A-sleep-monitoring-system%2Fupdates%2F4gQyGoPu6HhJGWtiXalq%2Fimage_0?alt=media&token=fca76b0a-1c5b-4ee7-a0ab-6caa5a95a515" />

This enhancement provides a platform for:

* Remote consultations.
* Quick feedback on sleep patterns and necessary adjustments to treatment plans.

***

### Phase 9: Final Testing and Deployment

In the final phase, comprehensive testing was conducted to ensure system reliability and accuracy in detecting and categorizing sleep apnea events.

This included:

* Evaluating the integration of software and hardware.
* Conducting tests to ensure the accuracy of predictions and data retrieval mechanisms.

Upon successful testing, the project transitioned to deployment.

<img height="609" width="862" alt="Final testing" src="https://firebasestorage.googleapis.com/v0/b/projects-43eea.appspot.com/o/projects%2Fapnea-aware%3A-sleep-monitoring-system%2Fupdates%2FPCa5oZN46UZvO92vAh8k%2Fimage_0?alt=media&token=ea2ab0de-fd09-4eb7-833d-ef0cda11e0b7" />

Platform for patient access is hosted at [Apnea Aware](https://apneaaware.web.app/).

***

## Conclusion

The **Apnea Aware: Sleep Monitoring System** represents a significant advancement in sleep apnea diagnosis and management. Through a structured development methodology, from initial design to final deployment, the integration of cutting-edge technology ensures accurate monitoring, predictive analytics, and improved communication between patients and healthcare providers. This project not only aims to enhance the understanding of sleep disorders but also strives for feasible solutions by utilizing affordable technology combined with innovative software solutions.

Ongoing enhancements and user feedback will continue shaping the platform, ensuring a valuable tool accessible to individuals managing sleep apnea effectively. Stay tuned for more updates as we progress further in enhancing functionalities to support efficient sleep monitoring and management.

Apnea Aware: Sleep Monitoring System is a cost-effective solution using machine learning to detect and assess Obstructive Sleep Apnea through SpO2, heart rate, and accelerometer data, providing critical information to both patients and doctors via a web interface.