IOT Based Industrial Air Pollution Monitoring System using Arduino with ...

IOT Based Industrial Air Pollution Monitoring System using Arduino with LabVIEW and Zigbee on Thingspeak | iot based air pollution monitoring system using arduino | IoT Projects using ESP32 | IoT Projects Arduino | WSN Based Real Time Air Pollution Monitoring System Using Zigbee and LabVIEW | Industrial Monitoring System using LabVIEW and GSM. *********************************************************** If You Want To Purchase the Full Working Project KIT Mail Us: svsembedded@gmail.com Title Name Along With You-Tube Video Link We are Located at Telangana, Hyderabad, Boduppal. Project Changes also Made according to Student Requirements http://svsembedded.com/  https://www.svskits.in/ http://svsembedded.in/  http://www.svskit.com/ M1: +91 9491535690  M2: +91 7842358459 We Will Send Working Model Project KIT through DTDC / DHL / Blue Dart / First Flight Courier Service We Will Provide Project Soft Data through Google Drive 1. Project Abstract / Synopsis 2. Project Related Datasheets of Each Component 3. Project Sample Report / Documentation 4. Project Kit Circuit / Schematic Diagram 5. Project Kit Working Software Code 6. Project Related Software Compilers 7. Project Related Sample PPT’s 8. Project Kit Photos 9. Project Kit Working Video links Latest Projects with Year Wise YouTube video Links 157 Projects  https://svsembedded.com/ieee_2022.php 135 Projects  https://svsembedded.com/ieee_2021.php 151 Projects  https://svsembedded.com/ieee_2020.php 103 Projects  https://svsembedded.com/ieee_2019.php 61 Projects  https://svsembedded.com/ieee_2018.php 171 Projects  https://svsembedded.com/ieee_2017.php 170 Projects  https://svsembedded.com/ieee_2016.php 67 Projects  https://svsembedded.com/ieee_2015.php 55 Projects  https://svsembedded.com/ieee_2014.php 43 Projects  https://svsembedded.com/ieee_2013.php 1100+ Projects https://www.svskit.com/2022/02/900-pr... *********************************************************** Creating an IoT-based Industrial Air Pollution Monitoring System using Arduino with LabVIEW and Zigbee on ThingSpeak involves integrating various components and technologies. Here's a step-by-step guide to help you get started: Components Needed: 1. Arduino Board (e.g., Arduino Uno): • Used for sensor interfacing and data processing. 2. Air Quality Sensors (e.g., MQ series sensors): • Measure air pollution parameters like CO, CO2, particulate matter, etc. 3. Zigbee Module: • Enables wireless communication between Arduino and the central system. 4. LabVIEW Software: • Used for creating a graphical user interface (GUI) and processing data. 5. ThingSpeak Account: • Online platform for storing and analyzing sensor data. Hardware Setup: 1. Connect Air Quality Sensors to Arduino: • Wire the sensors to the analog or digital pins on the Arduino. 2. Connect Zigbee Module to Arduino: • Use UART communication to connect the Zigbee module to the Arduino. 3. Power Supply: • Ensure that all components have a stable power supply. 4. Configure Zigbee Communication: • Set up Zigbee communication between the Arduino and the central system. Software Implementation: 1. Arduino Programming: • Write a program to read sensor data and send it to the Zigbee module. • Implement error handling and data formatting. 2. LabVIEW GUI Design: • Create a LabVIEW VI (Virtual Instrument) for the user interface. • Add indicators to display real-time sensor data. • Implement controls for system configuration. 3. LabVIEW Serial Communication: • Use LabVIEW to establish serial communication with the Arduino through the Zigbee module. • Implement data parsing to extract sensor values. 4. ThingSpeak Integration: • Create a ThingSpeak channel to store the sensor data. • Use the ThingSpeak API in LabVIEW to send data to ThingSpeak. Data Visualization: 1. LabVIEW Visualization: • Use LabVIEW to create charts, graphs, or other visual representations of air pollution data. 2. ThingSpeak Dashboard: • Explore ThingSpeak's built-in tools for data visualization and analysis. Testing and Debugging: 1. Test the System: • Ensure that the hardware connections are secure. • Check data transmission between Arduino and LabVIEW. • Verify data upload to ThingSpeak. 2. Debugging: • Use serial monitoring tools for Arduino to debug communication issues. • Check LabVIEW code for any errors or unexpected behavior. Finalization: 1. Optimization: • Optimize the code for efficiency and reliability. • Consider implementing features like data logging or notifications. 2. Documentation: • Document the system architecture, hardware connections, and software implementation. 3. Deployment: • Install the system in the industrial environment. • Monitor and maintain the system as needed. By following these steps, you can create a robust IoT-based Industrial Air Pollution Monitoring System using Arduino, LabVIEW, Zigbee, and ThingSpeak.

VIP Parking QRCode Based System Using IOT With ESP32CAM & IR Sensors

VIP Parking QRCode Based System Using IOT With ESP32CAM & IR Sensors | QR BASED CAR PARKING SYSTEM esp32 | QR code based car parking system using ESP32 CAM with IR sensors | QRCode Based IOT Car Parking System Using ESP32CAM & IR Sensors | QR Code Scanner with ESP32 CAM Module & OpenCV Python Library | QR Code Based Door Lock System using ESP32-CAM | How to make Car Parking System using Arduino and i2c lcd display | Automatic Car Parking System *********************************************************** If You Want To Purchase the Full Working Project KIT Mail Us: svsembedded@gmail.com Title Name Along With You-Tube Video Link We are Located at Telangana, Hyderabad, Boduppal. Project Changes also Made according to Student Requirements http://svsembedded.com/  https://www.svskits.in/ http://svsembedded.in/  http://www.svskit.com/ M1: +91 9491535690  M2: +91 7842358459 We Will Send Working Model Project KIT through DTDC / DHL / Blue Dart / First Flight Courier Service We Will Provide Project Soft Data through Google Drive 1. Project Abstract / Synopsis 2. Project Related Datasheets of Each Component 3. Project Sample Report / Documentation 4. Project Kit Circuit / Schematic Diagram 5. Project Kit Working Software Code 6. Project Related Software Compilers 7. Project Related Sample PPT’s 8. Project Kit Photos 9. Project Kit Working Video links Latest Projects with Year Wise YouTube video Links 157 Projects  https://svsembedded.com/ieee_2022.php 135 Projects  https://svsembedded.com/ieee_2021.php 151 Projects  https://svsembedded.com/ieee_2020.php 103 Projects  https://svsembedded.com/ieee_2019.php 61 Projects  https://svsembedded.com/ieee_2018.php 171 Projects  https://svsembedded.com/ieee_2017.php 170 Projects  https://svsembedded.com/ieee_2016.php 67 Projects  https://svsembedded.com/ieee_2015.php 55 Projects  https://svsembedded.com/ieee_2014.php 43 Projects  https://svsembedded.com/ieee_2013.php 1100+ Projects https://www.svskit.com/2022/02/900-pr... *********************************************************** Creating a QR code-based IoT car parking system using an ESP32-CAM (ESP32 with camera) and IR sensors involves several steps. Below is a basic outline to help you get started. Keep in mind that this is a high-level overview, and you may need to adjust the details based on your specific requirements and hardware setup. Hardware Components: 1. ESP32-CAM module: It integrates an ESP32 microcontroller with a camera. 2. IR Sensors: To detect the presence of a car in a parking space. 3. Power Supply: Provide power to the ESP32-CAM and IR sensors. 4. QR Code Scanner: If not built into the ESP32-CAM, an external QR code scanner may be needed. Software Components: 1. Arduino IDE: Used to program the ESP32-CAM. 2. ESP32 Board Support Package: Install the necessary package in the Arduino IDE for ESP32. 3. QR Code Library: Use a QR code library for Arduino to decode QR codes. 4. Programming Language: Write the necessary code in C++ for the ESP32-CAM. Steps: 1. Set Up Arduino IDE: • Install the Arduino IDE and add support for the ESP32 board. • Install the necessary libraries for QR code decoding. 2. Connect Hardware: • Connect the ESP32-CAM to the computer and configure the Arduino IDE to recognize it. • Connect IR sensors to GPIO pins on the ESP32-CAM for car presence detection. 3. Write Code: • Write Arduino code to handle QR code decoding using the QR code library. • Implement logic to use the camera to capture images and process them for QR code recognition. • Write code to handle IR sensor inputs for car presence detection. 4. QR Code Generation: • Implement a mechanism to generate unique QR codes for each parking space. • Associate each QR code with a specific parking space ID in your system. 5. Communication: • Implement communication between the ESP32-CAM and a central server or database. • When a QR code is scanned, send the parking space ID to the server. 6. Server-Side Logic: • Develop a server-side application to receive parking space IDs from ESP32-CAM devices. • Maintain a database of parking space statuses (occupied or vacant). 7. Web Interface (Optional): • Create a web-based interface to display the status of parking spaces. • Users can check available parking spaces and reserve a spot if needed. 8. Testing: • Test the entire system, including QR code scanning, IR sensor detection, and communication with the server. 9. Deployment: • Deploy the system in a real-world parking environment. 10. Optimization and Security: • Optimize code for performance and implement security measures to prevent unauthorized access or manipulation. Remember to refer to the datasheets and documentation for the ESP32-CAM module, IR sensors, and any other components you use. Additionally, consider the specific requirements and constraints of your parking system while implementing the steps above.