IoT Mining Tracking & Worker Safety Helmet

This guide will help you create an IoT-based mining tracking and worker safety helmet using Raspberry Pi. The helmet will monitor the worker's location, environmental conditions, and safety metrics in real-time, providing alerts and data to improve safety in mining operations.

Components Required

• Raspberry Pi (Model 3 or later)
• GPS module (for location tracking)
• Temperature and humidity sensor (e.g., DHT22)
• Accelerometer (e.g., MPU6050 for detecting falls)
• Microphone or sound sensor (optional, for detecting abnormal noises)
• Buzzer or vibration motor (for alerts)
• Battery pack (for powering the Raspberry Pi and sensors)
• Helmet (for mounting the components)
• Connecting wires and mounting materials
• Cloud service account (e.g., ThingSpeak, Blynk, or AWS IoT)

Setting Up the Hardware

Follow these steps to set up the hardware:

1. Mount the Components on the Helmet

   Securely mount the GPS module, temperature and humidity sensor, accelerometer, and optional sound sensor on the helmet. Ensure that they are positioned to collect accurate data.

2. Connect the Sensors to the Raspberry Pi

   Connect the sensors and modules to the Raspberry Pi using the GPIO pins or I2C interface as required. Ensure all connections are secure and properly insulated.

3. Power the System

   Attach the battery pack to power the Raspberry Pi and sensors. Verify that the power supply is sufficient for all components and securely attached.

Programming the Raspberry Pi

Write the code to read data from the sensors, process it, and send it to the cloud. Below is a basic outline of the code using Python:

                import RPi.GPIO as GPIO
                import time
                import requests
                from gps import *
                from Adafruit_DHT import DHT22
                from mpu6050 import mpu6050

                # Configuration
                GPS_PORT = "/dev/ttyS0"
                DHT_SENSOR_PIN = 4
                MPU6050_ADDRESS = 0x68
                CLOUD_URL = "https://api.thingspeak.com/update?api_key=YOUR_API_KEY"

                # Setup
                GPIO.setmode(GPIO.BCM)
                dht_sensor = DHT22(DHT_SENSOR_PIN)
                mpu = mpu6050(MPU6050_ADDRESS)
                gpsd = GPS(GPS_PORT)

                def get_sensor_data():
                    humidity, temperature = dht_sensor.read()
                    accelerometer_data = mpu.get_accel_data()
                    return temperature, humidity, accelerometer_data

                def send_data_to_cloud(temperature, humidity, accelerometer_data):
                    payload = {
                        "field1": temperature,
                        "field2": humidity,
                        "field3": accelerometer_data['x'],
                        "field4": accelerometer_data['y'],
                        "field5": accelerometer_data['z']
                    }
                    response = requests.get(CLOUD_URL, params=payload)
                    print(f"Data sent to cloud: {response.status_code}")

                try:
                    while True:
                        temperature, humidity, accelerometer_data = get_sensor_data()
                        print(f"Temperature: {temperature} C, Humidity: {humidity} %, Acceleration: {accelerometer_data}")
                        send_data_to_cloud(temperature, humidity, accelerometer_data)
                        time.sleep(60)  # Adjust as necessary for your application

                except KeyboardInterrupt:
                    GPIO.cleanup()
            

This code reads data from the temperature and humidity sensor, accelerometer, and sends it to the cloud. You can modify it to include additional features or improve data accuracy as needed.

Setting Up Cloud Integration

To monitor and analyze the data from the helmet, integrate the system with a cloud service. Configure the cloud service to receive data from the Raspberry Pi and set up dashboards or alerts based on the data received from the helmet.

Testing and Calibration

Test the helmet's sensors and data transmission by simulating different environmental conditions and movements. Ensure that the data is accurately recorded and transmitted to the cloud. Adjust the sensor settings and code parameters as needed for reliable performance.