A Health Monitoring System For Mine Truck Drivers And A Method Thereof

Abstract

The present invention is related to a health monitoring system for mine truck drivers. The health monitoring system for mine truck drivers integrates advanced components to enhance driver safety in hazardous environments. It features control units, including Arduino Mega (110), Arduino Uno, and NodeMCU, which process data from various input sensors, such as the MAX30100 Pulse Oximeter (121) and multiple gas sensors (MQ2 (123), MQ3 (124), and MQ135 (125)). The system utilizes output actuators, including buzzers (130) and LCD displays (160), to alert drivers and management when predefined thresholds are exceeded. An air quality control unit equipped with a CPU fan expels hazardous gases, while a servo motor (150) releases oxygen when critical health parameters are detected. Continuous monitoring of health metrics is transmitted via nRF24L01 (171) and GSM Module (172) to cloud platforms like ThingSpeak (173) for real-time analysis. The IoT-based alert system ensures timely notifications through visual and auditory signals.

Specification

Description:The present invention is related to an Arduino based health monitoring system for mine truck drivers. Figure 1 illustrates the schematic of thehealth monitoring system. The health monitoring system (100) designed for mine truck drivers represents a significant advancement in ensuring safety and well-being in hazardous working environments. This comprehensive system integrates multiple technological components to create a robust framework for real-time health and air quality monitoring. Central to the system's functionality are the control units-Arduino Mega, Arduino Uno, and NodeMCU (110)-which process incoming data from various sensors. These microcontrollers are capable of handling complex calculations and logic, allowing for swift decision-making based on real-time data analysis.
The sensing unit (120) is a crucial element of this system, comprising an array of specialized sensors. The MAX30100 Pulse Oximeter (121) measures the blood oxygen saturation (SpO2) levels of the driver, providing insights into respiratory health. The DS18B20 Temperature Sensor (122) tracks the driver's body temperature, identifying potential fever or other health anomalies. To monitor air quality, the system incorporates several gas sensors, including the MQ2 and MQ3 (123), which detect flammable gases and smoke, as well as the MQ135 Gas Sensor (124), which is sensitive to a wide range of air contaminants such as carbon dioxide and volatile organic compounds. Additionally, the DHT11 Humidity Sensor (125) provides essential data on cabin humidity, contributing to a comprehensive environmental assessment. Together, these sensors allow the system to monitor both the driver's health and the conditions inside the cabin, enabling proactive measures to ensure safety.
To alert the driver and management effectively when any monitored parameter exceeds predefined thresholds, the system utilizes various output actuators. The buzzers (130) emit audible alarms, while LEDs (140) provide visual signals to attract attention. The LCD display (160) presents real-time data in a user-friendly format, allowing drivers to easily comprehend their health status and the air quality of their environment. This multi-faceted alert system ensures that both drivers and fleet management are informed of any potential risks, thereby facilitating prompt action when necessary.
The wireless communication system (170), incorporating an nRF24L01 Transceiver (171) and a GSM Module (172), is integral for data transmission to a cloud platform, such as ThingSpeak (173). This feature enables remote monitoring and analysis of the gathered data, allowing fleet management to keep track of air quality and driver health in real time, regardless of their location. This capability enhances decision-making, as management can access critical information and respond swiftly to any emerging issues, thereby reducing risks associated with poor air quality and health conditions.
The system goes beyond mere monitoring; it actively manages the cabin environment to safeguard the driver. The air quality control unit is equipped with a CPU fan that automatically activates when gas levels, as detected by the MQ135, MQ2, and MQ3 sensors, exceed safe limits. This proactive measure helps expel hazardous gases, thereby improving the air quality inside the cabin. In addition, when critical health parameters are detected-such as low SpO2 levels or elevated body temperature-the system actuates a servo motor to release oxygen into the cabin, providing an immediate and life-saving response.
The NodeMCU and GSM Module enable the development of an Internet of Things (IoT) based alert system, allowing for seamless communication between the driver and fleet management. When health or air quality parameters deviate from normal levels, the system generates notifications that are delivered through multiple channels, including visual (LCD), auditory (buzzer), and remote alerts via the cloud. This ensures that both the driver and management are kept informed in a timely manner, significantly enhancing the overall safety and health management framework.
The data processing capabilities of the Arduino Mega are crucial, as it receives and interprets sensor data transmitted through the nRF24L01 module. This microcontroller not only processes the information but also triggers the output actuators, such as buzzers, LEDs, and the servo motor, based on predefined safety thresholds. This rapid response capability ensures that any health and air quality changes are addressed immediately, significantly reducing the risk of adverse health outcomes for drivers operating in challenging mining environments. In summary, this health monitoring system provides a comprehensive solution for ensuring the safety and health of mine truck drivers, combining real-time monitoring, proactive environmental management, and effective communication to create a safer working atmosphere. A health monitoring system for mine drivers utilizing IoT technology has been developed to enhance safety and well-being. This system integrates modern sensors with an Arduino and ESP8266 NodeMCU to continuously monitor critical health information, including pulse rate, SpO2 levels, and body temperature of the driver connected to the device. In the event of any unexpected changes in the driver's health metrics, the IoT technology swiftly records, transmits, and alerts both the driver and management. Additionally, it uploads the data to the ThingSpeak cloud platform, enabling remote access for continuous monitoring of the driver's health characteristics from any location.
The sensor data is transmitted through the nRF module and GSM network, ensuring real-time communication. The information is then uploaded to ThingSpeak, which serves as a storage and data analysis platform, allowing for efficient tracking and assessment of the driver's health over time. This comprehensive approach significantly improves the ability to respond promptly to health-related issues in challenging mining environments.
An embedded system is a specialized type of computer designed to perform specific tasks, such as accessing, processing, storing, and controlling data within various electronics-based systems. These systems integrate both hardware and software components, with the software, often referred to as firmware, embedded directly into the hardware. A defining characteristic of embedded systems is their ability to provide outputs within defined time constraints, which enhances precision and convenience in their operations. As a result, embedded systems are widely utilized in a range of devices, from simple household items like microwaves and calculators to more complex applications such as home security systems and traffic control mechanisms.
Embedded systems can be broadly categorized into two main components: hardware and software. The software for embedded systems is tailored to perform specific functions, typically written in high-level programming languages. This software is then compiled into code that resides in non-volatile memory within the hardware. When developing embedded system software, three critical factors must be considered: the availability of system memory, the processing speed of the microcontroller or microprocessor, and the need for power management, particularly because many embedded systems run continuously. Minimizing power dissipation during operations such as stopping, running, and waking up is essential for maintaining system efficiency.
The hardware platform is equally crucial for the operation of an embedded system. Typically built around a microprocessor or microcontroller, embedded system hardware consists of several essential components, including a power supply to provide energy, a processor to execute the embedded software, and memory to store data and code. Additionally, timers manage time-based operations, serial communication ports facilitate data exchange with other devices, and input/output circuits allow interaction with external systems. There may also be application-specific circuits designed for particular tasks or functions.
To ensure an embedded system functions properly, the integration of its software and hardware is critical. This integration involves writing source code that must be uploaded to a microprocessor or microcontroller, which will then execute the code to perform the necessary operations. Although source code for embedded systems is often written in assembly language, it must ultimately be compiled into executable files through a structured process. This process includes compiling each source file into an object file, linking all object files to produce a relocatable program, and assigning physical memory addresses to the program in a step known as relocation. The end result is an executable binary image ready for deployment on the embedded system.
The implementation of an embedded system follows a systematic flow, starting with identifying existing problems and developing solutions based on the basic requirements of the system. The next stage involves determining the hardware needs, which includes selecting essential components such as the microcontroller, inputs like sensors, and outputs like relays or loads. After assessing the hardware, the software requirements are evaluated based on the chosen microcontroller, utilizing various tools for coding, compiling, and debugging. Once the software is developed and tested, it is uploaded to the microcontroller, and all input and output modules are connected according to the system's specifications. This structured approach enables the creation of an effective embedded system that meets specific needs and enhances operational efficiency.
Figure 2 illustrates the control unit (110) with Arduino Mega (111), Arduino Uno (112), and NodeMCU (113) for processing data. The ATmega2560 microcontroller plays a crucial role in microcontroller boards such as the "Arduino Mega." This microcontroller features 54 digital input/output pins, with 16 designated for analog inputs and 14 capable of functioning as PWM outputs. Additionally, it incorporates four hardware serial ports (UARTs), a 16 MHz crystal oscillator, an ICSP header, a power jack, a USB port, and a reset (RST) button. Essentially, the Arduino Mega board contains all necessary components to support the ATmega2560 microcontroller, allowing for various power supply options. Users can power the board via a USB connection to a PC, a battery, or an AC-DC adapter. To safeguard the board from unexpected electrical discharges, a base plate can be utilized.
The Arduino Uno is another microcontroller board developed by Arduino.cc, an open-source electronics platform primarily based on the AVR microcontroller Atmega328. The inception of the first Arduino project took place in 2003 at the Interaction Design Institute Ivrea, led by David Cuartielles and Massimo Banzi. Their aim was to create an affordable and flexible solution for students and professionals to control various devices in the real world. The current version of the Arduino Uno includes a USB interface, six analog input pins, and 14 digital input/output (I/O) ports for connecting external electronic circuits. Among the 14 I/O ports, six can be utilized for PWM output, enabling designers to interact with external electronic devices. The board encompasses all necessary features for operating the controller, facilitating a direct USB connection to a computer for code transfer via the Integrated Development Environment (IDE) software. This IDE is compatible with Windows, macOS, and Linux systems, although Windows is typically the preferred platform. Programming in the IDE is done using languages like C and C++. Apart from USB connectivity, the Arduino Uno can also be powered by batteries or an AC to DC adapter.Arduino Uno boards share similarities with other boards in the Arduino family regarding usage and functionality. However, Uno boards do not include an FTDI USB to Serial driver chip. Numerous versions of Uno boards exist, with Arduino Nano V3 and Arduino Uno being the most recognized versions that feature the Atmega328 8-bit AVR Atmel microcontroller and 32KB of RAM. When tasks become complex, a Micro SD card can be incorporated into the boards to enhance storage capacity. The Arduino Uno is based on the Atmega328 AVR microcontroller, which offers 2KB of SRAM, 32KB of flash memory, and 1KB of EEPROM. The board contains 14 digital pins and six analog pins, utilizing an on-chip ADC for sampling. Additionally, a 16 MHz frequency crystal oscillator is present on the board.
The Arduino Uno has a wide array of applications and is popular among users for developing sensors and instruments for scientific research. Notable applications include embedded systems, security and defense systems, digital electronics and robotics, parking lot counters, weighing machines, traffic light countdown timers, medical instruments, emergency lights for railways, home automation, and industrial automation.
Figure 3 illustrates the components of sensing unit (120). The MAX30100 is a pulse oximeter and heart rate sensor module designed for I2C communication. It is a low-power, plug-and-play biometric sensor developed by Analog Devices. This modern integrated IC combines two LEDs, a photodetector, optimized optics, and low-noise analog signal processing to accurately detect pulse oximetry (SpO2) and heart rate (HR) signals, making it capable of measuring blood oxygen levels and heart rates.
The DS18B20 is a temperature sensor that provides accurate temperature readings with minimal hardware and wiring requirements. It utilizes a digital protocol to transmit temperature data directly to the development board. Testing of the DS18B20 sensor can be performed by holding the sensor's end, with temperature readings displayed on an LCD in Celsius. This sensor's accuracy and simplicity render it a preferable option compared to traditional temperature sensors like the LM35. It features user-programmable upper and lower trigger points that are non-volatile, operates within a temperature range of -55°C to +125°C, and achieves an accuracy of 0.5°C from 10°C to 85°C.
Gas sensors, such as the MQ2, are essential tools for monitoring air pollution. The MQ2 sensor can be employed to create gas leakage detectors that identify hazardous gas leaks, alerting users to potential dangers. It effectively detects concentrations of LPG, smoke, propane, hydrogen, methane (CH4), and carbon monoxide (CO) within a range of 200 to 10,000 ppm.
The MQ3 alcohol gas sensor specializes in detecting alcohol gas concentrations in the air. It is effective for identifying various substances, including alcohol, benzene, CH4, hexane, LPG, and carbon monoxide (CO). Renowned for its high sensitivity and quick response time, the MQ3 sensor can deliver readings within a concentration range of 25 to 500 ppm.
The MQ-135 air quality gas sensor module is utilized to detect smoke, benzene, vapors, and other harmful gases. When gas levels exceed a predetermined threshold, the digital pin will go high. This sensor can identify a variety of dangerous gases, making it suitable for air quality monitoring, pollution detection, and industrial applications. It has a detection range of 10 to 1,000 ppm for gases such as ammonia, toluene, hydrogen, and smoke.
The DHT-11 digital temperature and humidity sensor is an affordable, ultra-low-cost sensor known for its reliability and stability. Utilizing advanced digital signal acquisition techniques, it incorporates two components to measure temperature and humidity: a resistive-type humidity measurement element and an NTC temperature measurement component. The DHT-11 sensor offers excellent quality, rapid response, and resistance to interference. It communicates over a single-wire digital connection, providing temperature readings in degrees Celsius and relative humidity values as a percentage (20% to 90% RH).
Figure 4 illustrates wireless communication system (170).NodeMcu is an open-source firmware and development kit that plays a vital role in designing IoT products using minimal Lua script lines. The board features multiple GPIO pins that allow connectivity with various peripherals and support PWM, I2C, SPI, and UART serial communications. The module's interface consists of two parts: firmware, which operates on the ESP8266 Wi-Fi SoC, and hardware, based on the ESP-12 module. The firmware utilizes Lua, an easy-to-learn scripting language, providing a simple programming environment enhanced by a robust developer community. Open-source firmware allows for editing, modifying, and rebuilding the existing module, offering the flexibility to adjust the interface until optimal functionality is achieved.
The NodeMcu board is equipped with a number of GPIO pins. The distinction between VIN and VU is significant; VIN is the regulated voltage, typically between 7 to 12 V, while VU is the USB power voltage, which should be maintained at around 5 V. NodeMcu V3 is primarily utilized for Wi-Fi applications that other embedded modules cannot process unless integrated with an external Wi-Fi protocol. Major applications for NodeMcu V3 include Internet smoke alarms, VR trackers, serial port monitors, ESP lamps, incubator controllers, IoT home automation, and security alarms.A GSM modem is a device that can either be a mobile phone or a modem enabling a computer or other processors to communicate over a network. To operate, a GSM modem requires a SIM card and functions within the network range provided by the service operator. It can be connected to a computer via serial, USB, or Bluetooth connections. A GSM modem can also refer to a standard GSM mobile phone equipped with the appropriate cable and software driver for connection to a computer's serial or USB port. Typically, GSM modems are preferred over GSM mobile phones and have a wide range of applications, including transaction terminals, supply chain management, security applications, weather stations, and remote data logging in GPRS mode.
The nRF24L01 is an ultra-low power RF transceiver IC operating in the 2.4GHz ISM band, offering a data rate of 2Mbps. It features a genuine SPI interface, several pipelines, and a hardware link layer, enhancing its functionality compared to the nRF2401. The SPI (Serial Peripheral Interface) protocol facilitates device-to-device communication between a master and a slave device. Various modules, including sensors and displays, operate as slaves under microcontroller control, submitting data upon receiving a request from the master. The RF transceiver wirelessly receives serial information and transmits it through RF using its antenna, with data received by an RF receiver tuned to the same frequency as the transmitter.
The MAX30100 is a pulse oximeter and heart rate sensor module designed for I2C communication. It is a low-power, plug-and-play biometric sensor developed by Analog Devices. This modern integrated IC combines two LEDs, a photodetector, optimized optics, and low-noise analog signal processing to accurately detect pulse oximetry (SpO2) and heart rate (HR) signals, making it capable of measuring blood oxygen levels and heart rates.
Two prominent aspects of Embedded Programming are code speed and code size. Code speed is influenced by processing power and timing constraints, while code size is determined by available program memory and the programming language used. The primary goal of embedded system programming is to maximize functionality within limited space and minimum processing time. In the context of the patient monitoring system, efficient coding practices will be essential to ensure real-time data analysis and prompt alerts for any detected abnormalities. Embedded systems can be programmed using various types of languages, including machine code, low-level languages like assembly, high-level languages such as C, C++, and Java, as well as application-level languages like Visual Basic, scripts, and Access. For the real-time patient monitoring system, high-level languages like C or C++ may be utilized to facilitate the development of complex algorithms needed for biometric analysis and gesture recognition.
The software utilized by Arduino Uno is known as the Arduino IDE (Integrated Development Environment). This platform facilitates writing code, checking for errors during compilation, and uploading the code to the Arduino Uno. The Arduino IDE consists of several sections that provide a comprehensive programming environment, making it a valuable tool for developing the real-time patient monitoring system.This multi-platform software is compatible with various operating systems, including Windows, Linux, and macOS, and it supports the C/C++ programming language. Being open-source, users can modify and utilize the software as they see fit, including integrating their own modules and functions. When a user writes and compiles code for the patient monitoring system, the IDE generates a Hex file that is transmitted to the Arduino board via a USB cable. Each Arduino board is equipped with a microcontroller that receives this hex file and executes the instructions according to the code written. This capability allows the patient monitoring system to effectively process and respond to real-time health data.
ThingSpeak is an IoT analytics platform that enables users to aggregate, visualize, and analyze live data streams in the cloud. Users can send data to ThingSpeak from various devices, including Arduino, Raspberry Pi, and others. The platform allows for instant graphical visualizations of live data and the capability to send alerts. For the patient monitoring system, leveraging the ThingSpeak platform can enhance the way health data is managed and presented.To use the ThingSpeak platform, users must create an account and select a channel associated with that account. The platform provides an API key to facilitate the transfer of sensor data to ThingSpeak, which is managed within the microcontroller program. ThingSpeak plays a critical role in continuously updating data by providing APIs for collecting data generated by sensors as well as APIs for retrieving that data through applications. This functionality is particularly valuable for the real-time patient monitoring system, as it enables the continuous streaming of biometric data to a centralized platform for analysis and alert generation. Additionally, the platform leverages MATLAB's capabilities to analyze the transmitted IoT data, allowing users to run IoT analytics automatically based on predefined schedules or events. This feature can be crucial for developing predictive analytics capabilities within the patient monitoring system, helping healthcare providers respond proactively to potential health issues. By integrating the Arduino IDE and ThingSpeak platform, the real-time patient monitoring system can achieve greater efficiency, flexibility, and responsiveness, ultimately enhancing patient care.
Figure 5 illustrates the method of working of the monitoring system. A method for monitoring health using the system involves several systematic steps. First, the sensing unit gathers real-time data related to the driver's health and the conditions within the cabin. This data is then transmitted wirelessly to the control unit via the nRF24L01 Transceiver, which is connected to the Arduino Mega. The Arduino Mega plays a crucial role in processing the collected sensor data and comparing it to predefined thresholds established for various health and environmental metrics.
When any metric exceeds the set threshold, a buzzer is activated to alert the driver, while the abnormal status is displayed on LCD screens located inside the truck cabin. Additionally, in response to critical health warnings or the presence of dangerous gas levels, the system employs a Servo Motor to release oxygen within the cabin, thereby enhancing the driver's safety. Furthermore, a Relay activates the CPU fan to eliminate hazardous gases from the cabin environment.
To facilitate remote monitoring, the GSM Module transmits real-time data to the ThingSpeak cloud platform. This connectivity ensures that management personnel receive alerts via IoT whenever thresholds are breached, allowing for timely intervention and action. Through this comprehensive method, the health monitoring system enhances the safety and well-being of drivers in various operational conditions.
, Claims:We claim
1. A health monitoring system for mine truck drivers, the system comprising:
a) A control unit (110) with Arduino Mega (111), Arduino Uno (112), and NodeMCU (113) for processing data;
b) A sensing unit (120) consisting of input sensors including MAX30100 Pulse Oximeter (121), DS18B20 Temperature Sensor (122), MQ2, MQ3 (123), and MQ135 Gas Sensors (124), and a DHT11 Humidity Sensor (125);
c) Output actuators comprising buzzers, (130) LEDs (140), servo motors (150), and an LCD display (160) for alerting the driver and management when any sensor exceeds predefined thresholds; and
d) A wireless communication system (170) including nRF24L01 Transceiver (171) and GSM Module (172) for transmitting real-time data to a cloud platform such as ThingSpeak (173) and enabling remote monitoring.
2. The system of claim 1, wherein the air quality control unit is equipped with a CPU fan and integrated with MQ135, MQ2, and MQ3 Gas Sensors, which continuously monitor cabin air quality, automatically activating the CPU fan to expel hazardous gases when gas levels exceed safe limits.
3. The system of claim 1, wherein a servo motor is actuated to release oxygen into the truck cabin when critical health parameters, such as low SpO2 levels or elevated body temperature, are detected from the MAX30100 Pulse Oximeter or DS18B20 Temperature Sensor, ensuring immediate response to driver health risks.
4. The system of claim 1, wherein sensor data, including pulse rate, SpO2 levels, temperature, humidity, and gas levels, is transmitted through nRF24L01 and GSM Module to a cloud platform (ThingSpeak), allowing continuous real-time data monitoring and analysis for remote access by management.
5. The system of claim 1, wherein the NodeMCU and GSM Module facilitate an IoT-based alert system that notifies both the driver and management when health or air quality parameters exceed normal levels, providing visual (LCD), auditory (buzzer), and remote alerts via the cloud.
6. The system of claim 1, wherein the Arduino Mega receives data from the sensing unit via the nRF24L01 transmitter, processes it, and triggers the output actuators, such as buzzers, LEDs, and the servo motor, based on predefined safety thresholds, ensuring an immediate response to health and air quality changes in the truck cabin.
7. A method of monitoring the health using the system as claimed in claim 1; the method comprises:
(a) The sensing unit gather real-time data on driver health and cabin conditions;
(b) The sensing unit, connected to Arduino Mega, transmits the collected data wirelessly via the nRF24L01 Transceiver to the control unit;
(c) The Arduino Mega processes the sensor data and compares it to predefined thresholds;
(d) A buzzer alerts the driver, and the abnormal status is displayed on LCD screens inside the truck cabin when any health or environmental metric exceeds the threshold;
(e) The Servo Motor releases oxygen inside the cabin when dangerous gas levels or critical health warnings are detected;
(f) The Relay activates the CPU fan to remove hazardous gases from the cabin;
(g) The GSM Module transmits real-time data to the ThingSpeak cloud platform for remote monitoring; and
(h) Management receives alerts via IoT when thresholds are breached for real-time action.

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