Smart Helmet Safety Gear: Enhancing Rider Protection with Intelligent Features
In today’s fast-paced world, accidents caused by drinking and driving continue to be a major concern. Despite various laws aimed at curbing these incidents, many people still disregard them, resulting in serious injuries and fatalities. Although helmets and safety gear are readily available, many riders fail to use them, increasing the risk of accidents. To address these issues, an innovative solution has been developed with two main objectives:
- Ensure riders wear helmets before operating bikes.
- Prevent riding under the influence of alcohol using alcohol detection systems.
This intelligent safety system is designed to prevent riders from starting their bikes if they are under the influence of alcohol. Additionally, in the event of an accident, a fall detection system alerts emergency services. The system is powered by a solar panel integrated into the helmet, ensuring sustainability and continuous power.
Key Components of the Smart Helmet System
- Arduino UNO and NodeMCU: These essential microcontrollers are used for integrating various sensors such as the alcohol sensor, MPU-6050 (for motion detection), and other modules.
- Solar Panel: A small solar panel module with a 0.6W, 6V rating, providing up to 100mA of current in full sunlight, efficiently powers the system.
- DC-DC Boost Converter (XL6009): This device steps up the voltage from 3.7V to 5V, ensuring the system has enough power to function efficiently.
- LiPo Battery 18650: A rechargeable battery (1200mAh capacity, 3.7V output) powers the system, with charging facilitated by a TP4056 LiPo charger.
- TP4056 Lipo Battery Charger: A small module designed to charge 3.7V LiPo batteries, ensuring the system stays powered up.
- Flex Sensor: A variable resistor that detects helmet wear by measuring physical bending, providing input for the system.
- MPU6050 (Motion Sensor): This 6-degree-of-freedom sensor tracks acceleration and gyroscopic movement, essential for gesture and fall detection.
- Ultrasonic Sensor: Detects nearby vehicles, ensuring riders are aware of their surroundings and can avoid accidents.
- Sound Sensor: Detects vehicle horns to alert the rider to nearby vehicles attempting to overtake.
- Alcohol Sensor (MQ3): Detects alcohol vapor in the air and alerts the system if the rider is intoxicated, preventing bike operation.
- LEDs, Resistors, Wires: LEDs act as warning signals, while resistors limit current and ensure efficient operation.
Introduction to the Intelligent Safety System
The smart helmet system operates in two safety stages before the bike can be started:
- Helmet Wear Detection: The flex sensor ensures the rider is wearing a helmet. If the sensor detects that the helmet is not worn, the system prevents the bike from starting.
- Alcohol Detection: Using the MQ3 alcohol sensor, the system checks whether the rider is sober. If the rider is intoxicated, the bike remains disabled.
In addition, the system includes features like gesture detection, fall detection, and environmental awareness, ensuring that the rider stays safe while on the road. The fall detection system uses the MPU6050 to alert emergency contacts in case of an accident. Furthermore, the solar panel continuously charges the LiPo battery, ensuring that the helmet system remains operational for long periods.
System Operation and Implementation
NodeMCU and MPU6050 Integration
The NodeMCU microcontroller interacts with the MPU6050 motion sensor to detect both gestures and falls. The accelerometer’s values are used to calculate the rider’s head movements, and fall detection is triggered when there is a sudden acceleration change.
Arduino-Based Circuitry
The Arduino is responsible for integrating the flex sensor, alcohol sensor, sound sensor, and ultrasonic sensor. Here’s how the system works:
- Helmet Detection: The flex sensor detects if the rider is wearing the helmet.
- Alcohol Detection: The alcohol sensor checks for alcohol levels, ensuring the rider is sober.
- Vehicle Detection: The ultrasonic sensor checks for nearby vehicles, while the sound sensor detects horns, alerting the rider with a visual signal.
Fall Detection Algorithm
The fall detection system uses a 3-trigger mechanism:
- Trigger 1: If acceleration exceeds 12 units, Trigger 2 is activated.
- Trigger 2: If the angle change exceeds 80 degrees, Trigger 3 is activated.
- Trigger 3: If the angle remains unchanged after the fall, the fall is confirmed, and an emergency alert is sent.
Power Supply from Solar Panels
The system is powered by a solar panel, which continuously charges the LiPo battery. The solar energy keeps the system running without needing frequent manual charging. The DC-DC boost converter ensures the circuit receives a stable 5V supply.
Circuit Diagram and PCB Design
Using KiCad, two PCBs were designed for the system:
- One for the power supply and sensor integration.
- Another for communication and data processing.
Testing and Results
The system was tested to ensure functionality:
- Helmet and Alcohol Detection: The flex and alcohol sensors were successfully integrated. When both conditions (helmet worn and sober) were met, the bike’s system was enabled.
- Sound and Ultrasonic Sensors: The sensors were tested by obstructing the ultrasonic sensor and creating noise to activate the sound sensor, which successfully triggered the alarm.
- Fall Detection: The fall detection system worked as expected, triggering an alert with a red light.
Conclusion
The Intelligent Safety Gear system developed for smart helmets significantly enhances rider safety. With features like helmet and alcohol detection, fall detection, environmental awareness, and continuous solar-powered operation, this system offers a robust solution to reduce road accidents and injuries. By integrating advanced sensors and efficient power systems, this smart helmet technology ensures that riders stay safe and alert, even in challenging conditions.