Intelligent Wearable IoT Device for Road Safety with Advanced Gesture Detection via Machine Learning

Abstract

The present invention introduces an intelligent wearable IoT device aimed at improving road safety for vulnerable road users, such as cyclists, motorcyclists, and pedestrians. The device employs advanced gesture recognition powered by machine learning to interpret user movements and intentions in real time. Equipped with sensors such as accelerometers, gyroscopes, and environmental detectors, the device captures motion and contextual data, which is processed using a trained machine learning model for accurate gesture detection and classification. The system enables features like automatic signaling for turns or stops, real-time hazard warnings, and emergency alert notifications to nearby vehicles and traffic management systems. With seamless IoT connectivity, the device facilitates data exchange with smart infrastructure to enhance situational awareness and proactive safety measures. Compact, lightweight, and energy-efficient, this wearable offers an innovative solution for reducing road accidents and ensuring safer mobility in diverse environments.

Specification

Description:The present invention introduces an intelligent wearable IoT device aimed at improving road safety for vulnerable road users, such as cyclists, motorcyclists, and pedestrians. The device employs advanced gesture recognition powered by machine learning to interpret user movements and intentions in real time. Equipped with sensors such as accelerometers, gyroscopes, and environmental detectors, the device captures motion and contextual data, which is processed using a trained machine learning model for accurate gesture detection and classification. The system enables features like automatic signaling for turns or stops, real-time hazard warnings, and emergency alert notifications to nearby vehicles and traffic management systems. With seamless IoT connectivity, the device facilitates data exchange with smart infrastructure to enhance situational awareness and proactive safety measures. Compact, lightweight, and energy-efficient, this wearable offers an innovative solution for reducing road accidents and ensuring safer mobility in diverse environments. , Claims:1. A wearable IoT device for enhancing road user safety, comprising:
• a set of sensors configured to capture motion and gesture data of a road user;
• a processing unit with machine learning capabilities, trained to recognize a set of predefined gestures based on said motion and gesture data;
• visual and audible indicators to provide alerts to the wearer and surrounding road users;
• a proximity sensor to detect nearby vehicles or obstacles;
• a communication module for transmitting data to a central traffic management system; and
• a power source to provide energy to the device.
2. The device of claim 1, wherein the set of sensors includes at least one accelerometer, gyroscope, and proximity sensor.
3. The device of claim 2, wherein the processing unit employs machine learning algorithms to analyze and classify gestures in real-time.
4. The device of claim 2, wherein the visual indicators comprise LEDs or other light sources to signal the intentions of the road user.
5. The device of claim 3, wherein the audible indicators emit sounds or notifications to alert surrounding road users.
6. The device of claim 3, further comprising a data logging capability to record and store motion and gesture data for analysis of road user behavior patterns.
7. A system for enhancing road user safety, comprising a plurality of wearable IoT devices as claimed in claim 1, and a central traffic management system configured to receive and process data transmitted by said devices to optimize traffic control measures.

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