BrightPath: Smart Bike System

This paper presents the design and implementation of BrightPath, an IoT-enabled smart bike system aimed at enhancing cyclist safety and navigation, particularly during nighttime rides. The system integrates real-time navigation, dynamic turn signaling, and LED-based safety boundary projection to improve visibility and communication between cyclists and motorists. The proposed system demonstrates novel embedded system integration by coordinating real-time communication between micro controllers, dynamic sensor-based decision-making, and sustainable power management. Unlike existing solutions, BrightPath features an automated signaling and navigation interface managed by tightly coupled embedded software on both the Arduino and Raspberry Pi platforms. These contributions highlight innovations in multi-controller synchronization, sensor fusion for real-time motion detection, and self-sustaining energy-aware embedded processing.

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Publication Details

Published
2025-05-29
DOI
https://doi.org/10.1109/eit64391.2025.11103676
Primary Topic
Smart Parking Systems Research
Type
article
Field-Weighted Citation Impact
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article

BrightPath: Smart Bike System

Jafar Saniie, M. Gromov, Elizabeth Kindseth, Mungunshagai Bataa et al.
Smart Parking Systems Research
article

BrightPath: Smart Bike System

Jafar Saniie, M. Gromov, Elizabeth Kindseth, Mungunshagai Bataa, Brian Meagher
article en

Abstract

This paper presents the design and implementation of BrightPath, an IoT-enabled smart bike system aimed at enhancing cyclist safety and navigation, particularly during nighttime rides. The system integrates real-time navigation, dynamic turn signaling, and LED-based safety boundary projection to improve visibility and communication between cyclists and motorists. The proposed system demonstrates novel embedded system integration by coordinating real-time communication between micro controllers, dynamic sensor-based decision-making, and sustainable power management. Unlike existing solutions, BrightPath features an automated signaling and navigation interface managed by tightly coupled embedded software on both the Arduino and Raspberry Pi platforms. These contributions highlight innovations in multi-controller synchronization, sensor fusion for real-time motion detection, and self-sustaining energy-aware embedded processing.

Illinois Institute of Technology (US)
Openalex Percentile: Top 78%
Smart Parking Systems Research
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