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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM63333
Volume:
10 |
5 |
May 2026
Pages:
1-7
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Department of Electrical & Electronics Engineering
Ilahia College of Engineering & Technology, Mulavoor
Department of Electrical & Electronics Engineering
Ilahia College of Engineering & Technology, Mulavoor
Department of Electrical & Electronics Engineering
Ilahia College of Engineering & Technology, Mulavoor
Department of Electrical & Electronics Engineering
Ilahia College of Engineering & Technology, Mulavoor
A foldable, portable electric bicycle equipped with an automated fall-detection and alerting system is presented to deliver a compact, energy-efficient, and low-cost urban transport solution. The design centres on a hinge-based folding mechanism that minimizes storage footprint and eases handling and portability, enabling convenient carriage and stowage in constrained environments. Propulsion is provided by a brushless DC (BLDC) hub motor powered by a Lithium Iron Phosphate (LiFePO4) battery, selected for its favourable safety profile, extended cycle life, and reliable energy delivery; the drive train includes a motor controller, throttle, pedal-assist sensor, brake cut-off switch, headlight, horn, and a 26-inch wheel bicycle frame. A pedal-assist feature permits human-powered operation when electric energy is unavailable, enhancing operational flexibility and overall energy efficiency. The BLDC hub motor offers high efficiency, smooth torque delivery, and reduced maintenance compared with conventional brushed or chain-driven alternatives, while the LiFePO4 chemistry reduces thermal and fire risks relative to other lithium-ion variants. Rider safety is augmented by an embedded fall-detection system comprising an MPU6050 inertial measurement unit (IMU), an Arduino Nano microcontroller, and a SIM800L GSM modem. The IMU continuously measures angular velocity and acceleration to monitor vehicle orientation and detect abnormal tilt or impact signatures; the microcontroller executes a real-time algorithm to differentiate normal dynamic maneuvers from fall events and triggers the alert sequence if a fall is confirmed. On detection, the GSM modem transmits emergency text notifications to predefined contacts, and an audible buzzer provides an immediate local warning. The fall-detection electronics are battery powered and regulated via an LM2596 DC–DC buck converter to ensure stable supply voltages for the sensors, microcontroller, and communication module. System-level advantages include eco-friendly operation through zero tailpipe emissions during electric driving, improved travel efficiency from power-assisted pedaling, a relatively low initial cost enabled by off-the-shelf components and a simple folding mechanism, and enhanced portability afforded by the lightweight frame. The integrated safety subsystem is intended to reduce response time following accidents by enabling rapid remote notification, while the mechanical and electrical choices—BLDC hub drive, LiFePO4 energy storage, and a compact folding architecture—support reliability, reduced maintenance, and daily-commute suitability. Design trade-offs considered include balancing folding-stability and frame stiffness, optimizing controller parameters for smooth pedal-assist transitions, and tuning the fall-detection sensitivity to minimize false positives during normal riding. The overall architecture demonstrates a practical approach to combining compact form factor, efficient propulsion, and rider-protective sensing and communication, making the concept appropriate for short-distance urban mobility where storage constraints, safety, and lifecycle costs are primary concerns.
KEYWORDS
The foldable and portable electric bike with an integrated fall detection system demonstrates a practical and efficient solution for modern urban transportation, combining ecofriendly operation, energy efficiency, and enhanced rider safety. The integration of a BLDC Hub Motor powered by a Lithium Iron Phosphate (LiFePO) battery ensures reliable propulsion, reduced charging time, and consistent performance while maintaining low operational costs. The inclusion of a pedal assist sensor and throttle mechanism allows flexible riding modes, providing riders the option to conserve battery power or travel manually, further enhancing energy efficiency and extending operational range. The foldable frame, designed with a hinge mechanism, addresses space and portability concerns, allowing for convenient storage in compact urban environments or transport in vehicles. The fall detection system, utilizing an MPU6050 gyroscope sensor, Arduino Nano, and SIM800L GSM module, adds a critical safety layer by continuously monitoring the bike’s orientation and tilt. Upon detection of a fall, the system triggers a buzzer alert and sends an emergency SMS notification to predefined contacts, ensuring timely assistance for the rider. The system’s low-power design, regulated with an LM2596 DC-DC Buck Converter, provides reliable performance without significantly impacting battery life. Overall, the proposed electric bike achieves a balance of performance, safety, and practicality. Its eco-friendly propulsion, intelligent safety mechanisms, and foldable design make it highly suitable for urban commuters, students, and individuals seeking efficient personal mobility solutions. Future enhancements, such as rider sleep detection sensors and smart helmet integration, could further improve safety, making the system a comprehensive platform for intelligent and sustainable transportation. The combination of portability, cost-effectiveness, and intelligent features positions this design as a promising solution for next-generation urban mobility.
1 E. Chen et al., “Development of lightweight and foldable frames for electric bicycles,” IEEE Transactions on Industrial Applications, vol. 58, no. 3, pp. 987–995, Mar. 2023 2 D. Zhang and F. Wang, “Design and implementation of a hybrid pedal-assist system for electric bicycles,” IEEE Transactions on Vehicular Technology, vol. 71, no. 1, pp. 234–242, Jan. 2023. 3 E. A. Sa˘gba¸s and S. Ballı, “Elderly fall detection using autoencoder-based dimensionality reduction and smartwatch-based wearable motion detectors,” 2023 4 W. Lu, S. Kumar, M. Sandhu, and Q. Zhang, “An unobtrusive fall detection system using ceiling-mounted ultra-wideband radar,” in Proc. IEEE EMBC, 2023. 5 H. Yhdego, C. Paolini, and M. Audette, “Toward real-time robust wearable sensor fall detection using deep learning methods,” 2023. 6 B. Barshan and M. S. Turan, “A novel heuristic fall-detection algorithm based on double thresholding, fuzzy logic, and wearable motion sensor data,” IEEE Internet of Things Journal, 2023. 7 C. Lee et al., “Comparative study of lithium-ion and LiFePO₄ batteries for electric vehicles,” IEEE Transactions on Energy Conversion, vol. 37, no. 4, pp. 1456–1464, Dec. 2022. 8 A. Patel and B. Singh, “Optimization of BLDC motor controllers for electric bicycle applications,” IEEE Transactions on Power Electronics, vol. 69, no. 2, pp. 1123–1131, Feb. 2022. 9 S. Kumar et al., “Design considerations for lightweight foldable frames in electric bicycles,” IEEE Transactions on Consumer Electronics, vol. 67, no. 4, pp. 5678–5685, Nov. 2021. 10 R. Gupta and P. Sharma, “Auditory alert systems for enhancing safety in electric bicycles,” IEEE Transactions on Intelligent Transportation Systems, vol. 22, no. 7, pp. 4567–4575, Jul. 2021.
Publication Date
5/16/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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The authors declare no conflict of interest related to this research work.
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