Development of an Intelligent Quadcopter Using Smartphone Sensor Technology

Trishul Singh Sisodiya; Yuvank Soni; Shivani Nayak

doi:10.69968/ijisem.2026v5i3585-602

Authors

Trishul Singh Sisodiya Department of Electronics and Communication, Lakshmi Narain College of Technology, Bhopal, 462023, M.P, India.
Yuvank Soni Department of Electronics and Communication, Lakshmi Narain College of Technology, Bhopal, 462023, M.P, India.
Shivani Nayak Department of Electronics and Communication, Lakshmi Narain College of Technology, Bhopal, 462023, M.P, India.

DOI:

https://doi.org/10.69968/ijisem.2026v5i3585-602

Keywords:

Smartphone-Based Drone, Quadcopter System, ESP32, Mobile Sensor Integration, GPS Navigation, Wireless Communication, Autonomous Flight, Real-Time Monitoring

Abstract

This paper presents the design of a smartphone-based quadcopter in which a smartphone acts as the main processing, sensing and communication unit. Instead of relying on several separate onboard sensors and a conventional flight controller, the system makes use of the smartphone's pre-installed accelerometer, gyroscope, magnetometer, GPS, barometer, camera, Wi-Fi and Bluetooth for sensing, navigation, data processing and wireless communication. Flight commands generated by the smartphone are transmitted to an ESP32 microcontroller through Bluetooth or Wi-Fi. The ESP32 then produces PWM signals to control the Electronic Speed Controllers (ESCs), which drive the four brushless DC motors of the quadcopter. The drone is built on a lightweight X-shaped frame with a motor-to-motor distance of 450–500 mm and an overall weight of approximately 700–1000 g. By using the capabilities already available in modern smartphones, the design decreases hardware requirements, lowers overall cost and simplifies the drone architecture while still supporting functions such as GPS-based navigation, wireless control and object monitoring. The offered design proposes a low-cost, lightweight and simplified drone structure by using the smartphone's integral capabilities, reducing the need for dedicated hardware. This approach lets easier development, improved scalability and supports advanced applications such as independent navigation, real-time monitoring and aerial surveillance.

References

Smartphone-Based Quadcopter / Main Research References

[1] R. M. Hayajneh, M. Melega and L. Marconi, “Design of autonomous smartphone based quadrotor and implementation of navigation and guidance systems,” Mechatronics, vol. 49, pp. 119–133, 2018.Paper / ScienceDirect

[2] Astudillo, B. Bacca and E. Rosero, “Optimal and Robust Controllers Design for a Smartphone-based Quadrotor,” in Proc. 2017 IEEE 3rd Colombian Conference on Automatic Control (CCAC), 2017. Paper information

[3] Astudillo et al., “Altitude and attitude cascade controller for a smartphone-based quadcopter,” in Proc. IEEE Conference, 2017. This work specifically investigates using smartphone sensors and processor for quadcopter attitude and altitude control.Research paper page

[4] P. Caliston, C. J. G. Aliac and J. A. E. Nogra, “Quadcopter Position Hold Function using Optical Flow in a Smartphone-based Flight Computer,” 2025. Paper on arXiv

[5] X. Zhang et al., “Real-Time UAV Autonomous Localization Based on Smartphone Sensors,” Sensors, vol. 18, no. 12, 4161, 2018. MDPI Sensors paper

Smartphone Sensor References

[6] Google Android Developers, “Sensors Overview,” Android Developers. This provides official information about accelerometers, gyroscopes, magnetic-field sensors, pressure sensors and other Android sensor types. Android Sensors Overview

[7] Google Android Developers, “About Sensors and Location,” Android Developers. The documentation describes Android motion, position, environmental sensors and location/GPS capabilities. Android Sensors and Location

[8] Google Android Developers, “Motion Sensors,” Android Developers. This source explains accelerometer and gyroscope operation and their use for monitoring device motion and rotation. Android Motion Sensors

[9] Google Android Developers, “Position Sensors,” Android Developers. This documentation explains the use of geomagnetic sensors and accelerometers for determining device orientation and position. Android Position Sensors

[10] Google Android Developers, “Sensor API Reference,” Android Developers. It provides technical definitions for sensor types including accelerometer, gyroscope, magnetic field, pressure, proximity and rotation-vector sensors. Android Sensor API Reference

ESP32 / Communication References

[11] Espressif Systems, ESP32 Series Datasheet, Espressif Systems. The datasheet provides technical specifications for ESP32 Wi-Fi, Bluetooth, GPIO, UART, SPI, I²C, PWM, processor, memory and motor-control capabilities. Official ESP32 Datasheet

[12] Espressif Systems, ESP32-WROOM-32E and ESP32-WROOM-32UE Datasheet, Espressif Systems. It provides specifications for Wi-Fi, Bluetooth, antenna options, GPIO, PWM and communication interfaces. ESP32-WROOM Datasheet

Additional Reference for Smartphone + UAV Concept

[13] D. A. H. M. Hayajneh et al., “A review on drones controlled in real-time,” International Journal of Dynamics and Control, 2020. The review discusses smartphone-based UAV control and the use of smartphone-integrated sensors and processors in drone systems. Review paper

[14] R. Turner et al., “A Grassroots Remote Sensing Toolkit Using Live Coding, Smartphones, Kites and Lightweight Drones,” PLOS/PMC, 2016. The study discusses using smartphone cameras, GPS, accelerometers, compass and processing capabilities on lightweight aerial platforms. Full research paper

[15] J. S. Kim et al., “Feasibility of employing a smartphone as the payload in a photogrammetric UAV system,” ISPRS Journal of Photogrammetry and Remote Sensing, vol. 79, pp. 1–18, 2013. The work evaluates smartphone-based UAV systems using pre-installed imaging, location and attitude information.

Sensor Fusion and Flight Control

[16] Koksal, M. Jalalmaab and B. Fidan, “Adaptive linear quadratic attitude tracking control of a quadrotor UAV based on IMU sensor data fusion,” Sensors, vol. 19, no. 1, Art. no. 46, 2019.

[17] R. Mahony, T. Hamel and J.-M. Pflimlin, “Nonlinear complementary filters on the special orthogonal group,” IEEE Transactions on Automatic Control, vol. 53, no. 5, pp. 1203–1218, Jun. 2008.

[18] G. Hoffmann, H. Huang, S. Waslander and C. Tomlin, “Quadrotor helicopter flight dynamics and control: Theory and experiment,” in Proc. AIAA Guidance, Navigation and Control Conference, 2007.

Wireless Communication

[19] Bluetooth Special Interest Group, Bluetooth Core Specification, Bluetooth SIG. [Online]. Available: Bluetooth Core Specification

[20] Espressif Systems, “Bluetooth LE and Bluetooth,” ESP32 Technical Documentation. [Online]. Available: ESP32 Bluetooth Documentation