Raspberry Pi Based Voice Controlled Smart Wheelchair

Karim, A. B. M. F.; Haq, Ahtesham ul; Noor, Aqib; Khan, Burhan; Hussain, Zakir

doi:10.1109/icetst55735.2022.9922929

Cited by 3 publications

(2 citation statements)

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“…Automation in monitoring and managing ponds can be a solution to optimize resources and costs in fish farming processes. Research by Karim et al [5] developed a prototype for monitoring pH, temperature, and water level in fish ponds. However, in that prototype, actuator control was still manually controlled, limiting automatic pond management.…”

Section: Related Workmentioning

confidence: 99%

Design and development smart aquaculture in freshwater pond based on fuzzy logic

Pitowarno,

Oktavianto Leksono,

Budi Utomo

et al. 2023

BIO Web Conf.

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This research has the topic of Smart Aquaculture in freshwater ponds. Aquaculture or fish farming in Indonesia still monitors and manages ponds manually. Temperature, pH, and water turbidity are important parameters for the survival of fish in ponds. Therefore, it is necessary to design a tool that can monitor and control ponds automatically. This system worked by reading the pH, temperature, and water turbidity sensors. The microcontroller utilized the sensor readings to control the peristaltic pump for liquid pH, water pump, and valve operations. Subsequently, the sensor readings were transmitted to the ESP32, which further forwarded the sensor data to the cloud database. Applications that were integrated with the cloud database display sensor reading data. The system utilized Fuzzy Logic Control with the Mamdani method to automate its operation. The inputs for the fuzzy logic control included pH, temperature, and turbidity, while the outputs consisted of the peristaltic pump, valve, and water pump. This system successfully adjusts the control conditions of temperature 35°C, pH 5, and turbidity 1200 NTU, bringing them back to the normal setpoint, which is a temperature of 32°C, pH between 6-8, and turbidity of 150 NTU, and maintains them at these values.

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Section: Related Workmentioning

confidence: 99%

Design and development smart aquaculture in freshwater pond based on fuzzy logic

Pitowarno,

Oktavianto Leksono,

Budi Utomo

et al. 2023

BIO Web Conf.

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show abstract

“…A growing body of research is dedicated to the application of artificial intelligence technologies to modify power wheelchairs to improve the quality of life of people with ALS. In the past few decades, researchers have carried out corresponding research on wheelchair motion control methods, including gesture control [1][2][3][4][5], voice control [6][7][8][9][10], eye-tracking control [11][12][13][14][15], and brain-computer interfaces [16][17][18][19][20][21][22]. These control methods can replace the rocker to complete the reading of the user's motion direction intention and realize the motion control of the wheelchair.…”

Section: Introductionmentioning

confidence: 99%

Eye-Gaze Controlled Wheelchair Based on Deep Learning

Huang

Liu

et al. 2023

Sensors

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In this paper, we design a technologically intelligent wheelchair with eye-movement control for patients with ALS in a natural environment. The system consists of an electric wheelchair, a vision system, a two-dimensional robotic arm, and a main control system. The smart wheelchair obtains the eye image of the controller through a monocular camera and uses deep learning and an attention mechanism to calculate the eye-movement direction. In addition, starting from the relationship between the trajectory of the joystick and the wheelchair speed, we establish a motion acceleration model of the smart wheelchair, which reduces the sudden acceleration of the smart wheelchair during rapid motion and improves the smoothness of the motion of the smart wheelchair. The lightweight eye-movement recognition model is transplanted into an embedded AI controller. The test results show that the accuracy of eye-movement direction recognition is 98.49%, the wheelchair movement speed is up to 1 m/s, and the movement trajectory is smooth, without sudden changes.

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A Computer Vision-Based Eye-Tracking System Toward an Eye-Controlled Powered Wheelchair

Tran,

Nguyen

2024

Lecture Notes in Networks and Systems

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Raspberry Pi Based Voice Controlled Smart Wheelchair

Cited by 3 publications

References 0 publications

Design and development smart aquaculture in freshwater pond based on fuzzy logic

Design and development smart aquaculture in freshwater pond based on fuzzy logic

Eye-Gaze Controlled Wheelchair Based on Deep Learning

A Computer Vision-Based Eye-Tracking System Toward an Eye-Controlled Powered Wheelchair

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