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Research Article
Performance Assessment of Quantum CNN vs RNN for Medicinal Leaf Classification with UI Sustenance
Issue:
Volume 14, Issue 2, April 2026
Pages:
66-78
Received:
19 February 2026
Accepted:
2 March 2026
Published:
17 March 2026
Abstract: Accurate as well as automated medicinal leaf categorization is a critical chore in medicinal plant species identification. However, manual categorization is time compelling, error prone and mostly reliant on expert skills due to high inter as well as intra class variability among medicinal plant categories. Recent advancement in image processing and artificial intelligence has enabled automated plant species identification, providing reliable as well as scalable alternative to traditional procedures. This research represents a comparative analysis of Recurrent Neural Network (RNN) and Quantum Convolutional Neural Network (QCNN) for automated medicinal leaf categorization in terms of performance evaluation including accuracy, precision, recall and F1 score. Experimental outcome shows that QCNN significantly outperforms the RNN. RNN exhibits 68% accuracy, macro avg. precision 67%, recall 67%, f1 score 66% and weighted avg. precision 70%, recall 68%, f1 score 68% which is less as compared to QCNN which shows 96% accuracy, macro avg. precision 96%, recall 96%, f1 score 96% and weighted avg. precision 96%, recall 96%, f1 score 96%. Owing to its superior performance QCNN further integrated into a user interface framework to enable real time medicinal leaf categorization. The developed interface offers a user friendly, efficient and scalable platform for medicinal leaf identification application. The suggested system establishes the effectiveness of quantum motivated deep learning model in medicinal leaf image categorization as well as its usage and highlights the potential of QCNN trusted systems for intelligent medical applications.
Abstract: Accurate as well as automated medicinal leaf categorization is a critical chore in medicinal plant species identification. However, manual categorization is time compelling, error prone and mostly reliant on expert skills due to high inter as well as intra class variability among medicinal plant categories. Recent advancement in image processing an...
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Research Article
A Smart Helmet for Accident Detection and Response for Emergency Communication
Issue:
Volume 14, Issue 2, April 2026
Pages:
79-90
Received:
29 November 2025
Accepted:
11 March 2026
Published:
26 March 2026
Abstract: Road Traffic Accidents (RTA) have been a major cause of death and life-threatening injuries globally. The delay in Emergency Response Services (ERS) has heightened the number of death casualties in the event of motorcycle accidents. To address these life-threatening issues, the Smart Helmet for Accident Detection and Res communication device (SHADR) was developed to automatically detect accident, notify the registered emergency contact about the incident and disclose the location of the incident. This concept is designed for rural communities where motocycling activities are predominant. The design was actualized by deploying an accelerometer to detect accident, a load sensor to define when the helmet is being worn, GPS module to ascertain the exact location of the incident, GSM module for call activation and delivering short message service (SMS) of the emergency immediately after the incident has occurred. It leverages the user the opportunity to register the emergency contact by sending information as a coded text to the SHADR. This therefore eliminates the need for interface components and reduces the power consumption level of the device. The outcome of the design implementation demonstrated an efficient operation, with a fast response time for the GPS and GSM communication. Its major contribution stems from the fact that the response time was adequate since it was not affected by network delays and failures associated with communication systems in rural communities. It is a cost effective device which operates with minimum power consumption, the SMS delivery time was adequate and the call functionality was good, at minimum network connectivity. The implementation of SHADR on motorcyclists will greatly reduce casualties from road traffic accidents, provide more data for road traffic studies and give more confidence to road users. Future improvements will require the implementation of this device using 5G technology to improve communication speed and reduce latency for emergency services in urban communities.
Abstract: Road Traffic Accidents (RTA) have been a major cause of death and life-threatening injuries globally. The delay in Emergency Response Services (ERS) has heightened the number of death casualties in the event of motorcycle accidents. To address these life-threatening issues, the Smart Helmet for Accident Detection and Res communication device (SHADR...
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Research Article
Detection and Visualization of Distant Objects: A System Design Using Arduino and Processing Software
Yemna Bchiri,
Wided Saadi*
Issue:
Volume 14, Issue 2, April 2026
Pages:
91-98
Received:
5 October 2025
Accepted:
20 October 2025
Published:
7 April 2026
Abstract: A detection system is an electronic device that uses electromagnetic waves to determine the altitude, range, direction, or speed of objects, whether moving or stationary. In contrast, ultrasonic waves are used instead of electromagnetic waves in ultrasonic detection system. It has many advantages. Its low power consumption, low cost, and ease of implementation and use make it well-suited for various applications, including security systems, object detection and avoidance systems in robotics. In this paper, a low-cost ultrasonic detection system using Arduino microcontroller and processing software was developed. This system makes measurements of distance, direction or speed of both moving and fixed object. The ultrasonic sensors measure the distance to target objects using non-contact technology. They provide accurate distance measurement without causing damage and are easy to use. The sensor receives signals in analog form, which are then converted to a digital format and processed by a microcontroller. The detection distance of the proposed system is tested up to 400 cm for different types of objects: fabrics and aluminum. The distance error between the system and the objects were determined. The results obtained for all types of objects prove that a very low error can be achieved using the proposed design.
Abstract: A detection system is an electronic device that uses electromagnetic waves to determine the altitude, range, direction, or speed of objects, whether moving or stationary. In contrast, ultrasonic waves are used instead of electromagnetic waves in ultrasonic detection system. It has many advantages. Its low power consumption, low cost, and ease of im...
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Research Article
Characteristics of Optimal Wavelengths Selection for High Temperature Quadrispectral Pyrometer in Near-infrared Spectral Range for Metals with Non-linear Emissivity
Ratianarivo Paul Ezekel*
Issue:
Volume 14, Issue 2, April 2026
Pages:
99-109
Received:
10 March 2026
Accepted:
25 March 2026
Published:
13 April 2026
DOI:
10.11648/j.jeee.20261402.14
Downloads:
Views:
Abstract: This article examines the behavior of the quadri spectral method in the design of a pyrometer applicable to the heat treatment of metals. The quadri spectral pyrometer incorporates four different optical filters that filter the four spectra to be used and converge them towards the four detectors of the device. The light energy from these spectra will be converted by the detectors into a processable electrical signal. The application of the nonlinear model known as Temperature by Nonlinear Model (TNL) will calculate and select these four wavelengths. This method applies inverse calculus, exploiting Planck's relation for thermal radiation by setting the temperature and then determining the wavelengths using ordinary least squares. With this model, the four wavelengths will be selected sequentially by modeling the emissivity of the metal as a second-degree polynomial. The obtained wavelengths will be subjected to various criteria to choose the best groups for a suitable pyrometer intended for high-temperature metal treatment. Those criteria are flux sensitivity to wavelength and temperature, standard deviation at temperature, and the minimum difference between two successive wavelengths. The various tests against the criteria, given the non-linearity of the emissivity of metals, characterize the model in high temperatures in order to proceed with such a pyrometer design.
Abstract: This article examines the behavior of the quadri spectral method in the design of a pyrometer applicable to the heat treatment of metals. The quadri spectral pyrometer incorporates four different optical filters that filter the four spectra to be used and converge them towards the four detectors of the device. The light energy from these spectra wi...
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Research Article
IoT-Based Smart Vehicle Accident Detection and Alcohol Monitoring System Using Arduino
Anil Kumar,
Neeraj Marwaha*
Issue:
Volume 14, Issue 2, April 2026
Pages:
110-118
Received:
28 March 2026
Accepted:
13 April 2026
Published:
25 April 2026
DOI:
10.11648/j.jeee.20261402.15
Downloads:
Views:
Abstract: Road accidents are considered one of the major factors for injuries and deaths due to the delayed response of emergency services and driving conditions. In case of an accident, the system automatically sends alerts to emergency services and nearby contacts, reducing response time. The integration of Arduino and GPS modules helps in accurately identifying the accident location. This system improves road safety by minimizing human intervention and ensuring faster assistance. Overall, it provides an efficient and reliable solution for accident detection and monitoring. This is paper proposes an IoT-based smart vehicle accident detection and driver alcohol monitoring system using an Arduino microcontroller. The proposed IoT-based smart vehicle accident detection and driver alcohol monitoring system uses an accelerometer sensor for detecting accidents and an alcohol sensor for monitoring the driver. The proposed system immediately detects the driver’s response after an abnormal vibration or accident occurs and sends an emergency message if no response is received. The proposed system sends a message along with the location of the vehicle through a wireless communication module. Recent advances in Internet of Things (IoT), wireless communication, and embedded systems have led to the development of advanced accident detection and monitoring systems to automatically detect accidents occurring on the roads. Accidents occurring on the roads can be detected through various technologies such as accelerometers, vibration sensors, GPS modules, and communication devices. The proposed system displays the current status of the vehicle using a 16×2 LCD display. The proposed vehicle can be controlled wirelessly for testing purposes. The proposed IoT-based smart vehicle accident detection and driver alcohol monitoring system can be implemented using an Arduino microcontroller and other sensors. Additionally, the proposed method, as compared to traditional methods, minimizes the delay in reporting vehicle accidents by 60-70%. Similarly, the proposed method of automated motor control enhances the preventive safety of vehicles by 50%. Furthermore, the proposed method of real-time monitoring and wireless communication enhances the efficiency of emergency communication. The proposed IoT-based smart vehicle accident detection and driver alcohol monitoring system is compact and can be implemented for various purposes.
Abstract: Road accidents are considered one of the major factors for injuries and deaths due to the delayed response of emergency services and driving conditions. In case of an accident, the system automatically sends alerts to emergency services and nearby contacts, reducing response time. The integration of Arduino and GPS modules helps in accurately ident...
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