Traffic sign recognition is crucial for the safe and efficient operation of autonomous vehicles. While previous research has primarily focused on traffic sign recognition in foreign countries, these studies often face...
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ISBN:
(纸本)9798350352368
Traffic sign recognition is crucial for the safe and efficient operation of autonomous vehicles. While previous research has primarily focused on traffic sign recognition in foreign countries, these studies often face limitations such as differing traffic sign designs, language barriers in textual information, and varying environmental conditions. In this paper, we propose a traffic sign detection and recognition system tailored for Malaysia, utilizing Convolutional Neural Networks (CNNs) and Optical Character Recognition (OCR). In this paper, we propose a traffic sign detection and recognition system utilizing You Only Look Once (YOLO) V8 for object detection and EasyOCR to process textual information on selected traffic signs. Our system achieves a mean Average Precision (mAP) of 0.824 and an average processing time of 1.2 seconds per frame, which is comparable to existing literature. Furthermore, the complexity of our method is significantly reduced, enhancing its potential for real-time processing applications, as evidenced by its efficient processing time.
The growth of the Internet of Vehicles (IoV) has introduced new challenges and opportunities. Among the most crucial considerations is ensuring the safety of passengers and the environment. Connected vehicles offer nu...
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ISBN:
(纸本)9798350333398
The growth of the Internet of Vehicles (IoV) has introduced new challenges and opportunities. Among the most crucial considerations is ensuring the safety of passengers and the environment. Connected vehicles offer numerous benefits, but they are also at risk of fire incidents caused by various factors such as electrical failures, fuel leaks, and collisions. These events can result in devastating outcomes, including property loss, injury, and even loss of life. The conventional fire detection systems employed in vehicles are large, expensive, and consume a considerable amount of power, making them incompatible with the resource-limited environment of the IoV. The present work overcomes these limitations with the introduction of FlameNet, a custom-designed neural network for fire detection. FlameNet not only outperforms existing solutions but also boasts a lightweight design, which contributes to its high computational efficiency, allowing it to run smoothly on low-cost embedded devices with a frame rate of 28 frames per second. Accuracy, recall, precision, and F-measure were used to assess the model's efficiency on both industry-standard fire datasets and a custom-built test set. The results showed that FlameNet performed well on both datasets, with its performance being better on the standard fire test dataset due to its limited image diversity. The performance of the model is encouraging, and the IoT functionality allows immediate visual feedback and a fire alarm in the event of an emergency.
The embedded Graphics Processing Unit (GPU) module, which includes both Central Processing Unit (CPU) and GPU processors, can be easily integrated into radar systems, offering high performance and flexibility. Phased ...
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We propose fitting a distributed realtime Ethernet (RTE) device with more than one RTE communication stack. We target this proposal for increasing flexibility for the manufacturing and system commissioning phases as ...
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作者：
Arul, S.Kavitha, P.Kamalakkannan, S.
School of Computing Sciences Department of Computer Science Chennai Pallavaram India
School of Computing Sciences Department of Computer Applications Chennai Pallavaram India
School of Computing Sciences Department of Information Technology Chennai Pallavaram India
Smart cities are being created all over the world to enhance the safety and quality of life for their residents via the use of technology. Video surveillance, which includes placing cameras at key locations across the...
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It is suggested that visually impaired individuals use an assistive device to receive automatic direction and navigation. The gadget may provide obstacle-free navigation and use real-time image processing to detect im...
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This paper presents a bare-metal implementation of the ieee 1588 Precision time Protocol (PTP) for network-connected microcontroller edge devices, enabling sub-microsecond time synchronization in automotive networks a...
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Unmanned Aerial Vehicles (UAVs), commonly known as drones, have experienced rapid growth and widespread adoption across military and civilian applications in recent years. This paper offers a comprehensive survey of U...
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Reflecting Intelligent Surfaces (RISs) have garnered considerable attention as a viable solution for wireless communication systems in recent years1. RISs operate by manipulating the phase and amplitude of incoming si...
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Managing traffic data involves strategies to keep roads running smoothly, improve safety, and make transportation more dependable. How traffic systems work and how well they perform are important for a country's e...
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