Automatic face recording system based on quick response code using multicam

Julham, Julham; Lubis, Muharman; Lubis, Arif Ridho; Al-Khowarizmi, Al-Khowarizmi; Kamil, Idham

doi:10.11591/ijai.v11.i1.pp327-335

Cited by 3 publications

(4 citation statements)

References 38 publications

(38 reference statements)

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“…Another research [15] is covered that 10 am to 3:59 pm significantly reduces the chance of fatal injuries. Some researchers have used AI-based models for the early detection of intuition [16], [17]. Some studies have shown that heavier cars increase the chance of pedestrian fatalities [18].…”

Section: Related Workmentioning

confidence: 99%

Comparative analysis of influencing factors on pedestrian road accidents

Hafeez

Sheikh²,

Alshammari³

et al. 2023

Bulletin EEI

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Road accident data includes detailed information about incidents that occurred, such as where they happened, the severity of the accident, and the number of people on the road at the time. Such information is useful in determining the causes of accidents and developing potential countermeasures. This research aims to determine the factors that contribute to pedestrian fatalities and injuries in traffic accidents. This study examined 150 pedestrian-vehicle accidents that took place between 1990 and 2021 in forty countries. Eleven factors have been identified as the major causes of accidents. The categorical principal component analysis (CATPCA) technique is used to reduce the number of dimensions and identify the elements that contribute to accidents. The eleven variables are classified into three groups: human factors, roadway environment, and vehicle attributes. The study found that car speed, weather, lighting, traffic conditions, area types, accident locations, and road conditions all had a significant impact on pedestrian accidents and fatalities. The findings show that a pedestrian's state (walking, running) and intention significantly increase the risk of serious injuries and death. The analysis of the driver's status suggests that the driver's intentions may also play a role in car accidents.

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Section: Related Workmentioning

confidence: 99%

Comparative analysis of influencing factors on pedestrian road accidents

Hafeez

Sheikh²,

Alshammari³

et al. 2023

Bulletin EEI

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“…Where Faster R-CNN which is a method of object detection that is able to detect an object captured by the camera [21][22] [23]. The workings of the prototype start with the process of detecting whether the object is wearing a mask or not, then if it is wearing a mask, whether it is using a standard mask or not, then the data is sent to the cloud to be sent to the IoT device [24]. So, the door is only open for those who wear masks and use standard masks.…”

Section: Fig 2 Research Flow Mapmentioning

confidence: 99%

“…Where Faster R-CNN which is a method of object detection that is able to detect an object captured by the camera [21][22] [23]. prototype work begins with the detection process on mask detection or not using and whether the mask is used is standard or not so as to support prototype data stored in the cloud network [24]. After the prototype was developed in this paper, the application that was carried out was to provide a detection signal to IoT devices in carrying out automatic door opening for standard mask and mask users.…”

Section: Introductionmentioning

confidence: 99%

The Role of Faster R-CNN Algorithm in the Internet of Things to Detect Mask Wearing: The Endemic Preparations

2023

International Journal of Electronics and Telecommunications

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Faster R-CNN is an algorithm development that continuously starts from CNN then R-CNN and Faster R-CNN. The development of the algorithm is needed to test whether the heuristic algorithm has optimal provisions. Broadly speaking, faster R-CNN is included in algorithms that are able to solve neural network and machine learning problems to detect a moving object. One of the moving objects in the current phenomenon is the use of masks. Where various countries in the world have issued endemic orations after the Covid 19 pandemic occurred. Detection tool has been prepared that has been tested at the mandatory mask door, namely for mask users. In this paper, the role of the Faster R-CNN algorithm has been carried out to detect masks poured on Internet of Thinks (IoT) devices to automatically open doors for standard mask users. From the results received that testing on the detection of moving mask objects when used reaches 100% optimal at a distance of 0.5 to 1 meter and 95% at a distance of 1.5 to 2 meters so that the process of sending detection signals to IoT devices can be carried out at a distance of 1 meter at the position mask users to automatic doors.

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“…Before outputting music, the mp3 file required for voice output was placed in the raw folder. If the conditions for color recognition were satisfied, a voice file was output [24]- [28].…”

Section: Voice Outputmentioning

confidence: 99%

Security system using mobile image processing and color recognition for the visually impaired

Rhee

Cho

2022

IJEECS

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Voice technology at traffic lights or bus stops is emerging for the independent daily life of the blind, but there are few technologies that efficiently help the blind, such as knowing the color of clothes to wear before going out or entering the bus stop at once. To support such difficulties, this paper proposes a method that can be helped by using a smartphone application to distinguish the color of outdoor clothes. Smartphones, which are hardware-based for applications, have the advantage of predictable results, ease of transportation, independence from direct use, and personal support for the blind through various applications. However, there are very few applications to help the blind. This paper proposes the development of an application that can efficiently and independently recognize colors and images at anytime, anywhere by scanning images using smartphone cameras and converting them into bitmap images. Finally, the effects that can be expected through the application proposed in this study are described.

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Automatic face recording system based on quick response code using multicam

Cited by 3 publications

References 38 publications

Comparative analysis of influencing factors on pedestrian road accidents

Comparative analysis of influencing factors on pedestrian road accidents

The Role of Faster R-CNN Algorithm in the Internet of Things to Detect Mask Wearing: The Endemic Preparations

Security system using mobile image processing and color recognition for the visually impaired

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