Users of travel applications can arrange services that are referred to as “m-Travelling” by researching places, locating affordable flights and lodging, and booking such services. It is found that there is a current gap in the market for a comprehensive and user-friendly platform that promotes domestic tourism meanwhile get accurate information easily. Most travel apps also expect their users to have stable and strong internet connections and the apps are found to be not user-friendly. The aim of this study is to develop a travel application for tourism sites in the Selangor area. Data were collected from local citizens of Selangor and local travellers that travel a lot in Malaysia. It was found that most of the respondents were experienced with travel mobile apps and most of them were neutral with the problems faced as the casualties may not drastically affect the user experience throughout the usage of travel apps. This study concludes that the development of travel mobile applications can be an effective way to support Malaysian tourism destinations and promote domestic tourism, encouraging to exploration of appreciation the local culture, heritage, and natural beauty to provide users with a convenient and accessible platform. The apps include information about local attractions, hotels, restaurants, transportation, and other essential travel services. Overall, the development of a travel mobile application for local Malaysian tourism destinations will promote cultural awareness and appreciation and provide users with an enjoyable and memorable travel experience through social technological developments.
Smart parking is an essential component of smart cities as it provides numerous benefits, including improving transportation systems’ efficiency, reducing traffic congestion, and enhancing residents’ quality of life. Real-time parking guidance systems are commonly used in private parking to increase safety and better use the available parking space. However, many countries, such as Morocco, have limited private parking, resulting in a significant percentage of on-street parking. Onstreet parking does not have designated parking slots, causing users to park their vehicles in a way that affects parking capacity. This paper proposes a solution to this problem by presenting a guidance system for parallel on-street parking with two perspectives: a bird’s-eye view and a high-view camera that captures images of vehicles from the side or top. Our suggested system utilizes a real-distances optimization method to guide users during the parking process. We utilized the YOLOv7 object detector and k-NN algorithm in this approach. Moreover, the system incorporates fuzzy logic to help it understand the situation and make decisions based on the distances and time of maneuvering.
Gait, a biometric trait, is a highly valuable indicator that enables the identification of an individual from a significant distance and without requiring direct physical contact. Due to its unique attributes that are absent in other commonly used identifiers such as fingerprints and iris recognition, gait recognition has become increasingly prevalent and widely adopted in various areas where it is feasible to utilize video reconnaissance frameworks. As computer vision techniques have advanced, there are now numerous methods for recognizing individuals through their movements in the video, utilizing both traditional biometric characteristics such as the human skeleton, its silhouette, and its changes during walking, as well as unique signals. This paper explores the use of gait energy extraction as a fundamental approach for discriminating between different gaits, an analysis of the classification algorithms employed, and a comparison of the methods based on accuracy, gait datasets, as well as their characteristics, issues, and challenges encountered in the development of gait recognition systems. and identified the prevailing methods employed by researchers as GEI (Gait Energy Image) and FDF(Frequency Domain Feature ). Followed by GENI (Gait Entropy Image), CGI (Chrono-Gait Image ), and GFI(Gait Flow Image ). Among the available datasets, CASIA and OU-ISIR as the most extensively used and comprehensive datasets in the field. Using convolutional neural networks, they demonstrated that CGI achieved the highest level of accuracy when applied to the CASC-B dataset.
In most cities of the Philippines, numerous law enforcement checkpoints are stationed as a vital part of securing public order and road safety. As the country’s population grew, we saw a rise in the volume of vehicles on public roads. In areas where a checkpoint is located, the usual flow of traffic becomes congested while officers conduct their standard operating procedures in the verification of vehicles. This study focuses on the development of a motor vehicle plate recognition system for Philippine law enforcement checkpoints. You Only Look Once (YOLO) v4 was used to locate and detect motor vehicle plates through a video feed from an external camera installed in the local machine. OpenCV was used to preprocess the cropped images while Tesseract-OCR was used to extract the motor vehicle plate number as text. The extracted plate number was then used to retrieve the motor vehicle details from a local database. A mean Average Precision (mAP) of 97.67% was achieved after training the model. The experimental results and performance analysis of the study show that the proposed solution is capable of identifying motor vehicles through the recognition of motor vehicle plate numbers.
LIDAR is a well-known method for capturing points at extremely high resolution, but its resolution is insufficient for tasks like object recognition, façade categorization, and assessing the behavior of feature extraction in terms of edges, fractures, and changes. This review paper for coastal monitoring study uses the Terrestrial Laser Scanning (TLS) 3D LIDAR data cloud to extract linear features, locate and categorize fractures, and apply the line effect technique. Maybe shorten the time it takes to analyze data, manage a massive data TLS point systematically, eliminate irrelevant data, and investigate different LIDAR applications. Thus, with the addition of TLS 3D LIDAR coastal monitoring and Geographic Information System (GIS) application, user friendly understanding changes in natural disaster issues, coastline management efficiently, erosion prevention risk and subsequent action plans for decision makers or the general public are countered.
