Unveiling the support of 3D representation in mobile devices for pedestrians navigation aid

The problem of getting lost anywhere by pedestrians that uses mobile device will be reduce when 3D representation (Map) of an environment is provided in his/her mobile devices. Over the years, there are growing number of pedestrian navigation aided application for mobile devices, Unfortunately certain issue concerning the use of mobile devices as a navigation aid, in regards to the pedestrian behavior while-on-the-go in a different environment under different condition were still not properly address. Moreover, we don't know whether it safe or not interacting with mobile device while walking around and some other related support. This paper consider pedestrian behavior under different conditions in different environment while on the go and proposed the design of an application in Android platform with 3D representation meant for mobile device as a pedestrian navigation aid and investigates user's satisfactions with the applications interface design quality. The result shows that pedestrians consider interacting with the application as safe while using it in a calm condition in an unknown location and also its best usage is for mostly when it provides an exploration of environment rather route only

3d graphics visualization for interactive mobile users navigation

3D map visual navigation comes into being as a result of the drawbacks in two-dimensional mapexhibit navigation approaches, which are the most commonly available. The information provided for user in 2D are mostly limited with insufficient presentation and lack of interaction. However, applying 3D techniques surely yield realistic navigation fields. At first glance, it may seem like dealing with 3D map in mobile devices for navigation only present a single particular context (that is user's location). This initial perception fails to take into account other context like visualization, navigation and interactive technological capabilities. Thus, previous attempts at implementing realistic solutions to the visualization of complex 3D scene in mobile devices' interactivity of more than two user's navigation within a scene at the same time were faced with so many obstacles, which unfortunately were left unsolved, despite the enormous ongoing research. This paper aimed at providing solutions to the functional mobile 3D visual navigation system, in particular, one in which mobile devices' users will navigate within an environment and interact among themselves while tracking their position in real-time. The solutions will be provided through implementing an efficient, scalable dynamic entity navigation solution by means of Bi-A* pathfinding algorithm. As a result, a 3D model of a real place in a mobile device will be produced, for user's navigation which will makes it easier to perceive proportions, distances, and recognize landmarks, at the same time interacting with other users

License plate detection and segmentation using cluster run length smoothing algorithm

For the different types of license plates being used, the requirement of an automatic license plate recognition system is different for each country. In this paper, an automatic license plate detection system is proposed for Malaysian vehicles with standard license plates based on image processing and clustering. Detecting the location of license plate is a vital issue when dealing with uncontrolled environments and illumination diffi-culty. Therefore, a proposed algorithm called Cluster Run Length Smoothing Algorithm (CRLSA) was applied to locate the license plates at the right position. CRLSA consisted of two separate proposed algorithms which applied run length edge detector algorithm using 3 × 3 kernel masks and 128 grayscale offset plus a three-dimensional way to calculate run length smoothing algorithm, which can improve clustering techniques in segmentation phase. Six separate experiments were performed; Morphology, CRLSA, Clustering, Square/Contour Detection, Hough, and Radon Transform. From those experiments, analysis based on segmentation errors was constructed. The prototyped system has accuracy more than 96%

Parental involvement and awareness using Malaysian’s Smart School Management System

Parental involvement is one of the factors that effectively contributes to students’ learning. One of the existing problems in Malaysian Smart Schools is that parents are not fully utilizing the Smart School Management System (SSMS) due to lack of information, time, training, computer incompetence, and unrecognized features and functions in SSMS. The purpose of this paper is to assess the parental involvement in using SSMS at Malaysian Smart Schools. This paper also ascertained the need for training to utilize SSMS, and identify barriers in using SSMS while improving communication between parents and staff at Smart Schools. Although the integration of Information and Communications Technology (ICT) in Malaysian Smart Schools is relatively high, this study found that there was a need to introduce SSMS to parents as stakeholders and get them more involved in using the available resources at Smart Schools. Thus, this study proposed a number of guidelines for Malaysian’s Ministry of Education and Smart Schools in order to create an awareness and get parents engaged in their children’s education by using SSMS

Utilization of mobile phone sensors for complex human activity recognition

Activity recognition is a significant part of pervasive computing as it can be employed in a wide range of fields which include eldercare and healthcare. While previous efforts have proven to be successful in identifying simple human activities, the means for identifying complex human activities remains an on-going effort. It has been established that more often than not, in an actual circumstance, human activities are conducted in an intricate mode. The objectives of this study are (a) to examine the utilization of solely the sensors of a mobile phone to distinguish complex human activities and (b) to enhance the complex activities recognition capacity of mobile phones through the application of multiple or other forms of sensors. This endeavour reassesses earlier studies on mobile phone utilization for complex activity recognition with the emphasis on schemes directed at smart home applications. An overall configuration for a human activity recognition (HAR) scheme, as well as an analysis of the latest investigations related to the use of mobile phones for complex activity recognition is also included in this paper. We conclude with a discussion on the results obtained and the forwarding of our proposals

The web of things - Challenges and enabling technologies

The Internet of Things (IoT) is an active research area, focusing on connecting real-world things over TCP/IP. This trend has recently triggered the research community to adopt the interoperability of the Web (HTTP) as an application platform for integrating ‘things’ on the Internet. Harnessing physical things into the virtual world using Web standards is also enriching the arena of conventional Web services to unleash data and functions of real-world things as service providers and consumers on the Internet. This evolution of the Web as a highly interoperable application platform for connecting real-world things has raised many research challenges and problems, leading to the fast growing research area called the Web of Things (WoT). Current research on WoT is a catalyst for the realization of IoT, opening up the possibilities of creating ambient spaces (AS), where people and things seamlessly communicate over the Web. In this chapter we discuss the state of the art in WoT research, focusing on the various challenges, and enabling technologies that are driving this research. We discuss architectural frameworks, models and technologies to build applications for future ambient spaces with the WoT. We present case studies that reflect the feasibility and applicability of the WoT technology. We also discuss future trends and research directions within this domain to throw light on existing problems and challenges.Sujith Samuel Mathew, Yacine Atif, Quan Z. Sheng, and Zakaria Maama