Research Articles in Computer Science

Permanent URI for this collectionhttps://repository.nileuniversity.edu.ng/handle/123456789/50

Browse

Subject: search.filters.subject.GPS

Search Results

Now showing 1 - 2 of 2
  • No Thumbnail Available
    Item
    Four-Factors Authentication Algorithm For Preventing Fake Attendance
    (International Conference on Electronics Computer and Computation, 2019-02-02) Asim Balarabe Yazid; Moussa Mahamat Boukar; Salisu Ibrahim Yusuf
    Taking attendance is a day-to-day chore for every organization, human resources, and class teachers, traditionally people take attendance manually either by calling out names or allowing the user to sign the attendance sheets or clock in and out. The problem, however, people most likely sign the attendance on behalf of their colleagues that are absent. This makes the traditional method very vulnerable and may affect the integrity of the system. Researchers come up with different ideas and methods of minimizing fake attendance to improve efficiency in terms of integrity, time and cost. After reviewing the existing system’s strength and vulnerabilities, we are proposing a multi-factor authentication algorithm which makes use of QR code, GPS, and Facial recognition. The user will make use of their personal mobile phone. The research of this proposed is still ongoing, we are hoping the proposed technique can be applied to various attendance systems such as schools, universities, and organizations.
  • No Thumbnail Available
    Item
    Analysis of Bad Roads Using Smart phone
    (IEEE, 2019-02-02) Moussa Mahamat Boukar; Steve Adeshina
    Developing nations are faced with a lot of bad roads with potholes of different debt ranges, the maintenance and rehabilitation process by government agencies is an ongoing effort that requires periodic bad road inventory to guarantee safety. Bad roads are either identified by government agency’s survey teams or individual who volunteer to report these conditions to the authorities. Our research provided a simple but effective solution to aid in automatically reporting bad roads using smart-phones through measuring the pavement profile based on the vibration of a moving vehicle. In this article, we will explain how we used some a smart-phone in reading the vibration pattern, GPS location, speed and direction of a vehicle that drives through a pothole, these parameters are periodically streamed to a cloud application. We used standard deviation to measure the level of dispersion around a segmented set of streamed vehicle vibration to identify potholes of different sizes, we also used Artificial Intelligence - supervised learning algorithm (classification) to reduce the false positive error rates due to human behaviors. The final results show a distinct vibration levels between small pot-holes, speed bumps and big pot-holes, these values are displayed on map application to visualize the geographical locations of these pot-holes (Google maps)