Existing smart rest room automated faucet systems operate on traditional control theory, with absolute control value, irrespective of its degree of accuracy. For example, a hands-free hand wash basin may be programmed to release water when an object is about 2cm close to the infrared sensor. This absolute control value has pitfalls such as, ascertaining the quantity of water required for each operation, without activating the water flow switch to release water at maximum rate, leading to wastage of water resources. In order to develop an efficient and accurate smart rest room automated faucet system that will release water at an approximate quantity as required for varying condition, this research paper delves into employing a data-centric model for understanding and designing a smart rest room automated faucet system, that is more accurate in operation and properly utilizes water resources. To achieve this goal, we first designed a fuzzy model using MATLAB, for the proposed smart rest room automated faucet system, and then implemented the model on embedded atmel328 microcontroller, interfaced with an infrared obstacle sensor and an electronic flow control switch to automate rest room faucet activities. In order to understand and improve its operation, data logged from the system infrared sensor for 3cm distance, was mined for proper understanding of the system operational accuracy. During which the result indicated proper water utilization at various rate of water dispensation, as a function the nearness of the object to the sensor. This supports the improvement promised by the proposed system, when adopted in existing smart rest room automated faucet systems design and re-design.

Edge detection is important in image processing to aid operations such as object classification and identification amongst others. This is soley to improve interpretability of the image. Common edge detection techniques such as Sobel, Prewittt, Canny, Laplacian of Gaussian (LOG), Robertss and Zero-Crossing has attracted the attention of researchers to perform a comparative analysis on these techniques excepts fuzzy, using different type of images. Fuzzy logic based edge detection algorithms development and comparison with existing algorithm became important due to the fact that the pixels’ boundaries identifying image degs are crystal clear as expected, hence other edge detection algorithms using crisp values will be omitting some vital information pixels, this impairs the quality of the image edge detected and further application through proper interpretation. This research further extends the investigation of edge detection techniques optimality, through comparing Sobel, Prewittt, Canny, Laplacian of Gaussian (LOG), and Robertss edge detection algorithms with our proposed fuzzy based edge detection algorithm designed using MATLAB. The result indicated that the novel fuzzy based edge detection algorithm developed in this research outperforms the Canny, Sobel, Prewittt, Robertss and LOG edge detection algorithms in three different experiments with different images

Examination malpractice is a dishonest conduct by a candidate prior to examination and through the examination to attain success effortlessly. Examination malpractice is a plague that heralds severe menace for the nation and has constantly remained a bother in the Nigerian educational system. Supervising examination has been manual since the inception of examinations in Delta State University. Likewise, most of the State Universities and Federal Universities in Nigeria utilize manual supervision of examination though visit by examination supervisors. Thus, this research paper presents a virtual examination supervision system (VESS) that checks candidates who are writing examination. VESS is an information technology approach towards curbing the problem of cheating in examination hall, using computer vision motion detection technique on real-time IP-camera video stream from examination. The implementation and practical experiment of VESS was carried out in Delta State University and result analysis indicated shift in position by examinees during examination at every milliseconds, which is difficult for human eye to monitor accurately and other cases such as copying and impersonation. These further proved that VESS is a solution to mitigating examination malpractice of all kinds and protection of the invigilators. Furthermore, the stored result in VESS can be used as evidence to punish the culprit.