Browsing by Author "Ohize H.O"

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Design and Development of An IoT – Based Multi – Health Vital Signs Monitoring System
(I3C 2024, 2024-04-22) Adegboye N.J; Dauda U.S; Ajiboye, Johnson Adegbenga; Ohize H.O; Adegboye B.A
This study presents the design and development of an IoT-based multi-health vital signs monitoring system that can monitor a patient’s basic health physiological parameters in real-time. In this system, four (4) sensors were used to capture the data from the patient. These are body temperature sensor, electrocardiogram (ECG) sensor, accelerometer sensor and the eye blink sensor. The hardware modules were interfaced with the liquid crystal display (LCD) to display the required data. Memory modules stored the designated phone numbers. The GSM module retains connectivity with the cellular networks acting as SMS receiver, which sends data on the patient’s vital signs. The LCD displays the data, which can be seen through the IoT. The microcontroller was programmed using C++ programming language and connects all sensors. This enabled conveyance of data on the patient’s health condition via IoT to the doctor for further processing and analysis.
DEVELOPMENT OF MODEL METRICS FOR INDIVIDUALS AND PAIR PROGRAMMERS AMONG SOFTWARE DEVELOPERS IN AN AGILE ENVIRONMENT
(2023) Ajiboye M.A; Ajiboye, Johnson Adegbenga; Audu W.M; Ajiboye D.J; Ohize H.O; Majin R.N; Abolarin M.S
In this work, maintainability as a function of time to correct codes was examined among various categories of software developers. Deliberate errors, ranging from two to ten, were introduced into sets of agile codes written in python programming language and given to 100 programmers each in the groups of Individual Junior, Individual Expert, Random, Expert pairs, junior pairs and Junior Expert pairs. The time spent to correct the errors was analysed using regression model for prediction. Bivariate correlation was used to check the relationships between the number of bugs in projects and the time spent to correct the errors. The correlation between the number of bugs and time of debugging was highly significant, strong and positive. This revealed that the time spent in correcting system software errors increased significantly as the number of bugs increased. Linear, logarithmic, inverse, quadratic, cubic and exponential regression models were used to generate metrics with time spent on error as dependent variable and number of bugs as independent variable for each of the pair and individual programmers. On the average, cubic model gave the highest R2 value of 0.639 in comparison to other models. Therefore, Cubic model gave the best fit as it explains the patterns of the relationship between the dependent and independent variable most appropriately.
Wireless Sensor Networks: State of Arts
(IEC 2023, 2023-03-21) Okafor A.C; Dauda U.S; Kolo J.G; Ohize H.O; Ajiboye, Johnson Adegbenga
The enhancement of the Wireless Sensor Network (WSN) have made technology much easier and is impacting on all fields of endeavours. The invention of WSN and the present advancement especially in the field of Engineering is the main focus of this article. The paper has also enlightened the current state of the WSN in data collection procedure. The marketplace of the WSN and its growth has been elaborated in the paper along with the future scope and challenges.